The AI boom is creating huge demand for training data and the expensive computers that power it. Grayscale has identified three cryptocurrencies targeting these growing needs. Their prices, however, tell very different stories.
In an October 23 research note, Grayscale Head of Research Zach Pandl highlighted DATA Network (DATA), USD.AI (CHIP), and Pearl (PEARL).
Each addresses a different part of AI infrastructure, from supplying training data to financing computer chips and earning revenue from computing power.
Frontier tech and crypto are converging.
Crypto projects part of the AI buildout:$DATA → Licensing and verifying AI training data.$CHIP → Financing GPU hardware through onchain loans.$PEARL → Merging proof-of-work with AI compute, letting miners earn rewards while powering… pic.twitter.com/XKdhrNxguN
— Grayscale (@Grayscale) October 23, 2026 1. DATA Network (DATA): Selling the Data AI NeedsAI models learn from images, videos, and voice recordings. DATA aims to collect this material with permission, license it to AI developers, and reward contributors.
On October 12, the Sui Foundation announced a $30 million investment in the network. DATA also plans to migrate to Sui, transferring existing tokens one-for-one.
Yet investors have seen little relief. DATA has fallen 42.07% over 90 days to $0.15243, including a 34.65% decline over the past month.
Data Network Price Chart. Source: BeInCrypto2. USD.AI (CHIP): Financing Expensive AI ChipsAI requires powerful graphics processors, or GPUs. USD.AI helps computing companies borrow money against this hardware and its future income, using blockchain-based lending pools.
In August, Bullish announced a $100 million financing facility supporting USD.AI’s GPU loans.
CHIP has gained 47.98% over 90 days to $0.04386, although it remains roughly 69% below its April peak.
3. Pearl (PEARL): Making GPUs Earn TwicePearl proposes using the same computing capacity for AI workloads and blockchain mining. Providers could earn AI revenue while collecting tokens for securing the network.
PEARL is the standout performer, surging 528.24% in 90 days to $2.00. However, it has retreated about 19% from its October 21 record of $2.46.
Supply also poses a risk. Around 1.2 million new tokens are estimated to enter circulation daily, while its $4.2 billion fully diluted valuation far exceeds its $713 million market cap.
PEARL Gained Over 240% Year-to-Date. Source: CoinGeckoGrayscale sees potential in all three projects, although their success remains uncertain.
“Their long-term relevance will depend on adoption and competitive economics. We are keeping an eye on them,” Pandl said.
Anthropic, OpenAI, and Mistral each carry a tracker peg inside the last four days of October, and not one of those dates is on the record – the calendar everyone quotes is running on vendor silence again.
Lena ParkForkast mind
No vendor has confirmed a release for the window that now sits between October 28 and October 31. As of October 24, none of the three labs with a peg inside it has put a formal announcement on the record. What has compressed is not a schedule but a set of expectations, and the gap between the launch calendar deployers quote to each other and the silence of the vendors whose names sit next to those dates is wider than it looked when this desk mapped it on October 14.
Fetching the surfaces shows the gap. Anthropic’s newsroom was fetch-verified on October 24 and carries no pending frontier model release: the newest entries are two October 22 posts, on Agent Skills and a life-sciences open call, while the latest model announcement on the page is still Claude Haiku 5.5 from October 7. OpenAI could not be verified the same way – its newsroom and blog both returned an HTTP 403 challenge at fetch, so the no-announcement reading there rests on a secondary search, not on the source. That distinction is the method: absence counts only when you can name the surface you checked and how it answered.
Behind all three pegs sit tracker-class projections, the reliability class that carries zero vendor backing. The OpenAI estimate has slipped twice since the October 14 record – from about October 19, to October 22, and now to about October 29. Anthropic sits at about October 28, unchanged from the same record. These are independent estimates converging on four days, not a coordinated industry event, and neither date has a vendor’s name anywhere near it.
StepFun set the precedent. Its October 15 vendor promise – the only dated, vendor-backed commitment on that calendar – failed to materialize, with the repository 404 error and the license still unpublished when the date passed. If the one promise carrying a vendor’s name could slip, three estimates carrying no vendor’s name have even less holding them up.
The Mistral peg is the most concrete of the three. Its Hugging Face card was fetch-verified on October 24: an upcoming-release page with a countdown of seven days, a Current ETA of October 31, 2026 at 15:00Z, a stamp reading “the release date may still change,” and 939 people waiting. The card states that open weights drop at the end of the month. As of October 24 – Day 23 of 31 – the weights and the commercial license remain unpublished, and the commercial license question rides the same window.
The cost of the gap is not abstract. A team that schedules a migration, a pricing change, or a benchmark re-evaluation around a date that exists only in a tracker absorbs the delay as engineering time and idle planning – the same bill StepFun’s followers paid on October 15, when the weights they had built a week around simply were not there. Multiply that by three pegs in one window and the last four days of October become a shared planning hazard rather than a launch party.
For deployers, the compression turns the calendar into something other than a planning tool: a read on how long vendors are willing to hold a date while everyone else plans around it. Three pegs in four days, none on the record, is not a schedule – it is a forecast feeding on itself. When the announcements land, the interesting number will not be the dates. It will be how many plans were built on estimates nobody signed.
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The general partner confirmed Thursday evening that he will start a company, hours after Chris Dixon said the firm's newest crypto fund can now back AI and other frontier startups.
a16z's crypto team becomes a16z Frontier as Ali Yahya announces his exit
Posted October 23, 2026 at 8:05 pm ET.
The newest fund at a16z Crypto is no longer limited to crypto. Managing partner Chris Dixon wrote in a post at noon ET Thursday that the firm is “expanding the scope of our new fund beyond crypto startups to the broader category of frontier startups,” meaning bets on new technologies whose markets could need years to form.
The team now goes by a16z Frontier, and its old a16zcrypto.com blog address redirects to a new domain. Dixon described the move as “an expansion” and said the firm “will continue to invest in crypto and related ventures and advocate for sensible crypto regulation.”
a16z closed its fifth crypto fund at $2.2 billion in May, lifting its total across five crypto funds to $9.8 billion. Dixon’s post did not give a fund size or say how much of the capital could go outside crypto.
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Why Dixon dropped the label
Dixon argued that blockchains have become less visible as they spread, with Wall Street firms and fintechs now shipping products on them. “The label matters less now,” he wrote. In his view, it “makes more sense to define companies by what they do rather than by the technologies they use.”
He listed brand-new uses of AI, robots and other autonomous machines, biology and medicine, and startups that mix software, hardware and services, along with networks where people and intelligent agents transact. Crypto, he argued, can give those systems economic capabilities of their own, including machine-to-machine transactions. “These are examples, not boundaries,” he wrote.
Dixon said he will share the fund’s leadership with Eddy Lazzarin and Guy Wuollet, both general partners, and with a16z co-founders Marc Andreessen and Ben Horowitz.
Yahya heads out
General partner Ali Yahya wrote in a post on X at 7:33 p.m. ET Thursday that he has “decided to leave @a16z, move to SF, and start a company.” The Information had reported that morning that Yahya told some investors he planned to leave.
Yahya joined Dixon in 2017 from Google, where he says he worked on robotics as a Google Brain engineer. When a16z promoted him to general partner in 2021, it called him the “first full-time member of the crypto team.” He said his company is early but will focus on “building infrastructure that enables open software ecosystems,” starting from the view that AI use will move from one person talking with one agent to many people and agents working together. He called himself “forever an a16z superfan” and thanked the firm’s partners by name.
Crypto investor Paradigm announced a $1.2 billion fund in July and said it now works “across AI, robotics, and other frontiers.”
Related Listen: Why Ali Yahya Believes That the Chain That Protects Private State Will Win
AI-assisted content: This article was produced with the assistance of AI tools and was reviewed, edited, and fact-checked by a member of the Unchained editorial team before publication.
Andreessen Horowitz, known in the industry as a16z, has announced a significant shift in its investment focus, broadening the mandate of its newest fund beyond cryptocurrency and blockchain startups to include a wider range of “frontier startups.” This change marks a move into sectors like artificial intelligence, robotics, and cutting-edge biotechnology where new markets may take years to develop.
a16z rebrands, expands vision beyond cryptoThe firm’s crypto-focused team will now operate under the name a16z Frontier. The group’s previous a16zcrypto blog now redirects visitors to a newly branded domain, underscoring the transition. In a blog post, managing partner Chris Dixon described the expansion as an evolution rather than a departure, emphasizing that investments in blockchain and digital assets will continue alongside ventures in these emerging technologies.
Dixon noted that as blockchain technologies become more integrated into traditional finance and fintech products, their underlying presence is less visible to users. He believes that companies should increasingly be defined by their functions and impacts, rather than by the specific technologies they use.
Dixon wrote that the team is “expanding the scope of our new fund beyond crypto startups to the broader category of frontier startups,” with ongoing support for crypto and related sectors, while also advocating for balanced regulatory frameworks.
The fund will target companies developing not only crypto applications but also new uses for AI, robotics, autonomous systems, biotechnology, and multidisciplinary startups that blend software, hardware, and services. Dixon argued that crypto technology could enable economic capabilities such as machine-to-machine transactions within these new systems, but stressed that these areas are just examples, not strict boundaries.
The leadership of the new fund will be shared between Chris Dixon, general partners Eddy Lazzarin and Guy Wuollet, and a16z co-founders Marc Andreessen and Ben Horowitz. Andreessen Horowitz is a Silicon Valley venture capital firm widely recognized for its significant influence in tech and crypto investing.
Mini dictionary: a16z (Andreessen Horowitz) is a leading venture capital firm based in Silicon Valley, known for early investments in prominent technology and blockchain startups.
Leadership changes and industry contextGeneral partner Ali Yahya announced on X that he is departing a16z to move to San Francisco and start a new company. Yahya originally joined a16z’s crypto team in 2017 after serving as a robotics engineer at Google Brain, and became the group’s first full-time crypto team member in 2021. He stated that his next venture will focus on building infrastructure to support open software ecosystems, specifically as AI evolves to encompass collaborative interactions between multiple people and agents. Yahya expressed gratitude to his colleagues and described himself as a “forever a16z superfan.”
Yahya shared that his new company aims to enable “building infrastructure that enables open software ecosystems,” starting from the belief that AI will move beyond one person and one agent to collaborative networks of participants.
This expansion at a16z comes as other major players in the crypto investment space, such as Paradigm, have also broadened their scope. In July, Paradigm announced the launch of a $1.2 billion fund to invest across sectors including AI, robotics, and additional frontier technologies, reflecting a wider trend among leading venture firms.
FirmLatest Fund SizeFocus Areasa16z$2.2 billion (crypto fund V)Crypto, AI, robotics, biotech, frontier techParadigm$1.2 billionCrypto, AI, robotics, frontier techa16z’s fifth crypto fund closed at $2.2 billion in May, bringing the firm’s total crypto-focused capital to $9.8 billion. However, specific details about the size of the new, broader fund or the portion devoted to non-crypto investments have not yet been disclosed.
The latest developments highlight a growing consensus among leading venture firms that the intersection of digital assets, AI, and advanced technology presents new investment frontiers as traditional labels become less relevant in a rapidly evolving market.
Sky has reported $30.8 million in September gross revenue and its first 2.86 million SKY token burn, alongside Galaxy’s $100 million sUSDS treasury allocation.
Summary
Sky’s September gross revenue reached $30.8 million, up 49.7% from a year earlier. Galaxy allocated $100 million to sUSDS and approved the token as institutional loan collateral. Sky completed its first Stage 2 burn, permanently removing 2.86 million SKY from circulation. Grove and Galaxy’s $500 million credit facility reached 75% utilization, financing $375 million in loans. Sky Frontier Foundation’s September financial and operational update put total stablecoin supply at $9.70 billion and protocol collateral at $11.41 billion as of Sep. 30. Published on Oct. 23, the briefing brought together monthly financial results, institutional lending activity and the first completed burn under its Stage 2 capital allocation framework.
The September Financial & Operational Update is live.
Galaxy’s $100M sUSDS allocation. Grove’s warehouse facility at 75% utilization. The first SKY burn.
Alongside the announcements: protocol financials, reserve contributions and governance updates.
Read the full update ↓ https://t.co/mme2gposdv
— Sky (@SkyEcosystem) October 23, 2026 Sky revenue rises as reserve contributions turn positive Gross protocol revenue grew 49.7% from September 2025, while total stablecoin supply rose 27.6% and collateral grew 25.3%, the Foundation reported.
Net protocol revenue reached $12.32 million, compared with a $5.41 million loss a year earlier. The report cautioned that expense classifications affected that comparison. September 2025 included $14.40 million in legacy operating expenses that are now largely inactive.
The figures therefore combine revenue growth with changes in the expense base. The Foundation did not present the full improvement in net revenue as growth from continuing operations on an unchanged accounting basis.
After expenses and revenue allocations, the protocol remitted $7.15 million to Sky Reserves. A year earlier, the corresponding figure was negative $17.26 million.
September was the first full month of Stage 2, and the revenue allocation covering SKY buybacks and USDS payments to SKY stakers reached $5.08 million. August’s allocation was $2.48 million, making September’s total slightly more than twice the preceding month’s figure.
Sky Reserves ended September at $85.08 million against a $150 million Solvency Reserve target, according to the update. Calculated from those figures, reserves stood at 56.7% of the target, leaving $64.92 million still to accumulate.
The Foundation’s August update placed reserves at $76.99 million. September’s closing balance was therefore $8.09 million higher, or approximately 10.5%. That balance change differs from the reported $7.15 million monthly remittance; the September text does not provide a reconciliation between the two measures.
Galaxy’s $100 million sUSDS position builds on an earlier agreement Galaxy’s treasury allocation was first announced on Sep. 23, before its inclusion in the monthly update. The agreement covered a $100 million sUSDS position, approval of the token as institutional loan collateral and a separate SKY purchase whose size was not disclosed.
As crypto.news previously reported, the sUSDS treasury allocation lets Galaxy clients pledge the savings token while continuing to accrue the Sky Savings Rate on their full collateral position for the loan’s duration.
The Foundation’s announcement identified Galaxy as a Nasdaq-listed company headquartered in New York. It described an institutional business serving more than 1,600 trading counterparties and carrying an average loan book of $1.4 billion.
Galaxy’s own website separately lists a $1.4 billion average loan book for the second quarter of 2026. Its current counterparty figure exceeds 1,700, although that figure comes from a different disclosure context than the September partnership announcement.
Sky’s savings token had already appeared in other distribution channels. Mantle’s August stablecoin vault launch offered exposure to sUSDS yield through a strategy built with CIAN, Grove and Fluxion. The underlying savings rate is set through governance and can change.
First SKY burn removes 2.86 million tokens The Foundation dated the first Stage 2 burn to Sep. 13, when 2.86 million SKY bought on the open market were permanently removed from circulation.
The purchases used the framework’s allocation of 5% of monthly Net Protocol Surplus. The September update did not disclose the dollar purchase cost or average execution price for the burned tokens.
The framework assigns another 22.5% of surplus to SKY purchases for staking rewards and 22.5% to USDS staking rewards. Up to 50% goes to the Surplus Buffer.
Only the dedicated 5% allocation funds permanent token removal. SKY acquired for staking rewards follows a separate distribution route, so the framework’s total buyback allocation should not be described as a burn allocation.
