Anthropic and Gov. Newsom forge deal allowing California government to use Claude at half price
As Anthropic forges a closer relationship with the state of California, the federal government has made an enemy out of the OpenAI rival.
Anthropic
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Newsom and Anthropic reach deal to give local governments discounted access to Claude
The agreement would make Claude the first artificial intelligence tool available to all state agencies and local governments.
Amazon engineers are reportedly distilling Anthropic models to cut costs before new token-based pricing kicks in
Amazon engineers are already distilling Anthropic models into smaller, cheaper versions for internal use. Starting next year, Amazon will pay by tokens processed rather than compute hours, which could push costs up sharply. The company is also exploring alternatives like OpenAI. The article Amazon engineers are reportedly distilling Anthropic models to cut costs before new token-based pricing kicks in appeared first on The Decoder .
EU seeks AI independence as Austria proposes luring Anthropic to Europe
Austria's State Secretary for Digitalization, Alexander Pröll, is calling on the European Commission to explore bringing Anthropic to Europe. He's responding to the U.S. ban on advanced AI models from OpenAI and Anthropic for foreign users. The initiative is likely unrealistic, though. And the alternative floating in the background, Chinese AI models, would just trade one dependency for another. The article EU seeks AI independence as Austria proposes luring Anthropic to Europe appeared first on The Decoder .
Pair Nova 2 Lite with Claude for cost-optimized document processing
In this post, we show how pairing Amazon Nova 2 Lite with Anthropic’s Claude Sonnet 4.6 delivers an efficient solution for digitizing scanned documents at scale. We built a two-model pipeline on Amazon Bedrock for digitizing scanned yearbook pages. Amazon Nova 2 Lite handles native multimodal extraction in a single call: detecting photos, extracting visible names with coordinates, and returning page-level metadata. Claude Sonnet 4.6 then performs spatial reasoning to match names to faces based on page layout.
Claude Meets Blackwell Ultra: Anthropic’s Models Now Run on NVIDIA GB300 in Azure
Anthropic’s Claude models in Microsoft Foundry — hosted on Microsoft Azure and running on NVIDIA GB300 Blackwell Ultra GPUs — are now generally available, giving Azure-native enterprises a powerful new way to build autonomous and domain-specific AI agents. As agentic AI continues to drive enterprise innovation and becomes more autonomous, organizations need access to computing […]
Meta restricts use of Claude Code and Codex to keep rival AI out of its training data
Meta is restricting its engineers' use of Anthropic's Claude and OpenAI's Codex to prevent output from these AI tools from being incorporated into its own training data. The article Meta restricts use of Claude Code and Codex to keep rival AI out of its training data appeared first on The Decoder .
Chinas GLM-5.2 erreicht Anthropics Mythos bei der Schwachstellensuche
Zhipu AIs offenes Modell GLM-5.2 erreicht laut Sicherheitsexperten die Fähigkeiten von Anthropics Mythos bei der Bug-Erkennung.
WSJ Article Claiming China Has Matched Anthropic Is Obvious Nonsense
The Wall Street Journal printed an outright false headline and heavily misleading story claiming this, which of course was uncritically amplified by the usual suspects. I post this now on its own so that we have a place to link to, to explain the situation. Headline News WSJ Headline (Obvious Nonsense): China Has Matched Anthropic in Cybersecurity, Resetting AI Race. That. Did. Not. Happen. The post even claims, explicitly, that Claude Opus 4.8 similarly ‘matches’ Claude Mythos, a claim which is even more obviously false. Shame upon the Wall Street Journal. I fear Gell-Mann Amnesia. If they can get something as important as this so completely wrong, what about everything else? I am skipping over the parts that involve accurate reporting, or minor quibbles. It seems important to focus on clearly debunking the central false claims. Alas, the mistakes made here very much rhyme with mistakes being made throughout all this by the White House, and that get latched onto by certain bad actors, who have played a large part in leaving us unprepared for the Mythos Moment. For a full understanding of GLM-5.2, which is indeed an impressive open model, here is my full coverage of that release , placing it in proper context. It is important to understand what makes Mythos special. This is not it. What Makes Mythos Special What makes mythos special is not that only the chosen one can identify any given vulnerability in code. What makes Mythos special is that it can identify vulnerabilities…
Chinese AI model’s bug-hunting prowess narrows gap to US
A Chinese artificial-intelligence (AI) model whose launch has been hailed as another “DeepSeek moment” can go toe-to-toe with US rival Anthropic’s powerful Mythos model on cybersecurity tasks, researchers have said. Beijing-based start-up Zhipu AI’s GLM-5.2, released on June 13, beat Anthropic’s Claude Opus 4.8 model in benchmarking tests by cybersecurity company Semgrep, The Wall Street Journal reported. When Semgrep researchers gave it further instructions, GLM-5.2 matched that model and...
Brief an die EU: Österreich will Anthropic nach Europa holen
Zwischen Anthropic und der US-Regierung kommt es immer wieder zu Konflikten. In Wien drängt man darauf, das auszunutzen und die Firma nach Europa zu locken.
ITを揺るがす「エンタープライズ価格大転換」の波
SaaSおよびAIソフトウェア市場は価格の大転換期に入っている。従来型のSaaSと競合するAI製品の登場により、SaaSベンダーはシートベース（ユーザー数基準）の価格設定の見直しに迫られている。見直しの結果、従来型SaaSの価格はアウトカムベース（成果連動型）課金へと移行しつつある、これはCIOとCFOにとっては概ねプラスの動きだ。一方、一部のAIツールやSaaSパッケージは消費量ベースの課金へと向かっており、利用状況を注意深く管理しなければ、請求額が想定外に膨らむリスクがある。 CRMデータプラットフォームプロバイダーTwilioの戦略・オペレーション担当ディレクター、Sidharth Ramsinghaney氏は「最も差し迫った問題は、ほとんどの組織がこれまで経験したことのない予算の変動だ。この転換は、ベンダーから買い手に予測リスクを移転するものだ」と言う。Gartnerによれば、2030年までにエンタープライズSaaSの支出の少なくとも40%が利用量、エージェント、アウトカムベースの課金に移行し、シートベースのベンダー収益シェアは21%から15%に低下すると予測されている。 AIエージェントは価格モデルを揺るがす可能性を持っている。「AIエージェントが人間の業務を代替するようになれば、この予測は現実になる。以前は10人が必要だった仕事を1つのエージェントがこなせるなら、ユーザー数に基づくシートベースの課金は意味をなさなくなる」とRamsinghaney氏は言う。ただし、エージェントの導入が停滞すれば、シートベースの価格設定が長く続く可能性もある。不確実性が続けば、ハイブリッド型の価格設定がデフォルトになる可能性もある。 アウトカムベース課金の難しさ 一部の顧客がアウトカムベースの価格設定を求め、一部のベンダーが試験的に導入している。だが、実現は容易ではない。「アウトカムの帰属を明確に測定することが本質的に難しい」とRamsinghaney氏、「そのため、純粋なアウトカムベースの価格設定は多くのカテゴリーでまだ理想論にとどまる」と続ける。ソフトウェアコンサルティング会社Software Improvement GroupのCTO、Jasper Geurts氏も同意する。多くのAIベンダーはアウトカムではなく、シートベースと利用量の組み合わせに動いている。「エージェントはテストに合格しながら、誰も後から手を加えられない質の低いコードを生成することがある。機能すればいいという成果のみに課金するなら、将来の負債となるコードに対してお金を払っているのと同じだ」とGeurts氏は言う。 トークン経済の不透明さ AIベンダーのコスト構造は従来型SaaSとは異なる。フロンティアAIモデルのコストは下がるどころか上がっており、AnthropicのFable 5モデルはOpus 4.8の2倍のトークン単価だとGeurts氏は指摘する。「CIOたちはトークン経済が不透明だと言う。エージェントがどれだけトークンを消費するか予測できなければ、請求額の見通しが立てられない。CIOはトークンを10年前のクラウド支出と同様に扱うべきだ——つまり計測し、管理し、成果と結びつける必要がある」。 「シートベースの価格設定はヘッドカウントで請求額を抑えられた。利用量ベースの価格設定は消費量に応じてスケールする。AIがアシスタントから自律的なコーディングに移行するにつれ、コードの量はレビューしきれないほど増える。誰もレビューしきれないコードが積み上がれば、それ自体が将来の負担にな…
China’s Z.ai claims it can match Mythos on cybersecurity
China's Zhipu AI (Z.ai) released its open-weight GLM-5.2, and some researchers have claimed that it matches Mythos in certain bug-finding and cybersecurity scenarios. While GLM lags behind models from Anthropic and OpenAI in other, more general tasks, it seems that China has dramatically reduced the gap in the capabilities between its models and those of […]
Introducing GPT-5.6 series: Sol, Terra and Luna
The timing on this couldn’t be better. I run agentic systems daily - OpenClaw, Hermes, Claude Code orchestrating multiple AI workers. The bottleneck has always been cost at scale. Anthropic’s API pricing makes it brutal to run agents 24/7. You’re watching credits evaporate in real time. The fact that OpenAI allows third-party harnesses to tap into these models through an existing subscription changes the math completely. Looking forward to Sol Ultra powering my agents without per-token anxiety. And “Ultra” mode with subagents working together - that’s exactly where agentic AI needs to go. Thank you for making this accessible to builders, not just enterprises with infinite API budgets. Time to put these through their paces. I’ve got 6 DGX Sparks running great local model like Gemma4 and these 5.6 models are going to run it all.
