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OpenAI and Anthropic keep warning about a future they're building
Both Anthropic and OpenAI have released papers warning that frontier models are being deployed before government regulation can catch up.
Anthropic says 'we made the wrong tradeoff' in new model guardrails
"We're changing Fable 5's safeguards for frontier LLM development to make them visible," an Anthropic spokesperson said.
Anthropic's Amodei advocates for AI-related job displacement plan
Anthropic CEO Dario Amodei warns AI could cause long-term job loss, urging policies like universal basic income to mitigate its impact.
Researchers are furious over Anthropic's hidden AI limits
Anthropic faces backlash as Mythos-based models intentionally limit help for AI research, raising transparency and ethical concerns.
Microsoft AI head calls out Anthropic for acting like Claude is conscious
“This is exactly what we don’t want from AIs.”
Perplexity stays course on 2028 IPO amid OpenAI, Anthropic IPOs
Investors are closely watching whether OpenAI and Anthropic can justify their lofty valuations.
New Oregon State building will support five field sports
Oregon State University supporters have made philanthropic commitments totaling $25 million to construct a new facility that will support 150 student-athletes in softball, men’s and women’s soccer, women’s cross country an
We can create the future of science right now
Paul Litvak is the founder and Executive Director of the Robyn Dawes Institute and a Visiting Scholar at UC Berkeley. He has a PhD in Behavioral Decision Research from Carnegie Mellon where he studied emotions and the sunk cost bias. Over 15 years in industry, he solved a wide range of challenging technical problems. At Meta he created models optimizing the ad review process. At Google he ran experiments to measure social influence. At Airbnb, he was a product manager leading machine learning teams optimizing search ranking and price suggestions. He also co-founded and led product at Rhythmic Health, a venture-backed biosensing startup, creating an accurate low cost system using a color changing strip and a smart phone to measure salivary lactate. The bottleneck At this point, it is uncontroversial to say that science needs to stop using the PDF article as the unit of knowledge and currency. The unbearable slowness of scientific publishing, the profit motive and margins: I’m not saying anything new. The PDF also sucks because it’s hard to extract structured information, which makes it hard to do evidence synthesis. As a result, we do much less evidence synthesis than is needed. And evidence synthesis ultimately undergirds most policy and medical decision-making. I can see second-by-second real-time odds for any sporting or newsworthy event, but a school board can’t see the best evidence on whether their 8th graders should be taught algebra. As a society, we don’t treat this as an important problem. Again, not controversial. Not only is the problem well understood, but the solution has already been laid out. What we need is AI-assisted living evidence synthesis - (1) an open knowledge graph of atomic claims, (2) claims linked to evidence, (3) assessment and synthesis of each piece of evidence, and (4) continuous updating with new data. What few realize (yet) is that the technical capacity to build this vision for a significant portion of science already exists. Not only that, scientists and startup teams are already building many of these components. I know this because I’ve been surveying the space and talking to many of the builders. There are some missing pieces: for example, evaluations of how well some of the components work. But at this point, most of what’s missing is a fully end-to-end working integration of all of these parts. In the rest of this essay, I’m going to lay out all the parts of a working living evidence layer for science and who is working on them, and propose concrete next steps for building this system. What’s now possible The diagram above outlines the components of a living evidence synthesis platform, including some of the teams working on each component1. Scientific PDFs are processed into claims with associated evidence. The evidence is subjected to a forensic audit, methodological evaluation and robustness and reproducibility checks. Finally it’s given a weight in a continuously updating synthesis. What follows is a description and status of each component and a few of the teams working on them. Document understanding The first thing you need to be able to do is turn an article into structured data. Mostly that means parsing PDFs. There are often multicolumn layouts that confuse non-specialized PDF to text processing libraries. For scientific papers, there is the added complexity of parsing formulas and tables and figures. This is a really hot area - there are startups offering APIs, and it seems like a new open source package gets posted to Github every few weeks. What follows isn’t exhaustive. A package called GROBID was the state of the art for a while, they didn’t update their package for nearly two years until very recently. In the meantime reducto.ai released an AI powered PDF extraction API, PaddleOCR became popular, IBM released a model called Docling, and both Mistral and Gemini created models and libraries. I also know of at least one other well-funded psychology research group working on a paper parser. By contrast, there are few open evals in this space, with no extensive evals for complex table comprehension in particular. Nonetheless, I’m confident this will be a solved problem soon, given the combination of LLM advances and developer interest. Hypothesis level extraction There has been increasing interest in comprehending the extracted text of papers and linking information to evidence for each hypothesis. A lot of work has already been done. Trialstreamer (Marshall et al. 2020) and RobotReviewer LIVE (Marshall et al. 2023) demonstrated automated extraction of trial population, intervention, and outcome at scale on clinical RCTs. PaperQA2 (Skarlinski et al. 2024) and Ai2 ScholarQA (2024) extended this to retrieval-augmented question answering with citation grounding. Elicit, Consensus, and SciSpace operationalized claim-level extraction for end users. OpenEval (Booeshaghi et al. 2026) is the most recent and most ambitious: 1.96 million atomic claims extracted from 16,087 eLife manuscripts using Claude Sonnet 4.5, grouped into ~299,000 results, with LLM evaluations showing 81% agreement with human