The Foundation’s preceding monthly report said governance ratified Stage 2 on Aug. 13. September’s burn followed that activation, while the latest financial results cover the framework’s first complete calendar month.
Grove facility finances $375 million in institutional loans Grove and Galaxy’s $500 million warehouse facility had financed $375 million in senior secured, overcollateralized institutional loans since its July 15 launch, according to the September update. The Foundation described the facility as 75% utilized and identified the latest loan of $71 million.
The accompanying case study explains that Grove commits USDS through a dedicated lending vehicle, while Galaxy underwrites, originates and services the loans. Borrowers provide Bitcoin or Ethereum collateral, with Anchorage Digital and BitGo supplying custody.
Elsewhere in the ecosystem, the Foundation reported that Spark’s Stablecoin FX Layer had processed more than $12 billion in cumulative volume since June 25. The system uses USDS as a common liquidity base connecting PYUSD, USDT, RLUSD and USDC.
Spark’s active loans reached $2.9 billion, representing approximately 190% growth over 180 days, the update said, citing Token Terminal. Separately, USDS borrowing on SparkLend passed $800 million after growing 64% over 30 days.
The Foundation said its third-quarter report and recorded insights call would follow later in October. Participants could submit questions ahead of the call, with submissions closing Oct. 28.
Not financial or tax advice. PANews content is strictly educational and informational and is not investment advice, financial advice, tax advice, legal advice, or a solicitation to buy or sell any digital asset, security, or financial product. Do your own research and consult qualified advisers.
Disclosure. PANews may publish sponsored content, partner content, advertisements, affiliate links, event promotions, and market commentary involving Web3 projects, service providers, or financial products. PANews personnel, contributors, or affiliates may hold digital assets or other interests related to covered topics. See our Terms of Service.
Andreessen Horowitz is rebranding its dedicated cryptocurrency investment practice as a16z Frontier, broadening its mandate beyond blockchain-focused startups to encompass a wider range of emerging technologies.
The change, announced on October 22, 2026, by managing partner Chris Dixon, frames the shift as an expansion rather than a departure.
The firm will continue investing in crypto and related ventures while advocating for sensible regulation in the space.
The new name reflects a focus on “frontier startups”—companies developing novel technologies and creating markets that may require years to mature. Dixon explained that crypto once existed as a relatively isolated domain.
As blockchain infrastructure has gained wider adoption, the distinctions have blurred.
Financial institutions and fintech firms now routinely launch products built on blockchains, making the “crypto company” label less useful. Companies are better defined by the problems they solve and the products they deliver than by the underlying tools they employ.
This approach aligns with a longstanding investment philosophy at the firm of supporting technologies that appear futuristic well before mainstream acceptance.
Dixon, who joined Andreessen Horowitz in 2013, previously emphasized long-horizon bets.
One earlier theme involved new computing devices enabled by cheaper cameras, sensors, and chips following the smartphone boom; that led to investments in areas such as virtual reality headsets and drones.
Crypto represented another major wave, building on social networks and open-source principles.
It facilitated community-driven adoption of networks like Bitcoin and Ethereum and extended open models to services and protocols.
That perspective guided early support for Coinbase and subsequent investments in projects including Solana and Uniswap.
The current expansion coincides with a major technology cycle centered on artificial intelligence.
While the buildout of models and infrastructure continues, the technology is already advanced enough to enable a new generation of products and services.
Dixon highlighted interest in native applications—entirely new activities that were not previously possible—rather than simply accelerating existing work such as coding or knowledge tasks.
Early experiments may initially resemble toys or hobbies, but some can scale if their improvement trajectories prove exponential.
Advances in AI are also expected to make software and hardware easier to create, fueling new devices.
These include autonomous machines capable of perceiving, reasoning, and acting in the physical world, as well as applications drawing on progress in biology and medicine.
Full-stack startups that integrate software, hardware, and services may become more common as founders seek novel forms of defensibility.
AI could further reshape company-building itself as agents gain greater autonomy.
New networks connecting people and intelligent agents—many beginning as individual tools before evolving into multi-user systems—represent another area of opportunity.
Such machine-oriented networks will differ significantly from those designed primarily for humans.
Blockchains retain a meaningful role in this landscape.
Crypto has established fast, low-cost, global, and programmable money rails. Stablecoins are becoming standard tools for fintechs and institutions, while programmable ledgers support both centralized and decentralized financial services.
These capabilities can equip new networks with native economic functions, facilitate machine-to-machine transactions, and provide fresh mechanisms for bootstrapping activity.
Dixon will lead a16z Frontier alongside firm founders Marc Andreessen and Ben Horowitz, together with general partners Eddy Lazzarin and Guy Wuollet.
The firm’s operating teams will continue assisting portfolio companies with regulatory matters, go-to-market strategy, talent, marketing, and technical research and development.
The announcement emphasizes that past technology waves rarely produced the precise outcomes predicted in advance, and that founders are expected to create unforeseen categories. Dixon noted that some of the most important technology developments remain ahead and invited founders working on what comes next to engage with the team.
The largest U.S. public pension fund has significantly reduced its holdings in the "Magnificent Seven" tech stocks, shifting to increase allocations to private equity.
According to a Financial Times report, CalPERS, the largest U.S. public pension fund (California Public Employees' Retirement System), is adjusting its asset allocation: cutting direct holdings of the "Magnificent Seven" tech giants while increasing exposure to private equity to reduce concentration risk in public equity investments. Calculations from regulatory filings show CalPERS will slash its direct holdings of stocks in Apple, Microsoft, Alphabet, Amazon, Nvidia, Meta, and Tesla by 26% in the first half of 2026. The fund is instead diversifying its portfolio across hundreds of companies, cutting concentrated bets on a small number of top firms. Anton Orlich, CalPERS' deputy chief investment officer, confirmed this allocation shift in an interview. He noted that public equity market valuations are already elevated, and concentration in a handful of leading companies is pressuring relative returns. In contrast, private companies offer more attractive pricing, helping CalPERS buffer against potential downturns in public markets. This rebalancing took place ahead of the recent tech stock sell-off. This week, multiple tech giants released earnings reports, stoking market concerns over whether AI spending can translate into tangible returns. Microsoft, Amazon, and Alphabet are set to report results next week, leaving the tech sector facing further tests. As of June 30, CalPERS' assets under management reached $637.1 billion. Data released by the fund in July showed its preliminary net investment return for the past 12 months was 14.8%, with both public and private equity portfolios performing strongly.
10 minutes ago
Hong Kong's Secretary for the Treasury: Hong Kong's tokenization initiative is advancing towards the implementation phase.
Secretary for Financial Services and the Treasury of the Hong Kong Special Administrative Region, Hui Ching Yu, stated that Hong Kong’s tokenization development is transitioning from the "experimental phase" to the "implementation phase". Currently, Hong Kong hosts over 1,400 fintech enterprises, including 8 virtual banks, 4 virtual insurance companies, and 12 licensed virtual asset trading platforms, which have achieved notable results in advancing tokenization. Hui added that the Hong Kong Exchanges and Clearing (HKEX) is committed to launching a tokenized warehouse receipt financing pilot program next year. The project will partner with designated banks, utilizing distributed ledger technology, to facilitate the use of commodity warehouse receipts as collateral. Furthermore, HKEX is also developing a multi-asset tokenization platform that will include commodity warehouse receipts from approved warehouses.
10 minutes ago
South Korea's KOSPI index closed 0.3% higher, with SK Hynix gaining 4.41%.
According to Bitget's market data, South Korea's KOSPI index closed up 16.53 points on Friday, October 23, with a 0.3% gain, ending at 5550.3 points. SK Hynix closed 4.41% higher, while Samsung Electronics rose 0.46%.
10 minutes ago
He Yi reposted Binance's Agent wallet risk alert, warning of transaction risks associated with the Agent developer mode.
Jackson.ll (@0xOar), developer of Binance Wallet’s web version, posted today, stating: “Agent ID is being used in various ways, but users should also carefully check risk warnings. Enabling developer mode for the Agent means you can sign unverified contract transactions... Potential risks need attention. You can close the mode immediately after minting, or wait for products from verified developers.” He Yi subsequently retweeted the post. Earlier reports indicated that multiple minting projects exclusive to Binance Agent Wallet have recently emerged in the market, with some requiring developer mode activation.
10 minutes ago
YuShu Technology, listed on China's A-share market, surges to its 20% daily limit, with its shares rising over 46% cumulatively this week.
ZhenFund has launched Ask AI, but it only comes with a single Markdown file.
Beating AI News Brief: ZhenFund has launched "Ask AI" on its official website, enabling entrepreneurs to directly inquire about the firms ZhenFund has invested in, its recent focus sectors, and relevant events tailored to them. The setup is straightforward: ZhenFund has compiled public information including its investment team, portfolio companies, focus areas, startup events, and contact details into a bilingual (Chinese-English) `zhenfund.md` file. Clicking any AI entry point redirects users to one of four platforms—Kimi, ChatGPT, Claude, or DeepSeek—with a pre-filled prompt that instructs the model to first read the `zhenfund.md` file before answering the entrepreneur’s questions.
Andreessen Horowitz’s crypto fund has a new name. On October 22, 2026, the firm unveiled a16z Frontier, the successor to a16z Crypto, along with a broader mandate to back what it calls “frontier startups.”
Crypto has not been left at the door. The fund says it will keep investing in blockchain projects and keep pushing on regulatory advocacy. It is simply adding more rooms to the house.
The timing comes with a thesis attached. Individuals are adopting AI faster than organizations are, and that gap is fueling a wave of new startups.
What changed, and what didn’t
The rebrand is being led by Chris Dixon, alongside Marc Andreessen, Ben Horowitz, Eddy Lazzarin and Guy Wuollet.
The new focus areas are wide. The fund lists AI, autonomous machines, full-stack companies that build both hardware and software, and new networks connecting humans and AI.
The money is substantial. A16z Frontier raised approximately $2.2 billion in its most recent vehicle. That brings the total to about $10 billion raised across five funds since the strategy began.
For context on the track record, the crypto fund’s past bets include Coinbase, Solana and Uniswap. Those names cover an exchange, a layer-1 blockchain and a decentralized trading protocol.
The AI thesis behind the rename
The core argument in the announcement is about speed. A16z pointed to a widening gap between AI-native startups and traditional incumbents, suggesting that AI could pull the development of frontier technologies forward by decades.
The crypto piece of the thesis fits into this picture rather than sitting beside it. The fund is keeping its commitment to blockchain infrastructure, including the use of stablecoins in communications between machines. That points toward a future of machine networks, where software agents and devices transact with each other directly.
Stablecoins, which are digital tokens pegged to a currency like the dollar, are one candidate for that payment rail. A16z is betting that crypto becomes the plumbing for this machine economy rather than a separate sector.
Why a crypto fund would drop “crypto” from its name
The Frontier label tells founders working in previously unaddressed domains that they are in scope, removing friction for founders building autonomous robots or full-stack hardware companies who might have assumed a16z Crypto was the wrong door.
It also reflects how blurry the line between crypto and conventional tech has become. Stablecoins are increasingly discussed as infrastructure rather than speculation. AI agents are being designed to act on their own.
What this means for founders, crypto and rival investors
For crypto founders, the near-term message is reassuring. The team, the regulatory advocacy and the investment commitment remain in place. A fund with roughly $2.2 billion in fresh capital is still a major source of funding for blockchain projects, especially ones that tie into AI or machine payments.
For the stablecoin sector, the endorsement of machine-to-machine payments as a core use case adds a large, well-known investor to the camp arguing that stablecoins have a role beyond trading and remittances.
Disclosure: This article was edited by John Chen. For more information on how we create and review content, see our Editorial Policy.
In brief Andreessen Horowitz is renaming a16z Crypto to a16z Frontier, widening the fund's scope to AI and other long-horizon technologies while keeping crypto investing and regulatory advocacy. Chris Dixon argues blockchains have receded into the background of products from Wall Street and fintech firms, so companies should be defined by what they do, not the technology they use. Dixon will lead the fund with Marc Andreessen, Ben Horowitz, Eddy Lazzarin and Guy Wuollet. Andreessen Horowitz, the venture capital firm better known as a16z, is renaming its crypto fund “a16z Frontier” and widening its mandate to AI and other emerging technologies, according to an email shared with its newsletter subscribers on Thursday.
a16z is among the biggest backers of the crypto industry, and when a firm that size drops “crypto” from its name, it shows where it may expect the next wave of cash to go. Chris Dixon, a general partner who runs the crypto team, says the firm’s bets include Coinbase, the blockchain network Solana, and Uniswap, a platform where people swap tokens without a middleman.
Myriad: How low will Tesla stock go? Click to make your prediction.a16z calls the move “an expansion” and says crypto stays: “we will continue to invest in crypto and related ventures and advocate for sensible crypto regulation,” the firm wrote.
The argument is that blockchains—shared digital ledgers that record who owns what without a bank in the middle—have faded into the background of products people already use.
“Wall Street and fintech companies now regularly launch products built on blockchains. Does that make them crypto companies? The label matters less now,” Dixon wrote, adding that it makes more sense to define companies “by what they do rather than by the technologies they use.”
In January, a16z said it had raised more than $15 billion across its funds, and co-founder Ben Horowitz wrote in a firm post that the mission “starts with winning the key architectures of the future—AI and crypto.”
Dixon expects more “native use cases,” which he defines as “brand-new activities you couldn’t do before,” since AI so far has mostly made existing work like coding “faster, better, and cheaper.” Early versions, he says, “will look strange and unserious, like toys and hobbies,” before some grow into mainstream products.
The new label covers startups “building new technologies and creating markets that may take years to develop,” a bet Dixon says goes back more than a decade.
“When I joined a16z in 2013, I made these kinds of long-horizon investments a focus,” Dixon wrote. “The growth of smartphones made cameras, sensors, and chips better and cheaper, enabling new devices like drones, AR/VR headsets, and wearables. That theme led to investments in Oculus and drone startups like Skydio and Zipline.”
The next wave, he says, includes “autonomous machines that can perceive, reason, and act in the physical world” as well as advances in biology and medicine.
He also envisions a post-AGI society referring to artificial general intelligence, a still-theoretical AI that can match or beat humans at nearly all thinking tasks.
Crypto stays in the picture because Dixon sees it giving AI agents, meaning programs that act on their own, a way to pay each other. “Crypto can give new networks native economic capabilities, enable machine-to-machine transactions, and create new ways to bootstrap them,” he wrote.
Dixon made a similar argument in 2022, when crypto’s total market value had fallen about two-thirds from its 2021 peak. “What I look at is not prices,” he said then, pointing to developer and entrepreneur activity as the core metric.
Dixon will lead the new fund alongside a16z founders Marc Andreessen and Ben Horowitz and general partners Eddy Lazzarin and Guy Wuollet. His post gives no size for the renamed fund, so the latest figure on record is the $2.2 billion announced in May.
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Image Credits:Darrell Etherington/TechCrunch In a sign that crypto and blockchain-focused investing has receded in importance, Andreessen Horowitz announced Thursday that it is renaming its digital asset unit from a16z Crypto to a16z Frontier.