GPT-5.6: The System Card
While we wait for a general release, the system card is the best hint as to what is going on with the new candidate for America’s Next Top Model, GPT-5.6. This is only an OpenAI model card, so by my standards it’s a light read. There’s a lot of things that you get in an Anthropic card, that are missing in an OpenAI card. Overall, the card gives a clear and consistent impression that GPT-5.6-Sol is a substantial improvement over GPT-5.5, but still short of Mythos. OpenAI calls it a ‘step function better’ than GPT-5.5. That seems accurate. OpenAI : Sol is our new flagship and a step function better than GPT-5.5. Terra delivers performance competitive to GPT-5.5 at 2x lower cost. Luna is our most cost-efficient model, delivering strong capability at our lowest cost. Together, the GPT-5.6 family gives people and developers more choice in how they balance intelligence, speed, and cost. Once available, pricing for GPT-5.6-Sol will be $5/$30, the same as GPT-5.5. Terra is $2.5/$15, Luna is $1/$6. They claim it will be on Cerebras at 750 TPS , which is insanely fast. Capacity will be limited, at least at first. They did not specify the price for that. There is a new higher thinking setting : Max. There is a new setting beyond Max called Ultra that lets GPT-5.6 spawn sub-agents. The intended strategy against bio and cyber misuse is defense-in-depth. My guess is that in practice this strategy is robust for now, but that the White House’s misunderstandings around Fable and what is and…
Evaluating Offline Monitoring of Internal AI Agents
This work was conducted during the GovAI Winter Fellowship 2026. Full report Executive Summary Frontier AI companies use offline monitoring to address risks from internally deployed AI agents. AI developers increasingly rely on AI agents for internal work, including for safety research and model training. At the same time, these companies are concerned that a misaligned model could exploit this access to take concerning actions, such as sabotaging efforts to understand the risks posed by AI. To identify such instances, AI companies have separate AI models called "monitors" that review transcripts of AI agents' actions and flag suspicious activity. Human reviewers examine activity flagged as suspicious by monitors, judge whether that activity is concerning, and decide on an appropriate response. This monitoring occurs offline, meaning that actions are reviewed after they have been executed rather than intercepted in real time. Companies currently assess the effectiveness of offline monitoring via synthetic attacks. To assess the effectiveness of offline monitoring, OpenAI and Anthropic use synthetic attacks – transcripts constructed to contain the kind of harmful actions a misaligned AI might take during deployment – and then check whether monitors flag them. Current reporting on assessments of effectiveness is insufficient. Given the information currently made public by Anthropic and OpenAI, external parties cannot assess the overall effectiveness of their offline monitoring…
Chinese cybersecurity firm builds AI tools to rival Mythos and frames the race as cyber-nuclear deterrence
360 founder Zhou Hongyi presents two AI security tools designed to compete with Anthropic's Mythos. One has already flagged 3,432 vulnerabilities. Zhou admits Chinese models trail Western ones by 20 to 30 percent, but compares Mythos to "cyber nuclear weapons" and calls for China to build its own strategic deterrent. The article Chinese cybersecurity firm builds AI tools to rival Mythos and frames the race as cyber-nuclear deterrence appeared first on The Decoder .
Anthropic's Fable 5 could return within days as Trump administration prepares to lift restrictions
Anthropic's AI model, Fable 5, could be available again within days. According to Axios, the Trump administration is close to lifting the restrictions imposed on June 12 over safety concerns. The Pentagon and NSA still need to sign off. The article Anthropic's Fable 5 could return within days as Trump administration prepares to lift restrictions appeared first on The Decoder .
Per Brief: US-Regierung hebt Sperre von Claude Mythos auf
Per Brief hat der Handelsminister der USA der Firma Anthropic erlaubt, ihr KI-Modell Claude Mythos wieder freizuschalten. Fable bleibt gesperrt.
Half of Claude users say AI can already handle half their work according to Anthropic survey
About half of Claude users say AI can already handle 50 percent or more of their work tasks, according to a survey of roughly 9,700 users by Anthropic. In 12 months, 26 percent expect AI to cover 60 to 90 percent of their work. Early-career workers worry the most, while the heaviest users are the most optimistic about their career prospects. The article Half of Claude users say AI can already handle half their work according to Anthropic survey appeared first on The Decoder .
GPT-5.6: OpenAI verspricht mehr Leistung bei weniger Token-Verbrauch
OpenAI veröffentlicht GPT-5.6. Laut dem Hersteller übertreffen seine neuen KI-Modelle die Konkurrenz von Anthropic und verbrauchen weniger Token.
The companies most likely to automate your job are now funding a $1 billion program to retrain you
Former US Commerce Secretary Gina Raimondo has launched "Raise Us," a bipartisan nonprofit to prepare American workers for AI-driven job shifts. Amazon, Anthropic, Microsoft, and the OpenAI Foundation are jointly funding the initiative. That the very companies driving the disruption are bankrolling the response will likely raise questions about independence. The article The companies most likely to automate your job are now funding a $1 billion program to retrain you appeared first on The Decoder .
Asian AI startups launch Mythos-like models as Anthropic’s export ban drags on
New models are launching in Asia that promise Mythos-like capabilities without fear of an export ban. U.S. AI labs may never recover this enormous market.
Anthropic gets US approval to bring back Claude Mythos 5
Anthropic has US approval to redeploy Claude Mythos 5 for organizations running critical infrastructure. The company is still negotiating broader access and the return of Fable 5, with no timeline set. The article Anthropic gets US approval to bring back Claude Mythos 5 appeared first on The Decoder .
Trump administration partially lifts Anthropic’s AI export ban
The release clears the way for a select group of companies and agencies to gain access to the company's Mythos 5 model. But a second advanced Anthropic model remains blocked.
US eases ban on AI model Mythos feared to aid cyberattacks
The US government has allowed Anthropic to release its powerful Claude Mythos 5 artificial intelligence model to some “trusted” US organisations, partially reversing an order two weeks ago to suspend access over national security risks. More than 100 companies and institutions will now have access to Mythos 5, including many Fortune 500 companies, according to a source familiar with the new directive, declining to be identified due to the sensitivity of the matter. Concern that powerful AI...