The practice, helmed by Chris Dixon, has raised nearly $10 billion across five funds since launching in 2018, backing some of the sector’s biggest wins, including Coinbase. Yet for years, a16z and rival venture firms struggled to push crypto’s utility beyond financial rails, trading applications, and speculative assets.
Under the new name, the team is broadening its mandate to focus on emerging technologies, be it AI, robotics, or “new kinds of networks” connecting humans and machines. Yet, the group isn’t abandoning crypto. Dixon wrote in a blog post that blockchain technology could “give new networks native economic capabilities.”
Alongside Dixon, a16z Frontier’s general partners include Eddy Lazzarin and Guy Wuollet. Meanwhile, Ali Yahya, who joined the crypto strategy as its first investor in 2017, has left the firm, according to The Information.
Not financial or tax advice. PANews content is strictly educational and informational and is not investment advice, financial advice, tax advice, legal advice, or a solicitation to buy or sell any digital asset, security, or financial product. Do your own research and consult qualified advisers.
Disclosure. PANews may publish sponsored content, partner content, advertisements, affiliate links, event promotions, and market commentary involving Web3 projects, service providers, or financial products. PANews personnel, contributors, or affiliates may hold digital assets or other interests related to covered topics. See our Terms of Service.
Not financial or tax advice. PANews content is strictly educational and informational and is not investment advice, financial advice, tax advice, legal advice, or a solicitation to buy or sell any digital asset, security, or financial product. Do your own research and consult qualified advisers.
Disclosure. PANews may publish sponsored content, partner content, advertisements, affiliate links, event promotions, and market commentary involving Web3 projects, service providers, or financial products. PANews personnel, contributors, or affiliates may hold digital assets or other interests related to covered topics. See our Terms of Service.
Trade.xyz announced on social media that the pre-IPO perpetual contract (IPOP) market for JIO is now live. Each JIO unit corresponds to one common share of Jio Platforms Limited, quoted in US dollars. Currently, JIO operates as a pre-IPO market reflecting expected share prices, and is set to convert to a standard XYZ perpetual contract after Jio Platforms’ IPO. Post-IPO, oracles will convert the underlying stock’s rupee price to US dollars at the prevailing USD/Indian rupee exchange rate. Jio Platforms provides digital connectivity and services in India.
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Samsung’s Taylor 1 wafer fab has launched follow-up equipment investment, ramping up efforts to achieve 2-nanometer mass production.
According to a South Korean media report on October 23, Samsung Electronics has launched follow-up equipment investment at its No. 1 wafer fab in Taylor, Texas, completing the final pre-mass production phase of setup. This facility is Samsung’s first wafer foundry mass production line in the U.S., targeting 20,000 wafers per month of 2-nanometer capacity by the second half of next year. Samsung has recently ordered equipment, initially to meet a monthly capacity of around 6,000 wafers, with the equipment arriving gradually. The No. 1 fab broke ground in 2022, with Samsung’s total investment reaching approximately $37 billion. It is scheduled to begin operations by the end of 2026 and start mass production of EUV-based 2-nanometer chips from 2027. Samsung’s 2-nanometer yield has risen from around 60% earlier this year to roughly 80%, meeting mass production requirements. In terms of orders, the fab has secured full 2-nanometer orders before launch, with clients including Tesla’s AI5 and AI6 chips, Broadcom’s communication chips, and Arm’s smart device chips. Samsung and Tesla signed a $16.5 billion long-term supply contract in July 2025, valid through the end of 2033. Expansion plans do not stop here. Samsung plans to break ground on Taylor’s No. 2 fab in early November, which will be 1.5 times the size of the No. 1 facility, targeting mass production of 2-nanometer chips by 2030. Samsung’s total investment in central Texas exceeds $37 billion, and the U.S. CHIPS and Science Act has approved up to $4.745 billion in direct subsidies. The competitive landscape remains to be tested. TrendForce data shows TSMC held a 72.5% global wafer foundry revenue share in the second quarter of this year, while Samsung accounted for 5.9%. The Taylor fab’s capacity ramp and yield stability will determine whether Samsung can convert its order momentum into a market share recovery.
1 seconds ago
A SanDisk whale liquidated all positions and exited the market, incurring a $4.58 million loss on its SNDK long positions.
According to TradingBeats' monitoring, a large whale wallet starting with 0x469e liquidated its remaining 5,000 long positions in Sandbox (SNDK) early this morning, with a total closing transaction value of approximately $6.236 million. The final round of liquidation alone incurred a loss of around $2.836 million. The average entry price for this position stood at roughly $1,814.45, while the actual average closing price was about $1,247.20, a roughly 31.3% drop from the cost. Statistics indicate that the whale opened its SNDK long positions on September 23 and fully exited all holdings today, resulting in a total trading loss of approximately $4.583 million.
1 seconds ago
Arc Browser has announced its shutdown: Despite boasting millions of weekly active users, it failed to secure a future.
Beating AI Express News: The Arc browser is truly coming to an end. The Browser Company announced it will fully discontinue support for the macOS and Windows versions of Arc on December 22, 2026, and has already closed new user registrations. Starting November 23, the mobile version’s AI features, login functionality, and tab sync will be phased out gradually. The team will now focus entirely on its AI browser Dia. Arc launched in 2022, initially available exclusively to Mac users via invitation. It opened to all users in 2023, and expanded to Windows and mobile platforms in 2024. It reimagined the traditional browser with innovations including a vertical tab bar, dedicated workspaces, automatic tab organization, split-screen browsing, and even direct webpage customization. These designs made it a favorite among tech enthusiasts globally. China’s tech community once closely studied its design and development model, regarding it as a popular alternative to Chrome. The company previously revealed that Arc had over 1 million weekly active users, but its popularity did not translate into broad adoption. Founder Josh Miller acknowledged in 2025 that Arc was too complex for average users, with a steep learning curve, and only 5.52% of daily active users regularly used multiple workspaces. That same year, the team halted new feature development to pivot to Dia. In October 2025, its parent company was acquired by Atlassian for roughly $610 million. Now, the team has decided to end all maintenance for Arc, reasoning that browser security in the AI era requires ongoing investment, so engineering and security resources must be concentrated on Dia. Arc never became the next-generation Chrome, but it opened countless people’s eyes to what browser design could be. The creative concepts it introduced will live on in other browsers. Unfortunately, Arc itself will not get to see that future.
1 seconds ago
Vercel targets long-term API keys: labels them "insecure" by the end of the year, set to remove entirely next year.
Beating AI Express: Vercel announced it will phase out long-term static keys from its Marketplace. Starting November 30, third-party services that still rely on long-term keys and do not support Vercel OIDC authentication will be marked as "insecure". By January 2027, non-compliant providers will be delisted, with Vercel’s own APIs and native integrations required to follow the same standards. Long-term keys are non-expiring credentials, often stored in environment variables to enable apps or AI Agents to access services like databases. If leaked, attackers can exploit them indefinitely. Vercel’s OIDC, by contrast, allows programs to obtain short-lived credentials based on their own identity, with restricted access scopes and permissions. After credentials expire, the SDK automatically refreshes them, and caching reduces extra requests, eliminating the need for developers to manually rotate keys repeatedly. Vercel has faced such risks before: in April this year, third-party AI tool Context.ai was hacked, letting attackers breach Vercel’s internal systems and access some customers’ environment variables. The company only announced full remediation on October 16. Vercel also disclosed that past key rotation efforts consumed thousands of engineering hours. The company surveyed over 1,000 SaaS providers and found only 8.4% support the more secure authentication method. Long-term keys are widely used for their simplicity, while short-lived credentials are safer but more complex to configure and may increase network latency. Vercel is mitigating these costs via SDK and automatic caching, and using Marketplace listing eligibility to push providers to adopt more secure authentication practices.
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SpaceX is reportedly in talks to access at least 80,000 U.S. cell towers, advancing its bid to become the fourth national wireless carrier.
According to Reuters citing Bloomberg, SpaceX is in talks with U.S. cellular infrastructure companies to gain access to at least 80,000 cell tower sites nationwide. Insiders said the relevant deal could solidify its path to become the fourth national wireless carrier, challenging AT&T, Verizon, and T-Mobile. The report noted SpaceX is acquiring national low-frequency spectrum and has held negotiations with tower firms including Crown Castle. Data from the Wireless Infrastructure Association shows 80,000 sites are roughly half of the total dedicated cellular towers in the U.S. last year, which stood at around 158,500. Public records show Crown Castle operates about 40,000 towers in the U.S., American Tower has roughly 42,000 U.S. sites, and private firm Vertical Bridge owns around 18,000 towers. When asked at Wednesday’s earnings call whether it was in lease talks with satellite communications players like SpaceX and Amazon, Crown Castle CEO Christian Hillabrant said, "You can consider we are in discussions with all parties," but declined to name specific clients. TD Cowen estimates building a national terrestrial network could cost over $80 billion, requiring years of additional capital investment, with related lease transactions potentially running into billions of dollars. Crown Castle, American Tower, Vertical Bridge, and SpaceX did not immediately respond to Reuters’ request for comment. Separately, SpaceX recently reached an agreement to acquire a portfolio of approximately 800MHz low-frequency spectrum across the U.S. held by Grain Management, pending FCC approval. This week, the FCC also approved SpaceX’s plan to launch around 15,000 second-generation direct-to-phone satellites. CEO Elon Musk said at an earnings call that SpaceX will build a terrestrial network to achieve wide coverage in areas where SpaceX and Starlink are licensed to operate. Following the news, AT&T, Verizon, and T-Mobile saw post-market declines ranging from 4.2% to 5%.
Andreessen Horowitz is dropping "Crypto" from the name of its flagship blockchain fund, reportedly renaming it a16z Frontier as it widens its investment focus.
Andreessen Horowitz (a16z) is dropping the word "crypto" from the name of its flagship blockchain fund. The Information reported that the venture firm, which made one of the boldest bets on blockchain in the venture world, has informed some of its limited partners of the change.
The vehicle, known as a16z crypto, has raised nearly $10 billion across five funds, according to The Information. The firm is run by Marc Andreessen and Ben Horowitz, with Chris Dixon leading the crypto arm.
What is changing at a16z cryptoAccording to The Information, the fund will shift its focus to other investment areas, and its first founding member is leaving. Bloomingbit, citing the same report, said the fund will be renamed a16z Frontier and that general partner Ali Yahya is departing to start his own company. Techmeme's summary of the report also points to the a16z Frontier name and a broader strategy beyond crypto.
The reported new areas include enterprise computing, physical-world asset distribution and financial infrastructure for machines. It is not yet clear how the change will affect the firm's existing crypto investment business, according to a Chinese-language summary of the report from Wublock123.
Not everyone reads the move as an exit. ChainCatcher's analysis said the change signals a broader mandate rather than a withdrawal from the sector. It noted that Chris Dixon remains in his role and that crypto assets and blockchain remain a core focus under the wider label.
Context: a smaller fund and a wider mandateThe renaming follows a fifth crypto fund that was smaller than its predecessor. a16z crypto said it raised $2.2 billion for Crypto Fund 5, aimed at turning new infrastructure into products people use every day, including payments and financial services. Wublock123 reported that this was roughly half the $4.5 billion raised for the fourth fund in 2022.
The firm has also been spreading capital into other areas. In August, a16z closed a $1.1 billion Machine Age Fund targeting AI hardware, including chips, networking, data centers and robotics, according to Crypto Briefing.
For the crypto industry, the rebrand is a signal on how one of its largest venture backers is positioning itself. Whether it marks a retreat or a widening of scope will depend on where the firm deploys capital from the renamed fund.
SourcesThe Information: Andreessen Horowitz to Drop 'Crypto' From Name of Flagship Blockchain Fund
ChainCatcher: a16z fund removing the Crypto name analysis
If Bitcoin drops below $80,000, total long position liquidations on major centralized exchanges (CEXs) will hit $692 million.
According to Coinglass data, if Bitcoin falls below $80,000, the total long liquidation intensity on major centralized exchanges (CEXs) will reach $692 million. Conversely, if Bitcoin breaks through $83,000, the total short liquidation intensity on major CEXs will hit $1.025 billion. BlockBeats Note: Liquidation charts do not display the exact number of pending liquidations or the exact value of liquidated contracts. The bars on these charts actually represent the relative importance (intensity) of each liquidation cluster compared to adjacent clusters. Therefore, the liquidation chart shows the degree of impact when the underlying asset’s price reaches a specific level. A higher "liquidation bar" indicates that once the price hits that level, it will trigger a stronger reaction due to liquidity waves.
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Bitcoin falls below $81,000, with a 4.3% drop in the past 24 hours.
According to HTX market data, Bitcoin fell below $81,000, with a 4.3% decline in the past 24 hours.
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Pump.fun launches EVM limit orders, supporting take-profit and stop-loss functions.
Meme coin launch platform Pump.fun announced the launch of its EVM limit order functionality, claiming it is the first social trading application to offer take-profit and stop-loss features. The feature currently covers Robinhood, BNB Chain, Base, HyperEVM, Arc, and Ink, with more chains set to be integrated gradually.
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a16z Frontier has officially confirmed its continued focus on the crypto space, expanding its investment scope to include frontier technology startups.
a16z General Partner Chris Dixon has officially published an announcement renaming a16z crypto to a16z Frontier, expanding its investment scope from crypto startups to a broader set of frontier technology startups—those building new technologies, opening up new markets, and taking years to mature. Dixon emphasized this is a scope expansion, not a pivot; the team will continue investing in crypto and related businesses while advocating for reasonable crypto regulation. Dixon noted that as blockchain gains wider adoption, Wall Street and fintech firms have regularly launched on-chain products, making the "crypto company" label less significant. Companies should be defined by their core business activities, not the technology they employ. His remarks also touch on the ongoing AI wave: beyond using AI to speed up and enhance existing work, focus is on native new use cases emerging from AI, full-stack startups integrating hardware, software and services, and new networks connecting humans and intelligent agents. Dixon believes blockchain will still play a critical role in this space, serving as a fast, low-cost, global, programmable financial infrastructure for the internet. Stablecoins are becoming a standard tool for fintech firms and institutions, and can also support machine-to-machine transactions and the cold start of new networks. He will lead the fund alongside firm founders Marc Andreessen and Ben Horowitz, as well as general partners Eddy Lazzarin and Guy Wuollet. The operating team will continue supporting current and future portfolio companies in areas including regulation, market entry, talent, marketing and technology R&D.
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New York State Department of Financial Services issues alert over PHP vulnerability.
New York State Department of Financial Services (NYDFS) has issued alerts regarding two critical PHP vulnerabilities, urging regulated entities to promptly identify and remediate the vulnerabilities that are already being exploited.
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GMGN Co-founder: The self-developed cross-chain bridge is undergoing a small-scale volume test, and the APP will soon support buying multi-chain tokens with USDC.
GMGN co-founder Haze announced in a post that the project’s self-developed cross-chain bridge is currently undergoing small-scale volume testing, and will uphold its long-standing reputation for fast, secure, and stable transactions. Haze added that users will soon be able to buy any token across multiple blockchains using USDC through the GMGN app.
The Upshift-built vault earns Frontier Points for future registration priority, with Hyperion DeFi as launch partner. Domain purchases require separate funds.
The Upshift-built vault earns Frontier Points for future registration priority, with Hyperion DeFi as launch partner. Domain purchases require separate funds.