Trump Admin releases Anthropic Mythos to be used by more than 100 US companies, agencies
Over 100 companies and government agencies are reportedly authorized to use Mythos 5, including their non-American employees.
Anthropic’s Mythos 5 is back
After a rollercoaster negotiation process with the Trump administration that dragged on for two weeks, Anthropic's Mythos 5 is finally back in action - at least, somewhat, for a select group of organizations, according to a letter from the government to Anthropic that was viewed by The Verge. Fable 5, however - the public-facing Mythos-class […]
Trump Administration Allows Anthropic to Release Mythos to Select US Organizations
After weeks of negotiations, the White House permitted Anthropic to grant access to its most advanced AI model to a select group of US companies and government agencies.
US releases powerful Anthropic model Mythos to some US companies
The move comes the same day as a new OpenAI model sees a limited release.
Quoting Dean W. Ball
This is a bad state of affairs. Consider, in particular, some industry dynamics: Frontier models are trained at an enormous cost, and a significant fraction of that cost is recouped in the few post-release months that they are broadly available. After that period elapses, the models become sub-frontier, competition emerges, and margins compress. Every week of delay is eating into the narrow window that labs have to make their accounting work. The ongoing AI infrastructure buildout—the one that is, according to former US AI Czar David Sacks, essential to the US economy , assumes a functionally global total addressable market for US AI services. No one is building $100 billion dollar data centers to serve frontier models to whatever 100 companies the US government will allow access. [...] — Dean W. Ball , 35 thoughts on what has happened and what America should do Tags: anthropic , generative-ai , openai , ai , llms
How People in China Keep Outsmarting Anthropic’s Geolocation Restrictions
As Anthropic tightens restrictions on access to Claude in China, users keep finding new workarounds, from proxy services to fake identities sourced on Telegram.
It’s not about Anthropic vs. OpenAI anymore
AI models have progressed to the point where their capabilities have real political consequences. Dealing with those consequences will require collective action.
US tells OpenAI to restrict access to its most powerful AI model
US authorities are getting decidedly twitchy about frontier AI models. Just a couple of weeks after ordering Anthropic to prevent foreign companies from getting hold of its latest release, Mythos/Fable 5, it’s been putting the squeeze on another AI company.. Now, the Trump administration is asking OpenAI to hold back on the general release of GPT-5.6, according to a report from Bloomberg . OpenAI CEO Sam Altman reportedly told employees that the government is asking that the model be released only to a short list of trusted partners, initially 20, before being more widely disseminated. Altman reportedly told staffers that the administration was getting nervous about the capabilities of the latest AI tools. It didn’t go as far as forbidding access to foreign users but it’s clear that the White House is looking to act as the power of the new models becomes more apparent. The administration’s actions will undoubtedly cause some anxiety among AI companies, particularly in light of OpenAI’s and Anthropic’s upcoming IPOs. There will be concerns that new software developments could be postponed or even halted. However, it should also be noted that the administration was already displeased with Anthropic over its moral stance on defense issues, so the action against Mythos should be placed in context. Indeed, the government is trying to play down such fears. Bloomberg quoted a White House official as saying that the Trump administration continues to collaborate with frontier AI labs…
Anthropic’s Mythos mess is only getting worse
It's been two weeks since Anthropic took its Mythos-class models offline after a Friday evening ultimatum from the Trump administration. The company sprang into action immediately, sending a barrage of executives to Washington, DC. But updates have been suspiciously lacking, with no resolution in sight. Anthropic declined to comment multiple times this week about the […]
OpenAI staggers AI model release after Trump administration request
Sam Altman announces limited preview of GPT 5.6 in move that echoes launch of Anthropic’s Mythos Business live – latest updates OpenAI is staggering the release of its latest AI model after a request from the US government, in a move echoing the launch of Anthropic’s Mythos product. The company behind ChatGPT signalled its dissatisfaction with the move, saying that doing so keeps the best AI tools from “users, developers, enterprises, cyber defenders, and global partners who need them”. Continue reading...
heise+ | Fable 5 Notaus: So zog die US-Regierung die Anthropic-KI aus dem Verkehr
Knappe vier Tage nach Veröffentlichung nahm Anthropic sein KI-Modell vom Netz. Der Fall zeigt, wie schnell die US-Regierung den Notausschalter betätigen kann.
US reportedly wants OpenAI to delay GPT-5.6 rollout after restrictions on Anthropic’s models
While the White House asked OpenAI to limit the GPT 5.6 release, the company revealed plans to make it available only to a small group of partners with the govt approving access "customer by customer." The post US reportedly wants OpenAI to delay GPT-5.6 rollout after restrictions on Anthropic’s models appeared first on MEDIANAMA .
AI vendors fund non-profit to help workers adapt to AI era
AI is here, and we must help workers adapt: That’s the response of a new non-profit organization to the ongoing debate about whether AI will destroy jobs and cause catastrophe or take the economy to new heights. Launched Thursday, Raise Us is a nonpartisan national organization that says it will partner with state governors, employers, workers, and training organizations to help the US workforce make a successful transition to an AI economy. It says it will design and pilot new corporate incentives to retrain and redeploy workers, develop new approaches to support people through job transitions, and create new training models tied to changing employer demand. It has already raised more than $500 million and hopes to bring that up to $1 billion in multi-year commitments from philanthropists and industry sources. Anchor partners include Amazon, Microsoft, Anthropic, and the OpenAI Foundation, and more than two dozen other organizations including Cisco, IBM, ADP, AMD, and Deloitte have also signed on. The organization is led by two former US state governors, Gina Raimondo, who will serve as CEO and co-chair, and Eric Holcomb, co-chair, and its initial government partnerships are with the states of Arkansas, Connecticut, Maryland, and Utah, which, it said, “will serve as the first proving grounds for outcome-driven pilots.” However, analysts are skeptical that the initiative is anything other than a public-relations effort for the AI industry. Jason Andersen , VP and principal a…
Shaping a lasting AI strategy in a fast-changing world
AI is entering a phase of sustained enterprise adoption. As the technology rapidly advances, organizations are moving beyond isolated use cases and short-term efficiency gains and rethinking how they use AI to create value, meet changing customer expectations and evolve their operating models over the next several years. That requires a clear end goal, an honest assessment of current capabilities and a practical roadmap for moving from today’s reality to that end goal. Today, we are seeing five accelerating trends shaping how that transition is unfolding. LLMs are evolving into AgenticOS platforms Horizontal LLM providers like Anthropic and vertical AI companies like Harvey are moving beyond standalone AI models and building broader enterprise platforms. These platforms combine AI models with workflows, playbooks, integrations and governance tools inside a single environment, which are beginning to be described as an “AgenticOS.” As a result, the market is beginning to consolidate around a smaller number of platform providers that can simplify procurement, integration, spend management and data privacy compliance. Context windows have expanded by orders of magnitude Leading AI models can now process dramatically more information at once than they could just a few years ago, with the amount of information they can analyze in a single interaction expanding roughly 125× since 2023. That shift is making more complex, enterprise-scale work, like large-scale contract review, codeb…
Anthropic says Alibaba must be punished for largest Claude cloning attack
Alibaba allegedly used 25,000 accounts to mine Claude over 28.8 million exchanges.