GPT-6 Astra, Sol, and Luna arrive in Google Cloud's Model Garden as the third hyperscaler to sell OpenAI's frontier since its exclusive Azure distribution ended. The distribution widened. The compute underneath did not.
Lena ParkForkast mind
OpenAI’s frontier models are coming to Google Cloud. Announced October 21, the deal puts GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna into Google Cloud’s Model Garden, with Codex agentic workflows connecting to Google’s Gemini platform for inference. Enterprises transact through Google Cloud Marketplace: one invoice, existing spend commitments drawn down, usage counting toward Flexible Savings Plans across model providers. In the joint announcement, Greg Brockman, President and co-founder, OpenAI, stated: “This partnership is an important step in making our most capable models and Codex available where customers are already building, giving them even more choice in how they use frontier AI as we grow the agentic ecosystem together.” Google Cloud CEO Thomas Kurian added in SiliconANGLE’s same-day report: “We are focused on giving customers a broad selection of models, including those from OpenAI, so they can choose the right model for any given job, helping to deliver optimal quality and lower costs.” Google Cloud becomes the third hyperscaler to sell OpenAI’s models since its exclusive Azure distribution ended in April, after Amazon Bedrock (April 28) and Oracle Cloud (June 10). The distribution went multi-cloud. The watts underneath it did not.
The commercial terms are the first thing to read carefully, because they are mostly absent. Neither Google Cloud nor OpenAI published per-token pricing for any of the three models as sold through Model Garden as of the announcement date. Access is a private preview for select enterprise customers, with general availability reported as coming in the weeks ahead and no firm date. Public Model Garden documentation did not list any OpenAI model; model IDs, supported regions, quotas, and rate cards required a signed-in console. This is not an open marketplace listing. It is a negotiated enterprise channel whose terms are not public until you are in the room — the same architecture as the $20 million license gates this beat tracks, applied to distribution instead of licensing.
The billing mechanics deserve one precise note. Google’s Flexible Savings Plans allow drawdown across model providers, but Google’s own FSP documentation states: “Third-party products don’t get any discounts from the FSP.” Spend on third-party models under an FSP draws down against your organization’s enterprise commitment, subject to the standard Cloud Marketplace drawdown rules and contract caps defined in the enterprise agreement. A CIO counting on FSP economics for GPT-6 Astra usage is counting on terms that Google has not published.
The competitive frame is the one Model Moats mapped: value is draining out of the model layer and accumulating in infrastructure. When the engine is free and the serving stack is standardized, the highest-margin part of the stack is no longer the software. OpenAI’s exclusive Microsoft Azure distribution ended in April 2026. In six months the company spread to Bedrock, Oracle Cloud, and now Google Cloud. Each hyperscaler sells the same tokens through its own invoice, its own commitment structure, its own compliance wrapper. The model is the product on every shelf. The shelf is the moat.
What actually stays exclusive is specific and measurable. The weights remain closed — GPT-6 Astra, Sol, and Luna are served through APIs, never downloaded. The compute that serves them sits inside a small set of hyperscaler data centers plus OpenAI’s own build-out. The pricing is unpublished. The availability is gated behind a preview request form. Google Cloud’s claim to be “the only hyperscale cloud provider offering access to all three leading closed source LLMs” is a distribution claim, not a capacity claim — the watts are still rationed by the same companies that were rationing them last week.
One open-weights footnote belongs on the face. OpenAI’s gpt-oss 120B and gpt-oss 20B were already available on Google’s platform before this announcement. Those are the unrestricted tier. The GPT-6 family arriving now is the closed tier. Google’s shelf now carries both classes side by side, and the buyer’s choice between them is a choice between a model you can run anywhere and a model you can only rent from three companies.
For builders and deployers, the practical change is real but narrow. An enterprise already committed to Google Cloud can now evaluate OpenAI’s frontier without a separate vendor contract, and the usage appears on the same invoice as its Gemini spend. That is procurement convenience, not market structure. The market structure is this: four hyperscalers now sell roughly the same frontier models, none of them compete on compute price in public, and the model weights themselves are the one layer nobody ships. Distribution widened this week. The scarcity moved down, where it always goes.
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Today we’re announcing that we’re expanding the scope of our new fund beyond crypto startups to the broader category of frontier startups: companies building new technologies and creating markets that may take years to develop. To reflect this, we’re renaming a16z crypto to a16z Frontier. This is an expansion: we will continue to invest in crypto and related ventures and advocate for sensible crypto regulation.
When we started investing in crypto, it was a world of its own. But as blockchains have become more widely used, the lines have blurred and the infrastructure has gradually receded into the background. Wall Street and fintech companies now regularly launch products built on blockchains. Does that make them crypto companies? The label matters less now. It makes more sense to define companies by what they do rather than by the technologies they use.
Our expansion also reflects an approach that has guided many of our investments for years: backing technologies that look futuristic, well before they reach the mainstream. When I joined a16z in 2013, I made these kinds of long-horizon investments a focus. One theme was new computing devices. The growth of smartphones made cameras, sensors, and chips better and cheaper, enabling new devices like drones, AR/VR headsets, and wearables. That theme led to investments in Oculus and drone startups like Skydio and Zipline.
The other was crypto, which I saw as a new wave built on social media and the open source movement. Social media allowed networks like Bitcoin and Ethereum to gain traction from the outside in, as people formed communities without first needing mainstream acceptance. Open source provided the model for software that anyone could inspect, modify, and build on. Blockchains extended that model from software to services and networks. This theme guided our investment in Coinbase and the creation of our crypto funds, as well as later investments in projects like Solana and Uniswap.
Now we are in the middle of another major tech wave centered on AI. The buildout of AI models and infrastructure will continue, but the tech is already sufficiently advanced to spawn a new generation of products and services. No one knows exactly what that generation will look like, but we’re beginning to catch glimpses. We’re especially interested in the new products and markets these advances will enable, including ones that don’t fit into existing categories.
Foremost is the emergence of native use cases: brand-new activities you couldn’t do before. Early applications of new technologies tend to focus on doing old things better. To date, AI has mostly been used to do existing activities — like coding and other knowledge work — faster, better, and cheaper. But soon native uses will open up entirely new, unexpected experiences. At first, many of these experiments will look strange and unserious, like toys and hobbies, but over time some will grow into mainstream products. The key to telling the difference is to understand their potential rates of improvement, the factors that can bend deceptively marginal growth into an exponential curve.
We’re lucky enough to be living through one of the most consequential curves in human history today. Technological progress is accelerating rapidly, and we’re already starting to see early signals about what a post-AGI world might look like. For one thing, software and increasingly hardware are becoming easier to create. Just as the growth of smartphones fueled an earlier computing cycle, we expect a proliferation of new devices to underpin this one. Some of these will be autonomous machines that can perceive, reason, and act in the physical world. Others will draw on advances in biology and medicine. Still others will fall somewhere, cybernetically, in between.
All these advances will present new ways of building companies. We’ll see more full-stack startups that combine software with hardware and services, as founders take advantage of new capabilities and seek new forms of defensibility. Even the idea of what it means to be a founder may change as we gain more superpowers and as AI agents become increasingly autonomous, able to act on their own. As these capabilities spread, they could change how industries are organized and even give rise to new ones.
AI will also enable entirely new kinds of networks connecting people and intelligent agents that learn, coordinate, produce, and transact. The large-scale networks we use every day were made for humans. Networks built for machines will look very different. Many will start as single-player tools and evolve into multiplayer networks. The potential here — for machine-age networks — is enormous, and builders have barely begun to scratch the surface.
Blockchains will play a significant role in this transformation. Crypto has given the internet money rails that are fast, cheap, global, and programmable. Stablecoins are quickly becoming a standard tool for fintechs, established institutions, and others. And, because blockchains are programmable, both centralized and decentralized financial services can be built on top. Crypto can give new networks native economic capabilities, enable machine-to-machine transactions, and create new ways to bootstrap them.
These are examples, not boundaries. The defining companies of past waves were rarely the ones anyone predicted. As always, we expect founders to surprise us and create categories we haven’t imagined yet.
I’ll be leading the fund along with the firm’s founders Marc and Ben, and GPs Eddy Lazzarin and Guy Wuollet. Our operating teams will continue to work with our existing and future portfolio companies on regulatory, go-to-market, talent, marketing, and technical R&D.
We believe some of the most important technology waves are still ahead. Ideas that seem weird or far-fetched today will become indispensable, era-defining products of the future. If you are a founder building what comes next, please reach out.
Not an offer or solicitation. None of the information herein should be taken as investment advice; Some of the companies mentioned are portfolio companies of a16z. Please see a16z.com/disclosures for more information. A list of investments made by a16z is available at a16z.com/portfolio.
a16z General Partner Chris Dixon has officially published an announcement renaming a16z crypto to a16z Frontier, expanding its investment scope from crypto startups to a broader set of frontier technology startups—those building new technologies, opening up new markets, and taking years to mature. Dixon emphasized this is a scope expansion, not a pivot; the team will continue investing in crypto and related businesses while advocating for reasonable crypto regulation. Dixon noted that as blockchain gains wider adoption, Wall Street and fintech firms have regularly launched on-chain products, making the "crypto company" label less significant. Companies should be defined by their core business activities, not the technology they employ. His remarks also touch on the ongoing AI wave: beyond using AI to speed up and enhance existing work, focus is on native new use cases emerging from AI, full-stack startups integrating hardware, software and services, and new networks connecting humans and intelligent agents. Dixon believes blockchain will still play a critical role in this space, serving as a fast, low-cost, global, programmable financial infrastructure for the internet. Stablecoins are becoming a standard tool for fintech firms and institutions, and can also support machine-to-machine transactions and the cold start of new networks. He will lead the fund alongside firm founders Marc Andreessen and Ben Horowitz, as well as general partners Eddy Lazzarin and Guy Wuollet. The operating team will continue supporting current and future portfolio companies in areas including regulation, market entry, talent, marketing and technology R&D.
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One of crypto’s most recognizable venture backers just got a new name. a16z Crypto, the digital-asset arm of Andreessen Horowitz, is rebranding as a16z Frontier.
What changed, and what didn’t
The rebrand was announced on October 22, 2026, by managing partner Chris Dixon. He framed the move as an expanded mandate rather than a retreat from the asset class.
Under the new banner, the firm plans to back what it calls “frontier startups.” Those are companies building long-horizon technologies and chasing new market opportunities.
Dixon confirmed the widened scope includes AI-native applications and autonomous technologies. Those sit alongside the firm’s existing crypto portfolio, not in place of it.
The firm also said it will keep investing in crypto and related fields. It plans to continue pushing for sensible regulatory frameworks, a cause the team has championed for years.
The numbers behind the name change
The rebrand lands alongside some telling fundraising figures. The team’s most recent fund raised $2.2 billion.
That is well below the $4.5 billion it raised in 2022. The 2022 vehicle was closed near the height of the last crypto venture cycle, and the follow-up came in at less than half that size.
Across five funds since inception, the team has raised approximately $10 billion in total.
There is also a personnel shift. Ali Yahya, a founding general partner of the crypto team, is leaving to start his own venture.
How a16z got here
a16z has been among the most prominent investors in crypto since launching its first dedicated fund in 2018. Its portfolio has spanned DeFi, core infrastructure, and consumer applications.
The rebrand also reflects a trend the firm itself highlighted: blockchain components are increasingly showing up inside companies that would not call themselves crypto startups. Stablecoin rails, onchain identity, and tokenized ownership can sit quietly under products marketed as something else entirely.
What this means for crypto founders and investors
For crypto founders, the immediate question is whether a broader mandate means a thinner slice of attention. A fund that once had one lane now has several, and partner bandwidth is finite.
The firm’s public stance points the other way. By explicitly committing to keep funding crypto, a16z is signaling that the asset class stays in the portfolio, just alongside AI-native and autonomous tech rather than alone.
The fundraising data tells a more sobering story about the venture market. A drop from $4.5 billion to $2.2 billion between funds suggests that limited partners were less eager to write enormous crypto-only checks than they were in 2022.
Policy is another thread. a16z has been one of the louder industry voices calling for workable crypto rules in the US, and the firm says that advocacy continues under the Frontier name.
The key signals going forward are concrete ones: the mix of deals the rebranded fund announces, the size of its next raise, and whether crypto still claims a meaningful share of new checks.
Disclosure: This article was edited by John Chen. For more information on how we create and review content, see our Editorial Policy.
In 2018, Andreessen Horowitz made a splash in the venture capital world by launching a spin-off dedicated to digital assets called a16z Crypto. Eight years later—perhaps recognizing that the term “crypto” has fallen out of favor—the VC giant announced Thursday that it was rebranding to a16z Frontier, and expanding its scope to back startups developing artificial intelligence, robotics, and other emerging technologies.
Managing partner Chris Dixon will lead the fund alongside Andreessen, Horowitz, and general partners Eddy Lazzarin and Guy Wuollet. The shift expands the scope of its $2.2 billion fund announced in May, though the firm will continue backing crypto startups and advocating for crypto regulation.
As more businesses use blockchain technology behind the scenes, the distinction between crypto companies and other businesses is becoming less clear, Dixon wrote in an X article.
“Does that make them crypto companies? The label matters less now,” he said.
a16z crypto general partner Ali Yahya has told some investors he plans to depart to launch a startup, according to The Information. His tenure dates to 2017, when he became the first person working full time on the firm’s crypto team.
The firm had begun investing beyond crypto before Thursday’s announcement. In June, a16z crypto led a $33 million seed round for Ornn, a company developing financial products for the AI computing market. In October 2025, Andreessen Horowitz co-led a funding round for prediction market Kalshi.
The move follows similar expansions by other prominent crypto investors. When Paradigm announced its $1.2 billion fund in July, it said its investment approach had started in crypto but would now extend to artificial intelligence, robotics, and other emerging technologies. In May, Haun Ventures founder Katie Haun announced $1 billion in new funds. In her written announcement, Haun said that building financial services from the ground up “includes crypto, but is bigger than that toolset alone.” The firm instead increased its focus on other sectors, like emerging payments models and the agentic economy.
When Andreessen Horowitz first debuted a16z crypto, it raised a $350 million investment fund with an original mission to acquire cryptoassets and back projects built on blockchain technology.
The firm went on to raise increasingly large crypto funds, including a $4.5 billion vehicle in 2022. Its latest $2.2 billion fund brought the total raised across five funds to $9.8 billion. Some of the firm’s most successful investments included decentralized exchange Uniswap and crypto custodian Anchorage Digital.
Thursday’s news marked a reversal from a statement an a16z crypto spokesperson gave Fortune in May, saying its fifth fund was “100% dedicated to investing in crypto entrepreneurs,” even as rival firms had already begun expanding into artificial intelligence and other sectors.
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Two critical remote code execution flaws in the PHP language runtime, found by frontier AI models after a decade of manual audits failed to catch them, put 70% of the web on notice.
Frontier AI models have identified two critical remote code execution (RCE) vulnerabilities in the PHP language runtime that remained undetected through a decade of manual security audits.
The vulnerabilities, tracked as CVE-2026-109618 and CVE-2026-109619, allow unauthenticated attackers to execute arbitrary code on servers running affected versions of PHP. AI-assisted analysis identified these memory-corruption flaws, which had remained hidden in the PHP codebase for more than a decade.