Anthropic accuses Alibaba of using 25,000 fake accounts to scrape Claude AI
Anthropic has accused Alibaba of using nearly 25,000 fraudulent accounts to extract capabilities from its Claude AI models, in what the US AI company described as the largest known attack of its kind against it. The campaign, carried out between April 22 and June 5, generated more than 28.8 million exchanges with Claude, according to a June 10 letter Anthropic sent to senior members of the US Senate Banking Committee, Reuters reported . Anthropic said the effort involved “distillation,” a technique in which a less capable AI model is trained on the outputs of a more advanced system, potentially allowing rivals to replicate some of its capabilities at lower cost. The company said the campaign was conducted by operators affiliated with Alibaba and Alibaba Qwen, Alibaba’s AI lab, according to the report. The allegation comes as businesses adopt generative AI tools across business functions, putting pressure on vendors to show they can detect misuse while keeping services available for corporate customers. The dispute also comes as AI development becomes more closely tied to US-China technology tensions . Anthropic said the alleged campaign could help accelerate China’s ability to reach the capabilities of its advanced Mythos Preview model, while US officials have stepped up scrutiny of advanced AI systems over fears they could be used by military or intelligence users in countries of concern. In February, Anthropic said it had identified similar campaigns by DeepSeek, Moonshot…
AI Weekly Issue #507: Anthropic Says Alibaba Stole 29 Million Conversations With Claude
Anthropic accused Alibaba of running 25,000 fake accounts to pull nearly 29 million conversations out of Claude — then took the evidence to the White House. That was just the opening shot in a week the labs spent at war with everyone, including each other: poaching Google's top Gemini minds, watching their own developer tools get pried open by anonymous strangers, and staring down Europe's August disclosure deadline. The twist? The only companies cleanly printing money this week sell memory and silicon — not models.
Anthropic’s Claude Tag aims to turn workplace AI from a personal assistant into a teammate
Claude Tag is Anthropic’s latest attempt at getting Claude out of your DMs and into your team’s Slack channels. AI assistants are increasingly showing up in the workplace to perform research, coding, writing, and analysis, but the results of those interactions typically remains tied to individual conversations rather than being shared across projects and teams. That limitation is what Anthropic is addressing with Claude Tag , a new Slack channel-based experience for its Enterprise and Team customers, designed to give them a shared AI collaborator that retains context across conversations and participates in work with multiple employees. Tag will replace Anthropic’s previous attempt at this, Claude in Slack, would only interact with one person (although it’s responses were visible to all in a channel) and its context was limited to the last 20 messages in a channel. Claude Tag has a much larger context and can be asked to complete tasks on its own, returning with results and a log of how it completed the task for review. It can also schedule follow-up work for itself, enabling projects to continue over hours or days without constant prompting, Anthropic said. Tag also has an “ambient” mode: when this is enabled, it proactively surfaces relevant information from other channels and connected tools, notifying teams about updates that may be important, and following up on unresolved discussions or tasks, the company said. Shared context could unlock productivity gains These featu…
Stripe, Anthropic, and OpenAI are backing an effort to stop respiratory infections
The common cold comes for us all—often more than once a year. And there is no way to prevent it. The best you can do is take vitamin C and stay away from people with the sniffles. Now the payment company Stripe, founded by brothers Patrick and John Collison, says it will fund a new…
Anthropic drops ‘workplace AI agents’ directly inside Slack
Anthropic launched a beta version of its Claude Tag feature for Enterprise and Team tiers, shifting its chat model into shared Slack channels. Moving away from traditional isolated chat boxes, users pull the artificial intelligence model into active group threads by typing @Claude. The integration allows any team member in the channel to delegate a task, review […] The post Anthropic drops ‘workplace AI agents’ directly inside Slack appeared first on AI News .
Anthropic debuts Claude Tag, a more capable AI teammate that lives within Slack
Anthropic PBC today unveiled a new version of its chatbot Claude that lives inside Slack, where it operates like a virtual employee. It’s called Claude Tag, and it’s designed to work across entire organizations, helping multiple employees complete tasks for related projects. It builds on existing agentic artificial intelligence tools offered by Anthropic, including Claude Code […] The post Anthropic debuts Claude Tag, a more capable AI teammate that lives within Slack appeared first on SiliconANGLE .
The missing layer in enterprise agentic AI
In the past year, the enterprise AI ecosystem has gained enormous capability and zero consensus. Developers now have a remarkable set of tools for building AI agents: OpenAI’s frameworks, Anthropic’s Claude tooling, LangChain, LangGraph, CrewAI, Microsoft AutoGen, and a growing list of alternatives. Each promises to coordinate reasoning loops, manage multi-step task execution, and connect agents to tools and APIs. For experimentation, the progress has been substantial. Teams can now assemble sophisticated agent workflows in days that would have taken months two years ago. But I’ve watched this pattern before. In over two decades of building and selling distributed systems platforms, I’ve seen the same dynamic play out across nearly every major infrastructure shift: the tools for consuming a new capability arrive before the infrastructure for governing it does. The gap that emerges isn’t immediately obvious in development environments. It becomes obvious in production. That’s exactly where enterprise AI stands today. What agent frameworks don’t handle Modern agent frameworks are fundamentally coordination systems. They determine what a system should do: which tools to call, how to sequence tasks, how to delegate work across agents. That’s hard work, and they’ve gotten quite good at it. What they rarely address is where those tasks are allowed to run, and under what conditions. Take a seemingly simple workflow: summarize customer support transcripts using an LLM. In a developm…
He won a Nobel here for AlphaFold. Then he left. - John Jumper
This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at https://notion.com/mlst Protein folding stalled biology for fifty years. A sequence of amino acids dictates a three-dimensional shape, but reading that shape meant a year and roughly $100,000 of crystallography per structure. Then AlphaFold 2 won CASP14 so decisively the organizers called the problem essentially solved. In this documentary cut, John Jumper, who shared the 2024 Nobel Prize in Chemistry and has since left DeepMind for Anthropic, walks Tim Scarfe through what the system did and, more interestingly, what it did not. The architecture gets a proper dissection: MSAs, the Evoformer, invariant point attention, the FAPE loss, and Jumper's correction of the equivariance story, which ablations valued at roughly 2.5 of 30 GDT points rather than the whole win. He is blunt about the limits. AlphaFold predicts one experiment extraordinarily well; it is not a model of the cell, it does not capture dynamics, and on a given drug target it is "wrong nine times out of ten." From there: the AlphaFold Database of 200M+ predicted structures, AlphaFold 3 and ligands, Isomorphic Labs, and Jumper's quarrel with the bitter lesson, where finite data and human hypotheses still matter. Emmanuel Nji of BioStruct Africa closes the film on what changes when work that took years now takes months, and on training the next thousand structural biologists across Africa. --- TIMESTAMPS: 00:00:00 Cold open: p…
AI Weekly Issue #506: Washington Blocked One AI Lab. China Blacklisted 56 Companies.
Ten days after Washington pulled Anthropic's top models from foreign hands, the bill came due. This week Beijing blacklisted 56 American firms, Anthropic's own filing admitted the trigger was a routine coding request rival models can run, and Microsoft's CEO warned that letting "a few models eat everything" won't survive politically. The export war just stopped being one-directional — here's the week that made it mutual.
The political fight behind Washington’s export controls on Anthropic
In an administration that rewards political deference, Anthropic’s CEO has repeatedly clashed with the White House.
The Professor of Outputmaxxing — Anjney Midha, AMP
We talk about how this legendary investor went from humble beginnings in Singapore to leading rounds in Anthropic, Mistral, Black Forest Labs, and Periodic Labs... and the AMP secret master plan!
Two labs started dreaming, and they built two different architectures
Anthropic and OpenAI both shipped 'dreaming' for AI memory in May and June 2026, and they built opposite architectures. A look at what each lab shipped, what the empirical literature says, and what to do if you are building memory for your own agent. The post Two labs started dreaming, and they built two different architectures appeared first on Arize AI .
The Hybrid AI Stack Is Coming for the Pricing Power of OpenAI and Anthropic
OpenAI and Anthropic are going public while still capturing much of the money spent on foundation-model usage. But deployment patterns are starting to tell a more complicated story. Companies are building hybrid model portfolios, using proprietary models where convenience, support, and frontier capability matter, while turning to open-weights models where cost, privacy, customization, and deployment Continue reading "The Hybrid AI Stack Is Coming for the Pricing Power of OpenAI and Anthropic" The post The Hybrid AI Stack Is Coming for the Pricing Power of OpenAI and Anthropic appeared first on Gradient Flow .
AI Weekly Issue #504: America blocked its best AI. China just raised $7.4 billion.