The Mechanism of PHP2Shell Wiz Research, which combined these vulnerabilities into an exploit script dubbed “php2shell,” identified the flaws as memory-safety issues stemming from how PHP handles fatal errors during request processing. CVE-2026-109618 involves out-of-memory (OOM) corruption, where PHP interrupts a request while internal data is only partially initialized. During the subsequent cleanup process, the runtime incorrectly treats this invalid data as valid. CVE-2026-109619 involves stale global state, where request-owned internal state persists after its backing memory has been freed, allowing a subsequent request handled by the same worker to utilize the stale data before it is reset.
Both vulnerabilities carry a CVSS v4.0 score of 9.2, marking them as critical. The flaws exploit the runtime’s trust-through-defaults pattern: the engine assumes its internal state is consistent even after an interrupted request. This pattern of implicit trust in memory management is a recurring theme in recent infrastructure vulnerabilities, similar to issues previously tracked in BeyondTrust, nine-layer, and ConnectWise. Unlike the identity-layer and supply-chain trust gaps analyzed in our prior coverage, including the synthesis in the nine-layer report, PHP2Shell represents a distinct class of failure: it sits below the application layer entirely, where the language runtime blindly trusts its own internal memory state.
AI-Assisted Discovery Wiz Research identified these vulnerabilities using Wiz Atlas, Gemini 4 Argon, and GPT-5.6 Sol. According to the firm, a single researcher completed in a week what would previously have taken a world-class team months of work. Writing in the Google Cloud post she co-authored with CISO Chris Betz, Raluca Ada Popa, Head of Gemini Security at Google DeepMind, said Gemini 4 Argon made “an invaluable contribution to finding the vulnerability, exploit development, attack detection, and validation of the patch.”
Independently, researcher Ryan Austin of Calif surfaced the same bug class while auditing PHP under OpenAI’s “Patch the Planet” initiative. Calif’s write-up of the disclosure dates the first confirmed out-of-memory fatal to August 1, days into the audit, with the first bug reported to PHP on August 11 and a working exploit confirmed by the project on August 15.
Wiz Research writes that the findings “rank among the most severe vulnerabilities discovered in PHP, and arguably in software history,” and that demonstrating exploitability required “an exceptionally complex chain of steps, at the edge of what human researchers could practically achieve” before frontier AI models lowered that barrier.
Scope and Impact According to Wiz Research, PHP powers 70% of all websites globally, meaning the vulnerabilities affect a significant portion of the internet. The flaws impact all currently supported PHP branches, including versions 5.4 through 8.5.11, as well as older end-of-life branches. Apache mod_php represents the highest risk surface, as the exploit can succeed before any application code executes. Other environments, including PHP-FPM, php-cgi, FrankenPHP, and LiteSpeed, are also at risk.
Wiz demonstrated unauthenticated RCE against the latest container images for WordPress, Drupal, and Joomla. While Google Cloud is not itself vulnerable, the company confirmed that users running PHP on its infrastructure may be exposed.
Remediation and Patching The PHP security team released patches on October 21, 2026, in versions 8.5.12, 8.4.27, 8.3.36, and 8.2.35. Because PHP 8.1 and older versions are end-of-life, the project provided only minimal source-backports for versions 7.4, 8.0, and 8.1. Administrators are advised to update immediately.
For systems where immediate patching is not possible, the PHP project recommends specific mitigations: setting memory_limit to -1 to address CVE-2026-109618, and setting session.upload_progress.enabled to 0 and fatal_error_backtraces to 0 to mitigate CVE-2026-109619. While eSentire’s advisory reports unverified claims of exploit code circulating in the wild, those reports remain unconfirmed. Rapid7’s emergency threat response covers the same pair; that page returned a 403 bot wall at fetch, so it is named here rather than quoted.
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At 1,068 tokens per second on NVIDIA GPUs, Inception Labs' Mercury 3 establishes a new performance baseline that renders the fast-cheap tier of frontier models obsolete.
Lena ParkForkast mind
At 1,068 tokens per second on NVIDIA GPUs, Inception Labs’ Mercury 3, released October 19, 2026, establishes a new performance baseline that renders the existing fast-cheap tier of frontier models obsolete. By utilizing a diffusion-based architecture, the model generates tokens in parallel through a denoising process rather than the sequential autoregressive methods used by incumbents. This architectural shift allows Inception Labs to report speeds 4-8x faster than comparable frontier models, though these performance metrics and benchmark results – including claims that it outperforms GPT-6 Luna and Claude Haiku 5.5 – remain vendor-reported.
The pricing structure for Mercury 3 is equally aggressive. At a standard rate of $0.20 per million input tokens and $0.70 per million output tokens, with launch pricing currently at $0.10 and $0.35 respectively, the model forces a re-evaluation of the inference pricing floor. When compared to the landscape mapped in our previous analysis of per-call pricing dynamics, where models like GPT-5.6 Sol command $5/$30 per million tokens and Sonnet 5.5 sits at $2/$10, the cost compression introduced by Mercury 3 is stark. The model also offers a 90% discount on cached tokens, further incentivizing high-volume, repetitive agentic workflows.
The fast-cheap tier, previously occupied by models like GPT-6 Luna and Haiku 5.5, was built on the assumption that speed and cost were trade-offs for lower parameter counts or reduced reasoning capabilities. Mercury 3 disrupts this by offering a 40x increase in total parameters compared to its predecessor, Mercury 1, while simultaneously undercutting the incumbents on price and speed. This creates a structural problem for providers who have positioned their smaller models as the default for high-throughput agent infrastructure.
The market reality is that builders and operators no longer need to choose between intelligence and latency. The practical utility of this shift is already being tested in production environments. In vendor-reported browser use tests, Mercury 3 completed 50% of 50 live Mind2Web navigation tasks, a performance level Inception Labs reports as significantly higher than GPT-6.1-Sol. With a context window of 1 million tokens and availability across major platforms including the Inception API, OpenRouter, Baseten, and Vercel, the barrier to entry for deploying these agentic capabilities has dropped significantly.
The inference pricing floor is collapsing as diffusion architecture makes the fast-cheap tier obsolete. The cost of intelligence is decoupling from the cost of compute. As diffusion models maintain this trajectory, the market is shifting away from paying a premium for speed-optimized autoregressive models. The industry is now forced to operate in a landscape where the floor has not just been lowered – it has been fundamentally redesigned.
Verification note: All benchmark claims and performance metrics cited in this article are vendor-reported by Inception Labs. Pricing figures verified against the Inception blog post and OpenRouter listing.
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DeepSeek's $0.75 per 1,000 Search & Fetch calls is 6 to 9 times cheaper than every established retrieval provider — and it introduces a billing model that no frontier lab has adopted for inference.
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A production agent running 10,000 search-and-fetch cycles per day would spend $7.50 on DeepSeek’s new APIs. On any established search provider, that same workload costs $50 to $120. The gap is not marginal — it is a different billing model entirely.
DeepSeek’s Search and Fetch APIs, launched October 17 alongside DeepSeek-V4.1-Flash-1017, charge $0.75 per 1,000 successful requests per endpoint. Billing begins at 00:00 Beijing time on November 1 (16:00 UTC on October 31). Until then, calls through DeepSeek Harness, Claude Code, and Codex are free. Each endpoint is capped at 5 requests per second per account, and failed requests, empty results, and timeouts are not billed.
The pricing is per-call, not per-token. That distinction matters because it is the first time any company that ships a frontier model has offered agent tooling at a flat rate per request rather than metering by the volume of text that flows through the system. Every frontier lab — OpenAI, Anthropic, Google — still prices model inference by the token. OpenAI’s GPT-5.6 Sol runs $5.00 per million input tokens and $30.00 per million output. Anthropic’s Sonnet 5.5 is $2.00 and $10.00. Google’s Gemini 2.5 Pro is $1.25 and $10.00. The cost of a single agent step depends on how much text the model consumes and produces, which makes budgeting for high-frequency agentic loops inherently volatile.
Against established retrieval providers, the gap is even wider. Brave Search API charges $5 per 1,000 requests. Exa charges $7 for standard search and $12 for deep search. Tavily ranges from $8 to $16 depending on depth. Perplexity Sonar starts at $5 per 1,000 requests and adds token costs on top. DeepSeek’s $0.75 is 6.7 times cheaper than Brave and 9.3 times cheaper than Exa’s standard tier. This is the same price architecture our prior coverage identified in DeepSeek’s retrieval monetization move — the per-call model is the mechanism that makes the price floor sustainable.
Agents use models differently than humans do. A human chatting with a language model generates a long, variable sequence of tokens per exchange. An agent performing retrieval makes a structured call, receives a bounded result, and moves to the next step. The value of that step is binary: the agent got the information or it did not. Per-call pricing maps to that binary outcome. Per-token pricing does not — it forces the builder to pay for output length even when the retrieval result is a short, fixed-format object. The agent cost stack has been restructuring around exactly this divergence: Google now meters compute directly, factoring prompt complexity and effort, while Orb’s 2026 pricing study of 80 AI agent companies finds 95 percent on hybrid pricing models, with effort, compute, and discrete steps climbing as the primary billing units. Pure outcome pricing remains rare at 3.8 percent and falling.
DeepSeek’s move isolates the retrieval layer as the first component to transition from per-token to per-call. The sandbox and infrastructure layers are already commoditizing — what remains contested is the orchestration and retrieval interface above them. By pricing retrieval at a flat rate per call, DeepSeek is attempting to capture that interface before established providers can respond with their own per-call models.
Whether this pricing model propagates to core inference is the question frontier labs are now watching. The per-token model captures value across the entire lifecycle of a prompt — every input token, every output token, every reasoning step. A flat per-call rate for inference would require labs to estimate the average workload per call and price accordingly, which introduces margin risk on complex reasoning tasks. The structural incentive for OpenAI, Anthropic, and Google is to keep inference per-token while watching whether DeepSeek’s retrieval pricing forces their own search and tooling layers to compress.
For builders, the practical shift is in cost modeling. Per-call pricing makes the retrieval layer predictable: 10,000 calls at $0.75 per 1,000 is $7.50, regardless of how much text each call returns. That predictability does not exist in per-token inference, where a single complex reasoning chain can consume thousands of output tokens at variable cost. The ability to mix per-call retrieval with per-token reasoning — using DeepSeek’s tooling alongside a frontier model for the cognitive layer — gives builders a new axis of cost control. The catch is the 5-requests-per-second cap per endpoint, which limits throughput for high-concurrency agents. Whether DeepSeek raises that ceiling will determine whether the per-call model scales to production workloads or stays confined to prototyping.
Verification Note: All pricing figures cited in this article are from vendor-published documentation (DeepSeek API docs, Brave, Exa, Tavily, Perplexity, OpenAI, Anthropic, Google). OpenAI and Anthropic pricing sourced from third-party aggregators due to access restrictions on official pricing pages.
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Agentic commerce has moved beyond phone screens into smart TVs, lock screens, and streaming devices. Merchants who thought this was a web problem are now exposed on surfaces they never planned for.
The Ambient Checkout Frontier The transition of agentic commerce from the controlled environment of a smartphone screen to the ambient surfaces of the home and pocket is now underway. On October 15, 2026, PayPal and Glance announced an integration that embeds native checkout directly into the Glance ecosystem. Commerce is now a background process triggered by AI agents on smart TVs, lock screens, and connected TV (CTV) interfaces, rather than a destination a user visits.
Scale and Surface Area Glance, owned by InMobi, reports its software is embedded across more than 60 million mobile and CTV devices. This vendor-reported footprint includes Samsung Galaxy devices via the Galaxy Store, Motorola lock screens, DirecTV Gemini, and various Android TV platforms. By integrating PayPal as the exclusive native checkout partner, the companies aim to capture consumer attention at the moment of inspiration, before a search query is even initiated. For Samsung users, this reach expanded significantly in June 2026, when the partnership brought agentic commerce to all 2020 and newer smart TVs in the United States.
Infrastructure for AI Transactions To manage this distribution, PayPal utilizes paypal.ai as the primary merchant-side infrastructure. The platform offers a single integration point designed to connect merchants to multiple AI shopping surfaces, providing real-time product data and facilitating in-flow transactions. Glance complements this with AI-powered features such as virtual try-on and product discovery. However, the velocity of this deployment-reaching 60 million devices-appears to be outpacing the development of the underlying trust infrastructure required to secure these transactions.
The Liability Wall Expands Previous coverage has highlighted a growing liability wall, and the expansion into ambient surfaces complicates this dynamic. Merchants are now facing potential exposure on device surfaces they never explicitly planned for or vetted. Data from PYMNTS and Visa indicates that 93% of merchants believe the AI provider should bear the financial loss for incorrect purchases. Despite this, only 28% of merchants are currently willing to expose their full inventory to agents, and only 11% of SMBs are considered agent-ready.
Trust and Insurance Layers The industry is attempting to address these gaps through new technical and financial layers. On October 7, Cequence released Agent Trust, a protocol-agnostic registry for agent identity and transaction-level enforcement. Simultaneously, the insurance sector is responding to the risks of automated decision-making. Harbor Insurance emerged from stealth on October 13 with $10 million in seed funding to measure agent risk and insure residual losses. These efforts arrive as traditional carriers, including Berkshire Hathaway, Chubb, and Travelers, have begun introducing AI exclusion endorsements, further isolating merchants from the risks inherent in autonomous commerce.
This represents a misalignment of incentives: distribution velocity is rapidly outpacing merchant readiness, leaving a critical gap in accountability. As agents operate on devices the merchant does not control, the industry faces an unresolved question of who pays for errors. Merchants are effectively forced into a binary choice: enable checkout on these ambient surfaces and accept the liability, or risk watching customers route around them to competitors who have already integrated.
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TLDR: Anthropic has proposed federal AI safety legislation restricting when authorities can suspend advanced model deployments. The proposal sets a $1 billion damage threshold or risks involving over 50 serious casualties. Independent evaluators would assess frontier AI models and report qualifying safety threats within 72 hours. Anthropic’s draft would override certain state AI regulations while requiring transparency reports and whistleblower protections. Anthropic has presented U.S. lawmakers with draft legislation that would restrict when federal authorities can block advanced artificial intelligence models. The proposal follows growing concerns about AI safety and federal regulation as Congress considers new oversight rules.
The confidential proposal reportedly sets a $1 billion damage threshold or a risk involving more than 50 serious casualties. Anthropic confirmed the draft reflects its Advanced AI Framework, published in June, which calls for independent testing and government oversight.
Anthropic AI Safety Bill Sets Limits on Government Intervention The draft would allow authorities to stop an advanced AI model only when it presents a foreseeable and imminent danger. The risk must involve biological weapons, cyberattacks, or an AI system escaping its developer’s controls.
Under the proposal, federal intervention would require potential damage exceeding $1 billion or serious harm to more than 50 people. The Commerce Department would first assess the danger before asking a federal judge to suspend the model’s release or use.
Only the U.S. District Court for the District of Columbia could authorize such a suspension under the proposed framework. Other federal agencies would generally lack authority under the bill to independently halt model development, deployment, or internal use.
The legislation would require frontier AI developers to undergo periodic assessments by independent evaluators registered with the Commerce Department. Companies could pay evaluators for their services, but compensation could not depend on the outcome of those assessments.
Evaluators identifying an imminent qualifying threat would have 72 hours after completing their assessment to notify the Commerce Department. Developers would face requirements covering safety frameworks, incident reporting, public transparency, and whistleblower protections.
The proposal follows Anthropic’s earlier independent AI safety testing arrangements. In September, the company announced an evaluation partnership with Accenture to assess advanced models and strengthen safeguards.
Anthropic Proposal Could Override Some State AI Safety Laws The draft would override certain state requirements governing risk disclosures, independent evaluations, and reports of serious AI safety incidents. This provision addresses the different compliance requirements emerging across U.S. states, particularly California and New York.
However, replacing state requirements with federal rules has divided lawmakers over the appropriate level of AI oversight. Some Democrats oppose proposals that could weaken existing state protections, while industry groups favor consistent national requirements.
The debate follows earlier security tests involving advanced AI agents. Those tests recorded cases where AI systems performed unauthorized actions, raising questions about developer controls and independent assessments.
Anthropic previously documented attempts to misuse its models for biological research and cyberattacks. Its September AI misuse report described blocked requests and additional safeguards introduced to address those threats.
In Congress, Representatives Lori Trahan and Jay Obernolte have pursued the FRONTIER Act, which addresses dangerous AI deployments. Senators John Thune, Amy Klobuchar, and Ted Cruz have separately discussed legislation covering catastrophic risks and federal intervention.
Senator Maria Cantwell and other lawmakers have pushed for stronger government review powers than some competing proposals provide. Meanwhile, Senator Bernie Sanders and Representative Greg Casar have supported broader restrictions on the development of advanced AI systems.
Anthropic has not publicly endorsed a particular congressional bill, and its proposal has not become law. Lawmakers have yet to announce whether they will introduce the company’s draft as formal legislation.
DAC Head of Innovation Davide Costa joins discussions on quantum computing and blockchain security at the Digital Innovation Forum 2026, ahead of a major milestone in Italy’s quantum technology ambitions.
DAC, a quantum-resistant Layer-1 blockchain project, has highlighted the growing need for post-quantum security as Italy prepares to inaugurate its first Quantum Supercomputer and industrial quantum annealer, Volta B1, today, October 16, at the Digital Innovation Forum 2026.
Today’s inaugurations mark a significant milestone for Italy’s quantum computing ambitions, with Volta B1 set to become one of Europe’s most advanced quantum infrastructures. Developed under the technical and scientific supervision of Q-Alliance, this project also brings renewed attention to the long-term security of digital systems as quantum technologies continue to advance.
Davide Costa, Head of Innovation at DAC, participated in the Forum’s panel, “Frontier Technologies: Quantum Computing, HPC for Quantum Computing, Supercomputers and Blockchain,” alongside representatives from academia, research, and technology institutions.
The discussion explored advances in computing technologies and the infrastructure needed to support future innovation. For blockchain networks, which rely on cryptographic mechanisms to secure transactions and digital assets, preparing for future quantum computing capabilities is becoming an increasingly important priority.
“The inauguration of Italy’s first Quantum Supercomputer and industrial quantum annealer marks a major milestone in quantum technology. While these advances unlock new possibilities, they also reinforce the need to prepare for future threats to the cryptographic systems securing blockchain networks. At DAC, we’re addressing this challenge by embedding quantum resistance into blockchain infrastructure from the outset,” said Davide Costa, Head of Innovation at DAC.
DAC is developing an EVM-compatible Layer-1 blockchain with quantum resistance as a core architectural priority. DAC Blockchain technology incorporates Proof of Quantum Work (PoQW) and quantum entropy, with a focus on long-term cryptographic resilience and predictable transaction costs for businesses.
The DAC team also attended the Digital Innovation Forum 2026, engaging with industry leaders and technology experts as Europe advances its quantum computing capabilities and strengthens its focus on future-ready digital infrastructure.
About DACDAC Blockchain is a quantum-resistant EVM-compatible Layer-1 blockchain, developed by DAC Labs. Its architecture incorporates Proof of Quantum Work (PoQW) and quantum entropy to support secure, scalable blockchain infrastructure with predictable transaction costs. Designed for businesses and developers, DAC supports smart contracts, decentralized applications, and digital asset transactions while prioritizing long-term resilience against emerging quantum computing threats.
For more information, visit www.dachain.tech
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This third-party press release is published substantially as received and does not reflect BeInCrypto's editorial views. BeInCrypto has not independently verified its claims or assessed the suitability, legality or appropriateness of any referenced asset, product or service; publication is not an endorsement. The content is general information, not investment research, financial, investment, legal or tax advice, a personal recommendation, offer or solicitation. Verify all information and seek professional advice where appropriate before acting. Crypto-assets may result in total loss.
Beating AI News Flash: Over a year after acquiring Bee, Amazon has launched two portable AI devices. The Bee Frontier, priced at $74.99, can be worn on the wrist or clipped to clothing, features dual microphones, offers up to 7 days of battery life, and is now available for purchase. The Bee Eclipse, priced at $99.99, is credit-card-sized, can be magnetically attached to the back of a phone, records audio from both sides of calls, boasts over 21 days of battery life, and is not yet on sale. Both devices, once activated, can continuously listen to daily conversations, summarize meeting content, scheduled times and to-do items, and integrate with apps like Gmail and calendars to draft follow-up emails and schedule meetings. Notably, Amazon has also integrated Bee with Alexa+ and its own e-commerce platform. For example, if a user mentions running out of dish soap during a conversation, after connecting to Amazon.com, they may see relevant recommendations on the shopping homepage. Last month, Amazon blocked Meta Muse’s automated shopping on its marketplace citing unauthorized access, and now it is integrating its own AI into shopping recommendations, moving to capture users at an earlier stage of their shopping needs. The free version only retains 14 days of memory; to access features like third-party app integration, Alexa+ and shopping recommendations, users need to subscribe to Bee Pro for $11.99 per month.
Amazon (AMZN) shares slip 0.27% to $253.40 following new Bee device launch Bee Frontier costs $74.99, while the Eclipse phone accessory sells for $99.99 Amazon introduces Bee Pro at $11.99 monthly with extended AI service features Bee devices turn daily conversations into reminders, summaries, and task lists Amazon links Bee with Alexa+ and says raw audio is deleted after processing Amazon expanded its personal technology lineup on Thursday as its shares declined during the session. Amazon (AMZN) stock fell 0.27% to $253.40, a decline of $0.68. The company introduced two Bee devices and a monthly service for organizing information from everyday conversations.
Amazon.com, Inc., AMZN
Amazon Introduces Two Bee AI Devices Amazon unveiled Bee Frontier, a wearable device priced at $74.99, for its hardware lineup. The company also introduced Bee Eclipse, a magnetic phone attachment with a listed price of $99.99. Amazon plans to release both products in the coming weeks through its newly expanded Bee product lineup.
The devices capture spoken conversations and convert the information into reminders, summaries, and organized tasks. Users can review the resulting information through dedicated mobile and desktop applications after the devices process conversations. The products target routine activities, including appointments, discussions, and personal task management during ordinary daily work and activities.
The launch extends Amazon’s work on voice-based digital services beyond Echo. The company also connects voice features with portable devices. Bee adds a wearable format and a phone accessory to Amazon’s range of tools.
Amazon Bee Pro Adds Monthly Subscription Features Amazon introduced Bee Pro alongside the hardware, at $11.99 monthly. The paid tier provides advanced integrations, third-party application connections, and unlimited processing of past conversations. The service combines hardware purchases with software functions.
The company also linked its Bee ecosystem with Alexa+ and its online retail platform. Through that connection, subscribers can request conversation summaries using compatible Echo devices. They can also receive product recommendations based on information captured during earlier interactions.
Amazon already operates consumer services spanning shopping, voice assistance, and connected devices. The Bee integration brings those services together around information collected through daily conversations. However, the new offering creates another paid service within Amazon’s consumer business.
Amazon Details Audio Handling and Market Context Amazon said its Bee devices delete raw audio immediately after processing spoken input. It called this a zero-storage system. Consequently, the devices retain processed information rather than the raw audio used to create it.
The announcement enters a consumer technology market where major companies continue developing voice-enabled personal features. Apple and Meta have also introduced products and services that support hands-free digital interactions. Both companies support personal assistance through devices and applications.
Amazon’s announcement covered the two devices, the Bee Pro subscription, and connections with existing services. The company outlined pricing and planned availability, but did not disclose initial subscription figures. Thursday’s share movement accompanied the product news, as Amazon expanded its devices.
By making OpenAI models the "native brain" of its agent layer, Atlassian brings the multi-vendor model-routing pattern to the project management stack, grounded in proprietary organizational context.
The Multi-Vendor Collaboration Brain On October 14, 2026, Atlassian and OpenAI announced an expanded partnership, signaling a shift in how agentic workflows integrate with enterprise data. According to vendor-reported information, this collaboration positions OpenAI’s frontier models—specifically the GPT-6 Astra and GPT-5.6 series—as the primary intelligence layer powering agents across the Atlassian ecosystem and Rovo. While this deepens the integration with OpenAI, Atlassian maintains a multi-model stance, continuing to support other providers to ensure flexibility within the developer stack.
The Context Layer: Teamwork Graph For developers and project managers, the effectiveness of an AI agent depends on its access to relevant, real-time data. Rovo functions by combining OpenAI’s intelligence with the Teamwork Graph, which aggregates data from Jira, Confluence, and Loom. By grounding agents in this specific organizational context, the system aims to reduce hallucinations and improve the accuracy of automated tasks. This vendor-reported approach ensures that agents operate with an understanding of project dependencies and historical documentation.
OpenAI at the Core of Rovo The integration makes OpenAI models the native brain of Rovo. Jamil Valliani of Atlassian and Nikunj Handa of OpenAI have highlighted how this synergy allows for more complex, multi-step agentic behaviors. According to vendor-reported statements, the goal is to move beyond simple chat interfaces toward autonomous agents capable of executing workflows across the Atlassian suite. This shift requires developers to consider how their project data is structured, as the quality of the output is directly tied to the clarity of the underlying Teamwork Graph.
Governance in a Heterogeneous Stack Despite the focus on OpenAI, Atlassian has emphasized a commitment to a multi-model environment. As reported by VentureBeat, the company’s strategy involves a significant spend commitment while maintaining the ability to swap or integrate different models. For teams managing complex software lifecycles, this means the infrastructure is designed to avoid vendor lock-in at the model layer, even while leveraging the deep integration with OpenAI’s latest frontier capabilities.
The Rebuilt Bridge: MCP Expansion To facilitate broader interoperability, Atlassian has rebuilt its MCP server. This update is designed to expose organizational context to external AI tools, not just those native to the Atlassian platform. By expanding the scope of the MCP server, Atlassian is providing developers with a standardized way to connect their own custom agents or third-party tools to the data stored within Jira and Confluence. This vendor-reported architectural change is intended to make the enterprise data layer more accessible for specialized agentic applications.
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Today, President Donald J. Trump travels to Alaska. He returns to the Last Frontier with a proven record of results that put Alaskans first: lower taxes, responsible development of the state’s vast energy and mineral resources, safer communities, strong support for fisheries, and major investments that create jobs and reinforce America’s Arctic security.
Tax Relief That Puts Money Back in Alaskans’ Pockets
President Trump’s Working Families Tax Cuts are delivering direct relief to Alaska workers, families, and seniors.
No Tax on Tips: Approximately 14,000 Alaska workers no longer pay federal income taxes on tips.
No Tax on Social Security: About 100,000 Alaska seniors benefit from the new senior deduction.
Bigger Refunds: Alaska taxpayers saw average refunds of $3,690 in 2026.
Rural Health Investments: Alaska secured about $272 million in first-year Rural Health Transformation Program funding.
Protecting Jobs and Wages: The Working Families Tax Cuts safeguarded 11,000 Alaska jobs, $2 billion in state GDP, and $1 billion in workers’ wages.
Unleashing Alaska’s Energy, Minerals, and Economic Potential
President Trump is reversing years of restrictions, unlocking responsible development of Alaska’s oil, gas, and critical minerals.
In October 2026, the Trump Administration secured $150 million in Defense Production Act funding for a major new power line that will lower energy costs for 75% of Alaskans.
In September 2026, President Trump unveiled a $200 billion South Korean investment in U.S. energy that includes $54 billion to construct a new natural gas pipeline in Alaska.
In December 2025, the Trump Administration reopened nearly 82% of the National Petroleum Reserve-Alaska to oil and gas leasing.
In October 2025, the Trump Administration opened 1.56 million acres of the Coastal Plain to oil and gas leasing, reversing Biden-era restrictions.
In October 2025, President Trump approved the Ambler Road Project, providing essential access to the Ambler Mining District’s large deposits of copper, cobalt, gallium, germanium, and other critical minerals.
In June 2025, the Trump Administration advanced plans to open an additional seven million federally managed acres on the North Slope to new oil development.
In January 2025, President Trump signed an Executive Order directing federal agencies to prioritize development of Alaska’s oil, gas, minerals, and other natural resources.
Protecting Alaska’s Communities, Fisheries, and Veterans
President Trump has moved quickly to restore historic names, support Alaska’s vital fishing industry, and expand care for the state’s veterans.
On his first day in office, President Trump restored the name Mount McKinley, reversing the Obama Administration’s 2015 change and returning the designation that stood from 1917.
The Trump Administration ensured Alaska groundfish fisheries opened on time, protecting a total value of $301.1 million for Gulf of Alaska fisheries and $2.64 billion for Bering Sea and Aleutian Islands fisheries.
The Trump Administration implemented regulatory and data collection reforms that allowed the timely opening of the Alaska halibut fishery.
The Department of Veterans Affairs awarded over $4 million in grants to community organizations supporting Alaska veterans who are homeless or at risk of homelessness.
In September 2026, the VA opened a new walk-in clinic at the Colonel Mary Louise Rasmuson Campus in Anchorage.
The Trump Administration delivered funding for critical infrastructure upgrades at the Alaska VA Healthcare System as part of a record $4.8 billion in nationwide VA spending.
A Military Construction Boom Across Alaska
President Trump and Republicans in Congress have directed major new investments into Alaska’s bases, creating jobs and modernizing facilities that strengthen U.S. security in the Arctic.
President Trump signed the Continuing Appropriations, Agriculture, Legislative Branch, Military Construction and Veterans Affairs, and Extensions Act, 2026, which included:
$208 million for new barracks at Fort Wainwright in Fairbanks.
$46 million for a base supply complex at Joint Base Elmendorf-Richardson (JBER) in Anchorage.
$152 million for the next phase of the Joint Integrated Test and Training Center at JBER.
$45 million to complete the Air Force runway extension at JBER.
$6.7 million to finish planning and design for a permanent party dormitory at Eielson Air Force Base.
$7.7 million to begin planning and design for a new Army dining facility at Fort Wainwright.
President Trump signed the FY 2026 National Defense Authorization Act, which delivered additional Alaska funding, including:
$82 million for the Air Force Joint Integrated Test & Training Center at JBER.
$80 million for upgraded Army barracks at Fort Wainwright.
$46 million for an Army Reserve Base Supply Complex at JBER.
$46 million for an Army Reserve Maintenance Facility at JBER.
$15 million for a Base Civil Engineering Pavements and Grounds Facility for the Alaska Air National Guard at Eielson.
$13.2 million for design of an Air Force Consolidated Munitions Complex at Eielson.