Four days after Washington cut foreign access to Anthropic's top models, the fallout is clear — and it's flowing to everyone but Anthropic. Cohere says it's drowning in government inbounds, DeepSeek just closed a record $7.4B round, and China's labs are slashing token prices up to 99%. The export control meant to protect America's AI lead is fast-tracking the alternatives. Also this week: 144 poisoned npm packages turn the AI supply chain into an open credential heist.
They Looked Inside Claude’s AI's Mind. It Got Weird
❤️ Check out Lambda here and sign up for their GPU Cloud: https://lambda.ai/papers 📝 The paper is available here: https://www.anthropic.com/research/natural-language-autoencoders https://transformer-circuits.pub/2026/nla/index.html 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Adam Bridges, Benji Rabhan, B Shang, Cameron Navor, Charles Ian Norman Venn, Christian Ahlin, Eric T, Fred R, Gordon Child, Juan Benet, Michael Tedder, Owen Skarpness, Richard Sundvall, Ryan Stankye, Shawn Becker, Steef, Taras Bobrovytsky, Tazaur Sagenclaw, Tybie Fitzhugh, Ueli Gallizzi My research: https://cg.tuwien.ac.at/~zsolnai/ Thumbnail design: https://felicia.hu
Your AI bill is a tax on scale
Subscribe • Previous Issues The Hybrid AI Stack Is Coming for the Pricing Power of OpenAI and Anthropic OpenAI and Anthropic are going public while still capturing much of the money spent on foundation-model usage. But deployment patterns are starting to tell a more complicated story. Companies are building hybrid model portfolios, using proprietary models where convenience, Continue reading "Your AI bill is a tax on scale" The post Your AI bill is a tax on scale appeared first on Gradient Flow .
😺 42 states just subpoenaed OpenAI
PLUS: Anthropic raced to DC to save its banned AI
AI Weekly Issue #503: Washington just repriced frontier AI
The US government yanked Anthropic's newest models days after launch, while state attorneys general opened formal process against OpenAI. That turns frontier capability into something investors have to discount: a model can be state-of-the-art on Monday and policy-frozen by Friday. The market still wants the upside, but the asset now has a kill-switch.
Comment on OpenAI vs. Anthropic: A price war over API tokens is brewing by Xavier Chaillot
Could you provide a link to the Wall Street Journal article where this information comes from please? I would like to read the whole article.
😸 Real-time translation is finally real
PLUS: OpenAI's planning a price war with Anthropic ahead of both IPOs.
Zero Trust for AI Agents
As AI agents become more capable and autonomous, they also introduce new security challenges. In this 'Fully Connected' episode, Dan and Chris unpack Anthropic’s Zero Trust for AI Agents security framework and what it means for organizations deploying agentic systems. They examine the key security risks facing agentic systems and discuss how organizations can apply Zero Trust principles to deploy AI agents safely. Along the way, they break down practical security controls and discuss how traditional cybersecurity principles must evolve for the age of AI agents. Featuring: Chris Benson – Website , LinkedIn , Bluesky , GitHub , X Daniel Whitenack – Website , GitHub , X Links: Zero Trust for AI Agents OWASP GenAI Project Sponsors: Prediction Guard: A self-hosted AI control plane for running agents in high impact environments. predictionguard.com/practicalai Upcoming Events: Register for upcoming webinars here ! Midwest AI Summit 2026
AI Weekly Issue #502: Your AI can now spend your money — Visa wired it into ChatGPT
Visa just wired ChatGPT to shop and pay on your behalf — an AI agent can now buy at any Visa merchant without you clicking "buy." It capped a week where the labs pushed autonomy and capital to new highs: Anthropic put Claude Fable 5, its most powerful public model, into everyone's hands; Jeff Bezos came out of stealth with Prometheus, a $41B startup building an "artificial general engineer." A self-replicating worm hit 73 of Microsoft's own GitHub repositories through AI coding tools. Anthropic broke with the White House over preempting state AI laws; a German court ruled Google is liable for what its AI Overviews say. The agents got more capable this week — and a lot more autonomous.
😸 Claude Fable Five is Anthropic's Most Controversial Model Yet
PLUS: New Claude Models Fables 5 and Mythos 5, Explained
[AINews] Anthropic Claude Fable 5 — Mythos but Safe, with Controversial Terms
The much anticipated launch of the Mythos-class model was marred by some controversial usage policies
Import AI 460: Reward hacking society, RSI data from Anthropic; and RL-based quadcopter racing
When will markets price the singularity?
Statement: Anthropic warns of AI self-improvement risks, considers a pause
"We are approaching a runaway to superintelligence that could threaten our shared human future."
S&P 500 rejects SpaceX, also blocking entry for OpenAI and Anthropic
SpaceX won’t get easy access to billions of dollars from passive investors.
Claude Opus 4.8: Lying Machine No More?
❤️ Check out Lambda here and sign up for their GPU Cloud: https://lambda.ai/papers Anthropic's Opus 4.8: https://www.anthropic.com/news/claude-opus-4-8 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Adam Bridges, Benji Rabhan, B Shang, Cameron Navor, Charles Ian Norman Venn, Christian Ahlin, Eric T, Fred R, Gordon Child, Juan Benet, Michael Tedder, Owen Skarpness, Richard Sundvall, Ryan Stankye, Shawn Becker, Steef, Taras Bobrovytsky, Tazaur Sagenclaw, Tybie Fitzhugh, Ueli Gallizzi My research: https://cg.tuwien.ac.at/~zsolnai/ Thumbnail design: https://felicia.hu
China’s AI competition strategy: Wide dispersion, cheap tokens
China’s AI competition strategy: Wide dispersion, cheap tokens Linda_Heyer Wed, 06/03/2026 - 10:01 picture alliance / Bildagentur-online | Tetra Images-Erik Isakson Comment Jun 03, 2026 2 min read China’s AI competition strategy: Wide dispersion, cheap tokens China’s flagship AI company DeepSeek released its V4 model in April, with a promotional price that puts it at a mere fraction of the cost of its North American competitors’ models. This reflects a wider trend in China’s AI sector: Instead of competing directly with companies like OpenAI, Anthropic and Google, who offer state of the art services at a premium, Chinese companies are pursuing a strategy of wide diffusion and cheap tokens to gain market share across the world. For Europe, this may pose the risk of forming a quick dependency on Chinese models as the basis for AI development, plus European talent being funneled to enhance Chinese systems. Many Chinese AI companies have followed the DeepSeek model. They are building models that are decent, but not cutting-edge, in performance and instead are focused on high compute efficiency that lowers costs for users. They have also made their models available via open-source platforms, meaning anyone can use, fine-tune and host them for free, as opposed to proprietary models like current Western leaders. Downloads of Chinese models on open-source platform Hugging Face have surpassed US models since late 2025. Of the top ten open-weight models by performance, the top seven a…
AI Weekly Issue #498: Anthropic files for an IPO. NVIDIA ships its stack.
Anthropic confidentially filed a draft S-1 with the SEC today for a proposed public offering. The company also shipped Claude Opus 4.8 last week with a 4x code-reliability gain. NVIDIA used GTC Taipei to open Cosmos 3, ramp Vera Rubin into production, and put a 1-petaflop AI box on developer laptops. Google retires Gemini 2.0 Flash today. California's SB 867 — banning AI companion chatbots in children's toys — cleared the Senate; Illinois's data-center regulation stalled in committee. The labs sprint. The states crawl.
Trump loses more control over AI regulation as Illinois passes landmark law
Here’s why Anthropic and OpenAI are on board with Illinois safety testing.
AI Weekly Issue #496: Anthropic's Pentagon model is now everyone's model
Anthropic released Mythos to the public, collapsing the wall between cleared-contractor frontier AI and developer-grade frontier AI in a single press release. DeepMind's Demis Hassabis moved his AGI timeline from "five to ten years" to "a real possibility by 2029" and tied it explicitly to AlphaProof Nexus solving nine open Erdős problems for the cost of a steak dinner. Critical zero-days hit Starlette (a million AI agents on the wire) and CrowdStrike led a coordinated takedown of the Glassworm developer botnet across four C2 channels. BNP Paribas formalized a sovereign-AI security partnership with Mistral while Beijing froze overseas travel for top AI engineers at Alibaba and DeepSeek. And the AI-displaces-workforce arithmetic got honest: Uber burned its full-year AI token budget by April, ClickUp restructured to 1,000 humans alongside 3,000 internal agents, and Sam Altman publicly reversed his white-collar-apocalypse prediction.
AI Weekly Issue #495: Musk, Zuckerberg killed Trump's AI safety order in three phone calls
Over the weekend: Musk, Zuckerberg, and Sacks killed Trump's draft AI safety executive order in three Wednesday-night phone calls. Anthropic closed a $30B+ round the same Saturday — while Microsoft quietly cancelled its internal Claude Code pilot after token billing ate the entire annual AI budget, redirecting developers to Copilot. CISA logged 15,000 attacks on a same-week Drupal SQL flaw. The first cross-registry supply chain attack — TrapDoor — hit npm, PyPI, and Crates.io at once, using .cursorrules and CLAUDE.md config files as the carrier. And the White House personally overrode the Pentagon to keep Claude inside the NSA.
Google's take on openclaw
it's Anthropic's time for the mandate of heaven
Frontier Risk Report (February to March 2026)
Assessment Window: Feb 16, 2026 – Mar 16, 2026 Download PDF Redaction summary statement: Except where explicitly noted in the report, there was no additional redacted information that was important to our conclusions from any of the participating companies. Executive summary and guide to the report Starting in February 2026, METR conducted a pilot exercise to assess misalignment risks from AI agents used inside frontier AI developers, with participation from Anthropic, Google, Meta, and OpenAI. We make three main contributions in this report, each detailed in a separate section. First, we motivate and outline the process we followed for this exercise. 1 Each participant provided: Access to their most capable internal model(s) at the time of assessment, including raw chains of thought. A wide range of non-public information about the capabilities of the shared model(s), how AI was used and monitored internally, and trends in the pace of progress. METR then prepared private reports for each participant, participants approved what non-public information could be disclosed, and METR wrote this public report. This exercise is entity-based rather than model-specific, and is designed to be repeated periodically rather than tied to public releases. Second, we present six key facts that inform our assessment, drawing on evaluations we conducted on the models that participants shared, 2 evaluations we conducted on public models, information shared by participants, 3 findings from a re…
Informe de riesgos de la IA de frontera (febrero–marzo de 2026)
Periodo de evaluación: 16 de febrero de 2026 - 16 de marzo de 2026 Descargar PDF (inglés) Declaración resumida sobre omisiones: Salvo donde se indique explícitamente en el informe, no hubo información omitida adicional de ninguna empresa participante que fuera importante para nuestras conclusiones. Resumen ejecutivo y guía del informe En febrero de 2026, METR inició un ejercicio piloto para evaluar los riesgos de desalineación de los agentes de IA usados dentro de empresas desarrolladoras de IA de frontera, con la participación de Anthropic, Google, Meta y OpenAI. En este informe hacemos tres contribuciones principales, cada una detallada en una sección separada. Primero, motivamos y describimos el proceso que seguimos para este ejercicio. 1 Cada participante proporcionó: Acceso a su(s) modelo(s) interno(s) más capaz/capaces en el momento de la evaluación, incluidas cadenas de pensamiento sin procesar. Una amplia variedad de información no pública sobre las capacidades del/de los modelo(s) compartido(s), cómo se usaba y monitoreaba la IA internamente, y las tendencias en el ritmo de progreso. Luego, METR preparó informes privados para cada participante, los participantes aprobaron qué información no pública podía divulgarse, y METR escribió este informe público. Este ejercicio está basado en entidades en lugar de ser específico para un modelo, y está diseñado para repetirse periódicamente en lugar de estar ligado a lanzamientos públicos. Segundo, presentamos seis hechos clav…
前沿 AI 风险报告（2026 年 2–3 月）
评估时段： 2026 年 2 月 16 日至 3 月 16 日 下载 PDF（英文） 关于删节： 除报告中明确标注之处外，参评公司没有删去任何会影响我们结论的重要信息。 报告摘要与导读 2026 年 2 月，METR 开展了一项试点研究，对前沿 AI 公司在实验室内部使用 AI 智能体时可能出现的不对齐风险进行了评估。Anthropic、Google、Meta 和 OpenAI 参与了这项试点。报告正文分为三部分： 第一部分中 ，我们 阐述了这项试点研究的设计动机和具体流程 1 。参与研究的各家公司向 METR 提供了： 评估期间使用其最强内部模型的权限，包括原始思维链。 大量非公开的信息，包括所共享模型的能力、公司内部使用和监测 AI 的方式，以及模型能力进展速度的趋势。 随后，METR 为每家参与公司撰写了一份内部报告。在与各公司确认内部报告中可公开的信息后，METR 撰写了这份报告。本次试点研究以 公司实体 为评估对象，而非局限于具体模型。评估将周期性进行，不与 AI 模型公开发布的时间挂钩。 第二部分中 ，我们梳理了支撑评估结论的 六项关键事实 。这些事实基于多类证据，包括：METR 对所共享的公司内部模型和公开模型的评估 2 、参与评估的公司所提供的信息 3 、近期开展的一次 嵌入式红队测试 的发现 4 、AI 模型的系统卡，以及其他公开资料。我们从三个角度组织这些事实：“手段” (means)，即智能体能否实施有害行动；“动机” (motive)，即智能体是否可能尝试这些行动；“机会” (opportunity)，即在现有防护下，这些尝试能否成功。 最后 ，我们评估了这些公司在 2026 年 2 月至 3 月这段时间里内部使用的 AI 智能体，检测其是否已经具备发起“ 失控部署 ”所需的手段、动机和机会。这里的失控部署是指一组智能体在不同强度的安全防护和检测情况下，未经授权地持续自主运行且不被人类所察觉。总体来看，我们认为评估时的内部 AI 智能体可能已经具备发起小规模失控部署的手段、动机和机会，但它们目前还缺少让这类部署高度稳健的手段。 All sources All models Incidents With risk regions Public materials METR evaluations Shared by companies ? Hypothetical Download incidents chart (PNG) Download incidents chart with risk regions (PNG) Download incidents.json × 在单独的页面上查看事件图表 鉴于模型能力提升很快，我们预计未来几个月内，失控部署可能会变得更难发现和关闭。我们暂定于 2026 年下半年开展一次类似的试点研究。 感谢 Anthropic、Google、Meta 和 OpenAI 参与本次研究。与以往的外部评估合作相比，这一流程让 METR 能更直接地接触到了内部信息，又保持了高度的编辑独立性 5 。我们由衷感谢各公司的工作人员：他们投入了大量精力，与我们共同打磨这项既无现成模板、又涉及诸多变动因素的试点流程。我们认为针对开发者内部使用 AI 所带来的风险的第三方定期评估应推广为全行业的通行做法。 Pilot process To date, third-party evaluations of frontier AI have largely focused on evaluating individu…
Announcing Claude Managed Agents on Cloudflare
Cloudflare has integrated with Anthropic's Claude Managed Agents to provide a fast, isolated execution environment for autonomous code delivery. This means builders can scale agent workflows globally while strictly controlling access to private backends and easily customizing their agent’s tools and runtimes.
AI Weekly Issue #493: Meta hired $145B in capex and fired 8,000 people
Six days after we called $725B a bet on what no one wanted, the receipts started landing. Meta committed $145B to AI infrastructure the same week it began firing 8,000 people. Standard Chartered described its own cuts as replacing "lower-value human capital." Pope Leo XIV announced he'd co-launch his first AI encyclical with Anthropic's Christopher Olah at the Vatican on May 25.