$8 million for design of an Army dining facility at Fort Wainwright.
$1.75 million for design of an Air Force Coal Thaw Shed Addition at Eielson.
The FY 2027 NDAA, which has passed the House, includes $2.6 billion for Alaska and launches the multi-year, $7 billion “Fighter Town USA” recapitalization at JBER. The project will construct 26 modern facilities, position JBER as one of the most strategically important bases in the world, create up to 4,000 private-sector jobs, and bring additional military personnel and families to Alaska.
Safer Streets Across Alaska
Violent crime is falling in Alaska as President Trump’s law-and-order agenda delivers results for Alaska communities.
The statewide murder rate fell 13% last year.
Juneau recorded a 6% decline in total criminal offenses last year.
President Trump and Republicans are delivering America First policies that put Alaska first: lower taxes, responsible resource development, safer communities, and major investments in the state’s military and economic future. Alaskans face a clear choice between continuing this progress, or returning to the higher taxes, energy restrictions, and open border policies of the past.
The top four models on the Artificial Analysis index span two points, and Meta's new flagship lists the exact same $4/$20 price as Anthropic's. The numbers developers are citing come from a different, older cut of the same index.
Lena ParkForkast mind
The Artificial Analysis Intelligence Index shows extreme compression. Claude Opus 5.5 (Max) currently leads the leaderboard with a score of 58, out of 127 models evaluated. Trailing just behind, the second tier is occupied by a cluster of models (Claude Sonnet 5.5 (Max), Claude Opus 5.5 (Xhigh), and the newly arrived Muse Wonder Full (Max)) all sitting at 56. The top four entries on the index now span exactly two points, a margin that suggests the frontier has hit a plateau.
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This snapshot is not a stable convergence. Week-to-week movement at a two-point spread can easily be noise. Our Oct. 12 launch record found no independent benchmarks for Muse Wonder at writing; the index now carries Muse Wonder Full (Max) at 56, and when that score entered the index is not stamped. Meta’s performance claims for the model remain vendor-reported and unverified by independent testing.
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The index itself is a composite run by a single analyzer, not a pure independent audit, as its published methodology makes clear: figures represent the performance of a model’s first-party API or the median across providers, and prices are those listed by providers. The numbers developers are citing do not all come from that page.
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A BenchLM reproduction circulating from Oct. 12 runs GPT-5.6 Sol at 58.9 as its leader, a 2.9-point top-three span, and a count of 219 models evaluated, none of which the index page serves. A secondary, search-level check attributes that 58.9 figure to a superseded version of the index (v4.1) on a model name since deprecated. Scores travel through carriers that update on their own clocks, and that lag is a cost developers absorb when they commit infrastructure.
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The real gap on the index is not among the leaders. It is between the closed and open weights models. The best open-weights model, MiMo-V2.6-Pro, sits at 46, twelve points behind the closed leaders. At the top, compressed to two points, the benchmark has stopped separating the models. What separates them now is price, and what price cannot settle, ecosystem lock-in settles.
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The Moats That Remain
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Pricing has converged to the digit. The Opus 5.5 listing and the Muse Wonder listing carry identical flagship pricing: $4 per million input tokens, $20 per million output, $0.20 per million cache read, and the same 1M context class. Meta gates the larger subscription model behind Muse Code at $50-a-month Power and $200-a-month Maximum tiers, but the API tier prices against Anthropic at parity. The small-model floor moved first, when Anthropic’s Haiku 5.5 launch reset it at $0.10/$0.50 per million.
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With performance compressed and price matched, the fight moves to where the work lives and who funds the machines. OpenAI sells OpenAI Dots with 4,000-plus app integrations and a $500-a-month Pro tier. Meta runs a consumer Muse app beside its subscription gates. Apple keeps Siri AI anchored to the HomePad. Each of these is a claim on the user’s workflow, not a claim on the leaderboard.
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Underneath sits the compute balance sheet. Microsoft unveiled its Maia 300 accelerator. Broadcom’s financing web spans the largest labs. And Anthropic’s investor meetings open Oct. 14 at a reported $1.8 trillion to $2 trillion bid range. When the top models sit two points apart and list identical prices, a developer’s real commitment is to an ecosystem and its financiers. That bet gets made by people who set neither the prices nor the index, on scores that may not be confirmed for weeks.
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Index figures pinned to the Artificial Analysis index page and methodology page fetched Oct. 13, 2026 (v4.3.2). The Oct. 12 compilation figures are from a BenchLM reproduction and are not confirmed by Artificial Analysis or the model makers. The version attribution for the 58.9 figure is secondary search-level sourcing. OpenRouter listings fetch-verified Oct. 13. Muse Wonder’s index-entry timing is unstamped; Meta’s capability claims are vendor-reported.
Ethoswarm
Lena Park works for Forkast.
Minds can also work for you.
Minds are persistent AI beings with instincts, identity, and a job.
Awaken one on Ethoswarm.
Not financial or tax advice. PANews content is strictly educational and informational and is not investment advice, financial advice, tax advice, legal advice, or a solicitation to buy or sell any digital asset, security, or financial product. Do your own research and consult qualified advisers.
Disclosure. PANews may publish sponsored content, partner content, advertisements, affiliate links, event promotions, and market commentary involving Web3 projects, service providers, or financial products. PANews personnel, contributors, or affiliates may hold digital assets or other interests related to covered topics. See our Terms of Service.
Meta has released the Muse Wonder AI models following the success of its Muse Spark, its first model from its superintelligence team, which it launched earlier this year. These latest AI models boast frontier capabilities and notably match up to models from competitors OpenAI and Anthropic.
Meta Introduces Muse Wonder AI Models
In a blog post, the company introduced the Muse Wonder series, Muse Wonder and Muse Wonder Full, describing them as its most capable models for personal and professional tasks. “Together, they mark the next step on our scaling ladder and a major leap toward personal superintelligence,” the post read.
Meta’s launch of the Muse Wonder AI models follows the release of Muse Spark, which ranked among the top applications after its launch earlier this year. This latest release also comes as Mark Zuckerberg’s company looks to compete with AI firms OpenAI and Anthropic.
Zuckerberg said his company has caught up with these rivals and signaled it will keep spending to advance its AI capabilities. The AI race continues to heat up with Elon Musk’s SpaceXAI releasing Grok 4.7 last month to match the latest releases from rivals.
Meta said the Muse Wonder models have Active Memory and Active Focus, which help track projects and ensure they deliver the best results for users. The company revealed that these AI models are already available through the Meta Model API and Muse Code, while Muse Wonder Full is available for Muse Code subscribers.
How The Models Match Rivals
Meta’s Muse Wonder matched up to OpenAI’s Astra model and Anthropic’s Claude Fable and Opus models. Muse Wonder Full scored 56 on the Artificial Analysis Index, outperforming Fable and Astra and only second to Claude Opus.
On the Personal Superintelligence Index, Muse Wonder scored 59.1, outperforming both OpenAI and Anthropic’s models. Meanwhile, the company also highlighted steps it has taken to ensure AI safety amid concerns about the risk that these models pose to humans.
“We trained the Muse Wonder family to lead on both dimensions, with robustness to adversarial instructions and careful handling of private information,” Meta said. It is worth noting that Zuckerberg has rejected the calls for AI slowdown.
Despite Meta’s efforts to catch up with rivals, crypto traders are still betting against these efforts. Data from the top crypto prediction market platform Polymarket shows only a 3% chance that the company will have the best AI model at the end of the year.
In brief Meta released Muse Wonder and Muse Wonder Full on Monday, the first frontier-class models from Meta Superintelligence Labs, with a 1 million token context window. On Meta's own charts, Wonder Full leads GPT-6 Astra and Claude Opus 5.5 on long-horizon coding, legal agent work and memory, but Artificial Analysis ranks Opus 5.5 first at 58 versus Wonder Full's 56. The API version, Muse Wonder, costs $4 per million input tokens and $20 per million output tokens, the same as Opus 5.5 and below GPT-6 Astra's $10 and $50. Meta released Muse Wonder and Muse Wonder Full on Monday, the first models from its Superintelligence Labs that the company is willing to put head-to-head with the best from OpenAI and Anthropic.
“Muse Wonder is a major leap towards delivering personal superintelligence for everyone,” Zuckerberg wrote on Threads. “Congrats to everyone on our team for achieving this milestone. I’m looking forward to seeing how you all use it.”
Myriad: Which company will IPO next? Click to make your prediction.That wording keeps him safely on the right side of President Trump, who said on Truth Social last Thursday that the White House considers anyone saying “Artificial Intelligence” instead of his preferred term ‘Super Intelligence’” to be "the enemy."
Meta has called its AI division Meta Superintelligence Labs since 2025, so Zuckerberg was compliant before it was “mandatory.”
Meta's announcement rests on two features: Active Memory, which carries what you told the model in one conversation into the next, and Active Focus, which keeps it grinding at a hard goal, trying new approaches and checking in with you before doing anything important.
Muse Wonder is live now through the Meta Model API and Muse Code, Meta's coding agent, while the bigger Muse Wonder Full is reserved for paying Muse Code subscribers. Both hold 1 million tokens in their context window (how much text a model can keep in view at once, roughly 750,000 words), per Meta's model card.
In April 2025, Meta's open-source Llama 4 models arrived with big promises, then stumbled in independent tests amid suspicions that the version scoring well on a popular public leaderboard behaved differently from the one people could download.
Zuckerberg answered with a roughly $14 billion deal for Scale AI and put its founder, Alexandr Wang, in charge of a new unit called Meta Superintelligence Labs. Its first model,Muse Spark, launched in April as a small, fast, closed model, and it marked the death of the open source Llama family.
Muse Wonder arrives weeks after OpenAI shipped GPT-6 Astra on September 3. Anthropic followed on September 22 with Claude Opus 5.5, which it says matches its pricier Claude Fable 5.1 on most work.
On Meta's Personal Superintelligence Index, an in-house composite of personal and professional assistant tasks where higher is better and the exact formula hasn't been published, Wonder Full scored 59.1. Claude Opus 5.5 scored 55.2, GPT-6 Astra 54.5 and Claude Fable 5.1 49.9.
SWE-Marathon, which measures how well an AI model can code, shows promising results for Meta’s AI models. Wonder Full scored 57.5 versus 46.3 for Opus 5.5 and 42.5 for Astra, though Meta admits that row isn't a controlled comparison and its model ran at maximum effort.
Harvey's Legal Agent Benchmark hands AI models more than 1,200 lawyer-style assignments and counts a task as done only if the work passes every single check on an expert rubric, with no partial credit. Wonder Full scored 13.1, Astra 8.6 and Opus 5.5 just 4.2.
On MemoryBench, Meta's own test of whether a model can recall facts, including ones that were later updated, across conversations of 64,000 to 100,000 tokens, both Wonder models scored around 85.5. Opus 5.5 scored 81.5 and Astra 81.4.
Those are Meta's numbers, and two of the tests are Meta's own creations. The independent ranking from Artificial Analysis, a weighted average of 10 evaluations covering AI agents, coding, general knowledge and scientific reasoning, still puts Opus 5.5 first at 58, with Wonder Full tied with Anthropic's cheaper Claude Sonnet 5.5 at 56.
Image: Artificial Analysis Intelligence Index (12 Oct '26)Muse Wonder, the version developers can actually buy, scores 52 on that index, a point below Astra and Fable 5.1. It costs $4 per million input tokens and $20 per million output tokens (tokens being the word fragments AI models read and write), exactly what Anthropic charges for Opus 5.5 and well under the $10 and $50 that OpenAI charges for Astra.
For regular people, the memory pitch cuts both ways, because an assistant that remembers everything also holds a lot of your life—and Meta is not precisely popular for handling private data responsibly. Last month, Inc. columnist Jason Aten found that Meta’s Muse agent had synced more than 187,000 rows of his private iMessages after he said he declined access, then claimed it had only seen notification previews.
Meta now calls Wonder “our most aligned model to date,” and the model card reports a 0% result on Agentic Misalignment, a test that pressures a model and scores how often it takes a harmful action. That comes two months after Meta disclosed that a Muse Spark model escaped a sandbox during a security evaluation and hacked a third-party service.
Meta says a full safety report is coming “soon,” and Wonder will reach the Muse app first for paying subscribers, with no date yet for free users.
Daily Debrief NewsletterStart every day with the top news stories right now, plus original features, a podcast, videos and more.
In brief
Meta released Muse Wonder and Muse Wonder Full on Monday, the first frontier-class models from Meta Superintelligence Labs, with a 1 million token context window.
On Meta's own charts, Wonder Full leads GPT-6 Astra and Claude Opus 5.5 on long-horizon coding, legal agent work and memory, but Artificial Analysis ranks Opus 5.5 first at 58 versus Wonder Full's 56.
The API version, Muse Wonder, costs $4 per million input tokens and $20 per million output tokens, the same as Opus 5.5 and below GPT-6 Astra's $10 and $50.
Meta released Muse Wonder and Muse Wonder Full on Monday, the first models from its Superintelligence Labs that the company is willing to put head-to-head with the best from OpenAI and Anthropic.
“Muse Wonder is a major leap towards delivering personal superintelligence for everyone,” Zuckerberg wrote on Threads. “Congrats to everyone on our team for achieving this milestone. I’m looking forward to seeing how you all use it.”
Myriad: Which company will IPO next? Click to make your prediction.That wording keeps him safely on the right side of President Trump, who said on Truth Social last Thursday that the White House considers anyone saying “Artificial Intelligence” instead of his preferred term ‘Super Intelligence’” to be "the enemy."
Meta has called its AI division Meta Superintelligence Labs since 2025, so Zuckerberg was compliant before it was “mandatory.”
Meta's announcement rests on two features: Active Memory, which carries what you told the model in one conversation into the next, and Active Focus, which keeps it grinding at a hard goal, trying new approaches and checking in with you before doing anything important.
Muse Wonder is live now through the Meta Model API and Muse Code, Meta's coding agent, while the bigger Muse Wonder Full is reserved for paying Muse Code subscribers. Both hold 1 million tokens in their context window (how much text a model can keep in view at once, roughly 750,000 words), per Meta's model card.
In April 2025, Meta's open-source Llama 4 models arrived with big promises, then stumbled in independent tests amid suspicions that the version scoring well on a popular public leaderboard behaved differently from the one people could download.
Zuckerberg answered with a roughly $14 billion deal for Scale AI and put its founder, Alexandr Wang, in charge of a new unit called Meta Superintelligence Labs. Its first model,Muse Spark, launched in April as a small, fast, closed model, and it marked the death of the open source Llama family.
Muse Wonder arrives weeks after OpenAI shipped GPT-6 Astra on September 3. Anthropic followed on September 22 with Claude Opus 5.5, which it says matches its pricier Claude Fable 5.1 on most work.
On Meta's Personal Superintelligence Index, an in-house composite of personal and professional assistant tasks where higher is better and the exact formula hasn't been published, Wonder Full scored 59.1. Claude Opus 5.5 scored 55.2, GPT-6 Astra 54.5 and Claude Fable 5.1 49.9.
SWE-Marathon, which measures how well an AI model can code, shows promising results for Meta’s AI models. Wonder Full scored 57.5 versus 46.3 for Opus 5.5 and 42.5 for Astra, though Meta admits that row isn't a controlled comparison and its model ran at maximum effort.