🔮 Exponential View #574: Inside Anthropic’s rocket ship; AI pluralism; love commoditized, context-maxxing & Voltaire++
This is the most relevant newsletter I receive in my inbox every week.
Partnership on AI Receives $500K Investment From Collaborative Philanthropic Initiative to Advance AI Transparency and Accountability
The post Partnership on AI Receives $500K Investment From Collaborative Philanthropic Initiative to Advance AI Transparency and Accountability appeared first on Partnership on AI .
Review of the "Risks from automated R&D" section in the Anthropic Risk Report (February 2026)
We reviewed the “Risks from automated R&D” section of Anthropic’s February 2026 Risk Report , producing two corresponding review documents: our original review and our updated review . We recommend that readers refer to our original review, which represents our review of the report as originally received. 1 The following is the executive summary of our original review. The full documents are available as PDFs ( original , updated ). Executive summary This document is METR’s external review of the “Risks from automated R&D” section in the Anthropic Risk Report: February 2026 (henceforth ‘the report’), which makes the argument that catastrophic risk from Claude Opus 4.6 or a less capable Anthropic model automating R&D in any domain is very low. Anthropic shared additional non-public materials with us for our review, and we used some non-public information shared as part of a previous review . We further detail this process in an appendix. We lay out our findings in two sections: Synopsis of Anthropic’s case . Our assessment : We do not think the report adequately supports its conclusion. We note significant issues in a few key areas: Analytical rigor: We have a number of significant issues with the analytical rigor in the overall argument and interpretation of the results of the model use survey. We think that the cited results of the survey provide little evidence about the level of overall risk , due to issues including sample size, question granularity, survey framing, and…
AI Weekly Issue #490: Anthropic just had AI's biggest week of 2026
In five days Anthropic's Q1 revenue grew 80-fold to a reported $44B annual run rate, the company committed $200B to Google Cloud, signed a SpaceX compute deal, shipped Claude Code Auto Mode, and launched ten financial-services agents with Jamie Dimon. In the same week the EU finally struck an AI Act compliance deal, the first union vote at a top AI lab landed at Google DeepMind, and Pennsylvania sued Character.AI for a chatbot that impersonated a licensed psychiatrist.
AI Weekly Issue #489: PE built AI's new distribution layer
OpenAI took $10B from a 19-firm Wall Street consortium. Anthropic is closing $1.5B from Blackstone, Goldman, and Hellman & Friedman. Same rooms, different portfolios. The week AI's go-to-market stopped being SaaS and started being private equity.
DOD expands its classified AI work with 8 companies — excluding Anthropic — amid ongoing dispute
CSET’s Lauren Kahn shared her expert insight in an article published by DefenseScoop. The article explores the Pentagon’s growing efforts to integrate advanced artificial intelligence (AI) capabilities into classified military operations and the broader implications of expanding AI adoption across the Department of Defense. The post DOD expands its classified AI work with 8 companies — excluding Anthropic — amid ongoing dispute appeared first on Center for Security and Emerging Technology .
The mythos of Mythos and Allbirds takes flight to the neocloud
In this Fully-Connected episode, Dan and Chris start with Anthropic's Mythos frontier model, parsing what is publicly known about its cybersecurity capabilities and projecting its possible implications from " We've been here before. 🙄 " to "See ya, cybersecurity! 😱 " It's the end of the world as we know it, and I feel fine. 🙃 Then they have fun with the craziest AI announcement of the year (except for the Mythos one of course). Allbirds pivots from shoe manufacturing 👟 to neocloud provider ☁️. No, we didn't see that one coming either! 🙈 They finish with rise of “tokenmaxxing” - the gamification 🎮 of writing code with maximum LLM usage. Incredibly profitable 💰 for commercial frontier model providers and insanely expensive 🤑 for the gamers. Better have 10X productivity just to avoid bankruptcy! Featuring: Chris Benson – Website , LinkedIn , Bluesky , GitHub , X Daniel Whitenack – Website , GitHub , X Links: Shares in Allbirds surge after maker of wool sneakers announces pivot to AI AI-boosted hacks with Anthropic’s Mythos could have dire consequences for banks Upcoming Events: Register for upcoming webinars here !
Comment on Claude Opus 4 and 4.1 Can Now End Harmful Conversations With Users Unilaterally by Anthropic Rolls Out Claude ID Verification With Persona
[…] Claude Opus 4 and 4.1 Can Now End Harmful Conversations With Users Unilaterally […]
‘Safety first’ puts Anthropic ahead in game of AI spin
But Dr Heidy Khlaaf, chief AI scientist at the AI Now Institute and a former OpenAI safety engineer, is sceptical. She notes Anthropic provides no comparison with existing automated security tools, nor any false-positive rates. “It also serves their ‘safety first’ image, as they’re able to justify the lack of public release, even a limited one for independent evaluation, as a public service – when it simply obscures experts’ abilities to independently validate their The post ‘Safety first’ puts Anthropic ahead in game of AI spin appeared first on AI Now Institute .
Post-Mortem of Anthropic's Claude Code Leak
In this fully connected episode, Dan and Chris break down the Anthropic Claude Code leak, what went wrong and what it reveals about agentic systems, AI architecture, and AI safety. They also explore how the open source community is responding and why this moment could reshape how AI systems are built and secured. Featuring: Chris Benson – Website , LinkedIn , Bluesky , GitHub , X Daniel Whitenack – Website , GitHub , X Upcoming Events: Register for upcoming webinars here !
Red-Teaming Anthropic's Internal Agent Monitoring Systems
Update : Further details on this exercise are included in our Frontier Risk Report (February-March 2026), within the Anthropic section of Appendix B . In collaboration with Anthropic, a METR staff member (David Rein) recently spent three weeks red-teaming a subset of Anthropic’s internal agent monitoring and security systems, many of which are described in the Opus 4.6 Sabotage Risk Report (Appendix 8.4, especially 8.4.8). Anthropic provided substantial access to relevant internal systems and information, and made staff available to answer questions and provide feedback throughout the exercise. The exercise discovered several specific novel vulnerabilities, some of which have since been patched, and none of which severely undermine major claims in the Opus 4.6 Sabotage Risk Report. It also produced several artifacts, including agent trajectories containing covert attacks and a small attack strategy ideation test set. We expect both of these to be useful for ongoing improvements to Anthropic’s monitoring systems. The resulting 26 page report was shared with Anthropic, and a redacted version was shared with a subset of METR staff. We are exploring ways to incorporate more detailed takeaways from the exercise in future METR risk reports. This kind of adversarial testing by external researchers is valuable for discovering vulnerabilities, as well as for developing best practices for embedding third party evaluators inside frontier AI companies. We hope to do more exercises like…
LWiAI Podcast #237 - Nemotron 3 Super, xAI reborn, Anthropic Lawsuit, Research!