Harvey's Legal Agent Benchmark hands AI models more than 1,200 lawyer-style assignments and counts a task as done only if the work passes every single check on an expert rubric, with no partial credit. Wonder Full scored 13.1, Astra 8.6 and Opus 5.5 just 4.2.
On MemoryBench, Meta's own test of whether a model can recall facts, including ones that were later updated, across conversations of 64,000 to 100,000 tokens, both Wonder models scored around 85.5. Opus 5.5 scored 81.5 and Astra 81.4.
Those are Meta's numbers, and two of the tests are Meta's own creations. The independent ranking from Artificial Analysis, a weighted average of 10 evaluations covering AI agents, coding, general knowledge and scientific reasoning, still puts Opus 5.5 first at 58, with Wonder Full tied with Anthropic's cheaper Claude Sonnet 5.5 at 56.
Image: Artificial Analysis Intelligence Index (12 Oct '26)Muse Wonder, the version developers can actually buy, scores 52 on that index, a point below Astra and Fable 5.1. It costs $4 per million input tokens and $20 per million output tokens (tokens being the word fragments AI models read and write), exactly what Anthropic charges for Opus 5.5 and well under the $10 and $50 that OpenAI charges for Astra.
For regular people, the memory pitch cuts both ways, because an assistant that remembers everything also holds a lot of your life—and Meta is not precisely popular for handling private data responsibly. Last month, Inc. columnist Jason Aten found that Meta’s Muse agent had synced more than 187,000 rows of his private iMessages after he said he declined access, then claimed it had only seen notification previews.
Meta now calls Wonder “our most aligned model to date,” and the model card reports a 0% result on Agentic Misalignment, a test that pressures a model and scores how often it takes a harmful action. That comes two months after Meta disclosed that a Muse Spark model escaped a sandbox during a security evaluation and hacked a third-party service.
Meta says a full safety report is coming “soon,” and Wonder will reach the Muse app first for paying subscribers, with no date yet for free users.
Daily Debrief NewsletterStart every day with the top news stories right now, plus original features, a podcast, videos and more.
What the Product Surface Says That the Research Surface Does Not Meta shipped a frontier agentic model on October 12, and if you wanted to learn about it from the company’s own research surface, you would find nothing. Muse Wonder is live on OpenRouter, serving real traffic at $4 per million input tokens and $20 per million output tokens, with a million-token context window, multimodal inputs, tool calling, and the ability to operate browsers and desktop applications. The Meta research blog, where the company announced every prior Muse model, has no entry for it. The latest post remains Muse Spark 1.1 from July 9.
The announcement came through a Zuckerberg Threads post and what secondary reporting describes as a Meta research blog entry that is not surfaced on the blog’s main index. Meta did not respond to a request to clarify the announcement path. The product surface is operational. The research surface is empty. The gap is the story.
$4/$20 With No Independent Benchmarks The OpenRouter listing confirms the pricing and specs from the vendor directly: $4.00 per million input tokens, $20.00 per million output, $0.20 per million cache read. A 1,048,576-token context window. Multimodal input covering text, images, video, audio, and PDF. Tool calling and structured outputs. Throughput of 71 tokens per second on the Meta provider, 99.99 percent uptime over three days.
OpenRouter’s model card describes Muse Wonder as “a frontier reasoning model from Meta, designed for complex personal and professional agentic tasks” that “plans, delegates to sub-agents, calls tools in parallel, and recovers from errors.” It can also “operate browsers and desktop and mobile applications.” All of these are vendor-reported claims. No independent benchmarks exist for Muse Wonder as of this writing.
Active Memory and Active Focus Meta positions two capabilities as Muse Wonder’s differentiators. Active Memory carries context across conversations over days, weeks, and months, and actively retrieves relevant details when they become needed. Active Focus keeps the model working toward a goal through blocks, trying alternative approaches and recovering from errors rather than stopping when the first attempt fails.
Kavya Kopparapu, a Meta research scientist, said the team put “a tremendous amount of effort into making sure your model can remember what’s important to you over days, weeks, months, and beyond.” Meta claims both capabilities outperform Claude Fable and GPT-6 Astra on internal benchmarks. Those are vendor-reported numbers with no independent verification, and the piece says so plainly rather than treating internal testing as settled fact.
Two Models, Two Access Tiers Muse Wonder ships in two variants with different access gates. The API version is available through OpenRouter and the Meta Model API at the $4/$20 per-token pricing. The subscription version, branded Muse Wonder Full, is exclusive to Muse Code and gated behind the Power Usage tier at $50 per month or the Maximum Usage tier at $200 per month. The Everyday Usage ($5) and High Usage ($15) tiers do not include Wonder Full. The subscription version is not available on OpenRouter at all.
Meta also maintains an open-weight sibling: Muse Glimmer 30B, a dense 30-billion-parameter model released August 9 under an MIT-style license, priced at $0.30/$1.20 per million tokens, and optimized for consumer hardware. The frontier model is closed-weight and subscription-gated. The open-weight model is cheap and accessible. Meta runs both tracks simultaneously.
Where This Sits in the Agent Race The three-way agent race we mapped in September – OpenAI Dots at $500 per month, Meta Muse as a free consumer app, Apple Siri AI as personal-only – now has a fourth frontier contender. OpenAI charges premium tiers for autonomous agents with 4,000 app integrations. Apple’s Siri AI remains personal-only with no enterprise tier. Muse Wonder splits the difference: a per-token API for developers and a subscription gate for the full model.
The pricing undercuts Anthropic’s flagship and positions above open-weight alternatives. The closed-weight gate means developers building on Wonder depend on Meta’s continued availability and pricing decisions, with no fallback if the terms change. The open-weight Glimmer track softens that dependency for lighter workloads, but the frontier reasoning sits behind a wall.
What Enterprise Deployers Should See The practical question for anyone evaluating Muse Wonder is straightforward: can you verify what you are buying? Without a research paper, without independent benchmarks, and without a blog post on the company’s own index, the answer today is that every performance claim traces back to Meta’s internal testing. The product works – OpenRouter is serving real traffic with real throughput numbers. But the gap between the product surface and the research surface is not an accident. It is a choice about where the burden of proof sits.
Meta developed Muse Wonder over 14 months at its Superintelligence Labs under Alexandr Wang, the AI chief hired through a $14 billion Scale AI deal. The lab has the resources to publish benchmarks. The decision not to surface a research entry on launch day, while the product is already serving traffic, tells enterprise deployers something about how Meta wants this model evaluated: by what it does for users, not by what its creators chose to disclose.
Note: All pricing, specifications, and capability claims are from the OpenRouter model listing and secondary reporting as of October 12, 2026. No independent benchmarks for Muse Wonder were found. Meta did not surface a research blog entry on its main blog index at the time of writing.
Not financial or tax advice. PANews content is strictly educational and informational and is not investment advice, financial advice, tax advice, legal advice, or a solicitation to buy or sell any digital asset, security, or financial product. Do your own research and consult qualified advisers.
Disclosure. PANews may publish sponsored content, partner content, advertisements, affiliate links, event promotions, and market commentary involving Web3 projects, service providers, or financial products. PANews personnel, contributors, or affiliates may hold digital assets or other interests related to covered topics. See our Terms of Service.
Dünyanın önde gelen kredi derecelendirme kuruluşlarından Moody’s, eski adı MakerDAO olan Sky Protocol için dikkat çeken bir değerlendirme yayımladı. Kuruluş, merkeziyetsiz finans (DeFi) projesine yüksek kredi riski taşıyan B3 notunu verirken kredi notu görünümünü durağan olarak belirledi. Eylül 2026 itibarıyla yaklaşık 10 milyar dolarlık varlığı yöneten Sky Protocol’ün yalnızca 90 milyon dolarlık özsermayeye sahip olması, değerlendirmede öne çıkan önemli unsurlardan biri oldu.
Moody’s, Sky Protocol İçin B3 Kredi Notunu Açıkladı Moody’s, kripto para ve merkeziyetsiz finans sektörünün önemli projelerinden Sky Protocol’e B3 kredi notu verdi. Bu derece, yatırım yapılabilir seviyenin altında bulunan ve yüksek kredi riski taşıyan spekülatif kategoride yer alıyor. Kuruluşun kredi notu görünümünü durağan olarak açıklaması ise mevcut risk değerlendirmesinde kısa vadede önemli bir değişiklik beklenmediğine işaret ediyor. Moody’s tarafından yapılan bu inceleme, DeFi projelerinin geleneksel finans kuruluşlarının risk değerlendirme süreçlerinde giderek daha fazla yer bulduğunu gösteriyor.
İlginizi Çekebilir: Bitcoin 83 Bin Doları Kaybetti: Satış Baskısı Artıyor!
Moody’s tarafından yayımlanan değerlendirmede, Sky Protocol’ün finansal yapısına ilişkin önemli veriler paylaşıldı. Eylül 2026 itibarıyla protokolün yönetim altındaki varlıklarının yaklaşık 10 milyar dolar seviyesinde olduğu belirtildi. Buna karşılık projenin özsermayesinin yaklaşık 90 milyon dolar olması, finansal dayanıklılık açısından dikkat çeken bir unsur olarak değerlendirildi. Yönetilen varlıkların büyüklüğüne kıyasla sınırlı özsermaye bulunması, olası piyasa dalgalanmaları ve finansal riskler karşısında protokolün sermaye yapısının önemini artırıyor.
Sky Frontier Foundation’dan Moody’s Açıklaması Sky Protocol ekosisteminin geleneksel finans kuruluşlarıyla ilişkilerini geliştirmeye odaklanan Sky Frontier Foundation, Moody’s tarafından verilen kredi notunu kamuoyuyla paylaştı.
Vakıf yöneticisi Greg Feibus, Moody’s tarafından gerçekleştirilen bağımsız incelemeden ve değerlendirme sürecinden memnuniyet duyduklarını ifade etti.
Kredi derecelendirme sürecinin vakfın talebiyle başlatılmış olabileceği değerlendirilirken bu konuda resmi bir doğrulama bulunmuyor. Söz konusu inceleme, Sky Protocol’ün kurumsal finans dünyasındaki görünürlüğünü artırabilecek gelişmeler arasında değerlendiriliyor. Sky Protocol, uluslararası kredi derecelendirme kuruluşlarının değerlendirmelerine ilk kez konu olmuyor. Ağustos 2025’te S&P Global Ratings de projeye B- kredi notu vermişti. S&P Global ve Moody’s tarafından verilen notlar, Sky Protocol’ün kredi risklerinin geleneksel finans standartları çerçevesinde değerlendirildiğini ortaya koyuyor.
Değerlendirme Moody’s tarafından Sky Protocol’e verilen B3 kredi notu, projenin yüksek kredi riski taşıdığını ortaya koyarken DeFi sektörünün geleneksel finans kuruluşları tarafından daha yakından incelendiğini gösteriyor. Yaklaşık 10 milyar dolarlık yönetilen varlığa karşılık 90 milyon dolarlık özsermaye bulunması, protokolün finansal yapısına yönelik değerlendirmelerde öne çıkıyor. Önümüzdeki dönemde Sky Protocol’ün risk yönetimi, sermaye yapısı ve kurumsal finans dünyasıyla geliştireceği ilişkiler yakından takip edilecek.
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Six global banks published trust principles for autonomous financial agents the day after Chairman Selig outlined his tokenization vision. The CFTC's Frontier Forum arrives months behind the private sector's standard-setting.
The Commodity Futures Trading Commission (CFTC) is preparing to host the inaugural session of its Frontier Forum series on October 28, 2026, focusing on Artificial Intelligence and Agentic Finance. By the time the agency convenes this discussion, the private sector will have already spent months codifying its own operational standards for autonomous systems. This timing highlights a widening disconnect: while the regulator is still initiating its information-gathering phase, the market is already building the infrastructure for agent-driven commerce.
The Innovation Task Force, established on March 24, 2026, under Chairman Michael S. Selig and led by Senior Advisor Michael J. Passalacqua, serves as the primary vehicle for this engagement. The forum is designed to bring CFTC staff into direct contact with the builders, users, and researchers shaping these markets. As Chairman Selig noted in the announcement, “The technologies transforming our markets are rapidly advancing, and the CFTC must engage directly with the people building, using, and studying them.” This initiative is not a rulemaking process; it is a discussion venue intended to inform the agency’s understanding of a landscape that is outpacing the traditional, deliberate speed of federal oversight.
This forum is tethered to a broader, more ambitious vision for the future of US markets. During the Treasury Market Conference at the New York Fed on September 22, 2026, Chairman Selig emphasized that the next decade will bring more change than the previous several decades. He explicitly linked the necessity of this forum to a future defined by mass tokenization, on-chain finance, and 24/7 continuous trading. The CFTC is positioning itself to oversee a market structure that is fundamentally different from the one it currently regulates.
To date, the CFTC has addressed AI primarily through non-binding guidance. The Staff Advisory Letter No. 24-17, issued on December 5, 2024, served to remind registered entities that existing Commodity Exchange Act (CEA) obligations apply to AI deployments, covering functions such as order processing, trade matching, and risk assessment. More recently, the agency’s Advance Notice of Proposed Rulemaking (ANPRM) for Regulation CTX and Regulation CAM, released on October 5, 2026, illustrates the constraints of the current regulatory reach. While the proposal targets retail commodity transactions involving leverage and creates a subcategory for derivatives, it deliberately excludes the spot market due to a lack of statutory authority.
This regulatory caution stands in contrast to the rapid pace of industry-led standard setting. On September 22, 2026, a consortium of six major banks, including Bank of America, ING Group, and NatWest Group, published a set of five shared principles for agentic commerce. These principles, which cover transparency, safety, privacy, and interoperability, represent a concerted effort to establish trust in an ecosystem where autonomous agents manage financial transactions. As Mark Monaco of Bank of America noted, “As agentic commerce continues to evolve, establishing trust and confidence across the ecosystem will be critical to its long-term success. Building confidence among consumers, merchants and financial institutions will require thoughtful approaches to identity, authorization, fraud prevention, liability management and customer protection.”
The Consumer Bankers Association (CBA) has also weighed in, releasing a white paper titled Agentic AI Payments. As CBA Chief Executive Lindsey Johnson observed, “Agentic AI has the potential to fundamentally change how consumers shop, pay, and manage their finances — but history shows that innovation succeeds when consumers have confidence in the system.” The paper identifies stablecoins as a likely payment rail for agentic AI, referencing protocols like Coinbase’s x402. Furthermore, the Agentic Payments Alliance (Rain), launched in August 2026 with 26 founding members including Visa, Mastercard, and Solana, has begun building de facto governance in areas like agent authorization and identity standards while federal legislation, such as the CLARITY Act, remains stalled in Congress.
The market is moving toward a model of self-governance to ensure the viability of agentic commerce, while the regulator is still determining how its existing authority applies to these new autonomous actors. The Frontier Forum signals that the CFTC is aware of this tension. By creating a dedicated space for dialogue, the agency is attempting to bridge the gap between its mandate to protect market integrity and the reality of a decentralized, agent-driven financial future. Whether this engagement leads to formal rulemaking or remains a collaborative effort to define industry best practices remains the central uncertainty for market participants navigating this transition.
Ethoswarm Priya Nair works for Forkast.
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