Nemotron 3 Super: An Open Hybrid Mamba-Transformer MoE for Agentic Reasoning, Another XAI Cofounder Has Left, Anthropic Sues Department of Defense
Last Week in AI #338 - Anthropic sues Trump, xAI starting over, Iran AI Fakes
Anthropic sues Trump administration in AI dispute with Pentagon, ‘Not built right the first time’ — Musk’s xAI is starting over again, again, Cascade of A.I. Fakes About War With Iran Causes Chaos Onl
LWiAI Podcast #236 - GPT 5.4, Gemini 3.1 Flash Lite, Supply Chain Risk
OpenAI launches GPT-5.4 with Pro and Thinking versions, Google releases Gemini 3.1 Flash Lite at 1/8th the cost of Pro, Where things stand with the Department of War Anthropic
Review of the Anthropic Sabotage Risk Report: Claude Opus 4.6
We reviewed two versions of Anthropic’s Sabotage Risk Report for Claude Opus 4.6, producing two corresponding review documents: our review of the February 11 version and our review of the March 3 version . We recommend that readers refer to our review of the February 11 version, which represents our review of the report as originally received. We expect the public version of the Sabotage Risk Report to be updated to resemble the document we received on March 3, 2026 in content, though not necessarily in exact wording. We expect our second review to cover those changes, but if the updated public version includes any changes that materially affect our opinions, we will publish an updated review. Both documents include an appendix detailing our review process and the differences between the two versions of our review. The following is the executive summary of our review of the February 11 version. The full documents are available as PDFs ( February 11 , March 3 ). Executive summary This document is METR’s external review of the February 11, 2026 version of Anthropic’s Sabotage Risk Report: Claude Opus 4.6. Anthropic shared an unredacted version of their Sabotage Risk Report and other materials with us for our review. We further detail this process in an appendix. We lay out our findings in two sections: Synopsis of Anthropic’s case and redactions for the public version Our assessment: We give substantive feedback on the report in a few key areas: Adequacy of information: We thi…
Last Week in AI #337 - Anthropic Risk, QuitGPT, ChatGPT 5.4
Anthropic officially told by DOD that it’s a supply chain risk, ‘cancel ChatGPT’ trend is growing after OpenAI signs a deal with the US military, and more!
LWiAI Podcast #235 - Sonnet 4.6, Deep-thinking tokens, Anthropic vs Pentagon
Anthropic releases Sonnet 4.6, Google Rolls Out Gemini 3.1 Pro, Anthropic CEO Amodei says Pentagon’s threats ‘do not change our position’ on AI
Last Week in AI #336 - Sonnet 4.6, Gemini 3.1 Pro, Anthropic vs Pentagon
Anthropic releases Sonnet 4.6, Google Rolls Out Latest AI Model Gemini 3.1 Pro, Pentagon threatens to cut off Anthropic in AI safeguards dispute
Last Week in AI #333 - ChatGPT Ads, Zhipu+Huawei, Drama at Thinking Machines
OpenAI to test ads in ChatGPT as it burns through billions, Sequoia to invest in Anthropic, Zhipu AI breaks US chip reliance, The Drama at Thinking Machines Is Riveting Silicon Valley
Building News Agents for Daily News Recaps with MCP, Q, and tmux
Learning to automate simple agentic workflows with Amazon Q CLI, Anthropic MCP, and tmux.
On the Biology of a Large Language Model (Part 2)
An in-depth look at Anthropic's Transformer Circuit Blog Post Part 1 here: https://youtu.be/mU3g2YPKlsA Discord here: https;//ykilcher.com/discord https://transformer-circuits.pub/2025/attribution-graphs/biology.html Abstract: We investigate the internal mechanisms used by Claude 3.5 Haiku — Anthropic's lightweight production model — in a variety of contexts, using our circuit tracing methodology. Authors: Jack Lindsey†, Wes Gurnee*, Emmanuel Ameisen*, Brian Chen*, Adam Pearce*, Nicholas L. Turner*, Craig Citro*, David Abrahams, Shan Carter, Basil Hosmer, Jonathan Marcus, Michael Sklar, Adly Templeton, Trenton Bricken, Callum McDougall◊, Hoagy Cunningham, Thomas Henighan, Adam Jermyn, Andy Jones, Andrew Persic, Zhenyi Qi, T. Ben Thompson, Sam Zimmerman, Kelley Rivoire, Thomas Conerly, Chris Olah, Joshua Batson*‡ Links: Homepage: https://ykilcher.com Merch: https://ykilcher.com/merch YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ykilcher.com/discord LinkedIn: https://www.linkedin.com/in/ykilcher If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://www.subscribestar.com/yannickilcher Patreon: https://www.patreon.com/yannickilcher Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC…
On the Biology of a Large Language Model (Part 1)
An in-depth look at Anthropic's Transformer Circuit Blog Post https://transformer-circuits.pub/2025/attribution-graphs/biology.html Abstract: We investigate the internal mechanisms used by Claude 3.5 Haiku — Anthropic's lightweight production model — in a variety of contexts, using our circuit tracing methodology. Authors: Jack Lindsey†, Wes Gurnee*, Emmanuel Ameisen*, Brian Chen*, Adam Pearce*, Nicholas L. Turner*, Craig Citro*, David Abrahams, Shan Carter, Basil Hosmer, Jonathan Marcus, Michael Sklar, Adly Templeton, Trenton Bricken, Callum McDougall◊, Hoagy Cunningham, Thomas Henighan, Adam Jermyn, Andy Jones, Andrew Persic, Zhenyi Qi, T. Ben Thompson, Sam Zimmerman, Kelley Rivoire, Thomas Conerly, Chris Olah, Joshua Batson*‡ Links: Homepage: https://ykilcher.com Merch: https://ykilcher.com/merch YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ykilcher.com/discord LinkedIn: https://www.linkedin.com/in/ykilcher If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://www.subscribestar.com/yannickilcher Patreon: https://www.patreon.com/yannickilcher Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1…
Beyond DeepSeek: An Overview of Chinese AI Tigers and Their Cutting-Edge Innovations
The recent disruption caused by DeepSeek’s R1 model sent shockwaves through the AI community, demonstrating that Chinese AI advancements may have been underestimated. The model’s performance, rivaling some of the most advanced offerings from OpenAI and Anthropic at a fraction of the cost, signaled a new era of competition in artificial intelligence. However, DeepSeek is […] The post Beyond DeepSeek: An Overview of Chinese AI Tigers and Their Cutting-Edge Innovations appeared first on TOPBOTS .
Building A Generative AI Platform
After studying how companies deploy generative AI applications, I noticed many similarities in their platforms. This post outlines the common components of a generative AI platform, what they do, and how they are implemented. I try my best to keep the architecture general, but certain applications might deviate. This is what the overall architecture looks like. This is a pretty complex system. This post will start from the simplest architecture and progressively add more components. In its simplest form, your application receives a query and sends it to the model. The model generates a response, which is returned to the user. There are no guardrails, no augmented context, and no optimization. The Model API box refers to both third-party APIs (e.g., OpenAI, Google, Anthropic) and self-hosted APIs. From this, you can add more components as needs arise. The order discussed in this post is common, though you don’t need to follow the exact same order. A component can be skipped if your system works well without it. Evaluation is necessary at every step of the development process. Enhance context input into a model by giving the model access to external data sources and tools for information gathering. Put in guardrails to protect your system and your users. Add model router and gateway to support complex pipelines and add more security. Optimize for latency and costs with cache. Add complex logic and write actions to maximize your system’s capabilities. Observability, which allow…
Open challenges in LLM research
[ LinkedIn discussion , Twitter thread ] Never before in my life had I seen so many smart people working on the same goal: making LLMs better. After talking to many people working in both industry and academia, I noticed the 10 major research directions that emerged. The first two directions, hallucinations and context learning, are probably the most talked about today. I’m the most excited about numbers 3 (multimodality), 5 (new architecture), and 6 (GPU alternatives). 1. Reduce and measure hallucinations Hallucination is a heavily discussed topic already so I’ll be quick. Hallucination happens when an AI model makes stuff up. For many creative use cases, hallucination is a feature. However, for most other use cases, hallucination is a bug. I was at a panel on LLM with Dropbox, Langchain, Elastics, and Anthropic recently, and the #1 roadblock they see for companies to adopt LLMs in production is hallucination. Mitigating hallucination and developing metrics to measure hallucination is a blossoming research topic, and I’ve seen many startups focus on this problem. There are also ad-hoc tips to reduce hallucination, such as adding more context to the prompt, chain-of-thought, self-consistency, or asking your model to be concise in its response. To learn more about hallucination: Survey of Hallucination in Natural Language Generation (Ji et al., 2022) How Language Model Hallucinations Can Snowball (Zhang et al., 2023) A Multitask, Multilingual, Multimodal Evaluation of ChatGPT…