peer review on a 2,487-paper subset. None of these solutions link claims to test-statistics, as you would need to evaluate randomized controlled trials. This is why I built the evidence.guide API - to extract hypotheses and associated test statistics from behavioral science papers. The best public eval of this kind of extraction I’m aware of comes from the recent SCORE project - they had humans code thousands of psychology papers to extract their claims by hand. It would be extremely helpful to the world if all scientific PDFs were available as structured open data. I’ve been working to make this happen, both directly at Berkeley and through coordination with large entities I can’t yet speak of; as hard as it is to do, I think it’s possible2. Forensic audit A lot of work has been done on forensic audit, but some gaps remain. Of course, for biology papers that rely on images for evidence, there are a variety of tools (notably Proofig and ImageTwin) to spot anomalies. These are still well short of what sleuths like Elizabeth Bik can do on her own, but these tools are constant companions among fraud analysts. There’s someone working on auditing Excel files for anomalies, and a number of teams are automating numerical checks like GRIM and SPRITE, including Scrutiny project, the INSPECT-SR team as well as statcheck. The regcheck team is building a way to use AI to compare preregistrations to analyses in papers, to ensure there aren’t significant deviations. Nonetheless, there are many other kinds of anomalies to screen for, both public and less publicly known. And there are no formal evals for anomaly detection that I’m aware of. Still, there’s a lot to draw from in this space and I’m pretty certain we will be able to scan papers for most kinds of obvious anomalies in the near future. Methodological review This area has been white hot, though I fear for many of the startups in this space, because this capability may become commoditized. There are at least six different AI peer review companies, including Refine.ink, Reviewer3, ReviewerZero.ai, Q.E.D. Science, Paper Wizard, and Isitcredible. Coarse (a pun on refine) was also recently created as an open source alternative. These systems provide qualitative feedback on the content of papers, spotting methodological weaknesses and mathematical errors. They seem to work pretty well, and many academics report bitterly that they exceed the average quality of typical peer reviewers. But there are few evals here either. What evals exist so far involve using LLM-as-judge (circularity problems abound) or comparing against human reviews of questionable quality. What you’d ideally want is an eval that measures capturing known errors in papers3. Reproducibility and robustness Another active area has been using AI agents to automate computational reproducibility4 and robustness5 checks in papers that report numerical results. For more recent papers where data and code are available, AI agents can see whether they can re-run the analyses and produce the numbers reported in the published paper. In addition to a handful of individual academics who have been experimenting using Claude Code for this, the Institute for Replication is a leading group working on building an end to end system. The evals related to this problem are the most mature, with CORE-Bench (Siegel, Kapoor, Narayanan 2024) and PaperBench (OpenAI 2025) available to benchmark agents on this task. There is also work on getting AI agents to test alternative ways of analyzing the data to ensure the results are robust to small analytic design choices. Synthesis This is the most underdeveloped area where significant investment is required. Although some automated evidence synthesis systems exist — for example, otto-sr is building an AI agent to write systematic reviews — none of these incorporate the full range of paper level signals to weight evidence appropriately. Nor is there anything like an eval or a gold standard for a good systematic review. Arguably Cochrane reviews are the closest we have to gold standard human systematic reviews, though I’ve heard academics in the know complain about their uneven quality. A key question for a synthesis platform is how to weight anomalies and methodological issues in assessing the quality of a piece of evidence. This is an unsolved problem and one I’m very keen to work on. Continuous updating There are many pieces of basic infrastructure available for monitoring for new research and initiating updates. OpenAlex is the current open citation graph. Retraction Watch integrated into Crossref in October 2023. Scite tracks how citations support, contrast, or mention prior claims. The Living Evidence Network demonstrated continuous-update workflows in clinical guidelines. Engineering this is a relatively straightforward task. When you look over this technical architecture and all the progress being made, it’s hard not to be optimistic that a living guide to scientific evidence will be built. The stakeholders are ready The social infrastructure for this is starting to coalesce — it’s not just a pie in the sky academic exercise to imagine this coming into existence. Institutions like the Center for Open Science, the Institute for Replication, the INSPECT-SR, the Living Evidence Network and more are all working on scaling work to improve research quality. Funders are also aligned. The Sloan Foundation has funded living evidence work through COS. Coefficient Giving supports the Institute for Replication and COS. The Astera Institute and the Institute for Progress have shown interest in this space. NIH has established an Office for Replication and Reproducibility. Although there are (very unfortunately) serious headwinds in science funding generally, there is an active group of funders interested in metascience. A brief word about what I’ve been doing at RDI. First, as a Visiting Scholar at Berkeley I’ve been actively figuring out how a non-profit and a public university can conduct and make public the results of large-scale academic article data mining. With some of the money I raised from donors, I commissioned a legal analysis of recent case law and publisher text data mining (TDM) agreements in order to understand whether a massive open data mining of academic articles is possible (with caveats, it is). I’ve also been working to bring together stakeholders in this space, and identify gaps. I’ve also been doing some software development in this space, with more to come. A pilot proposal The assumption undergirding all of this is that an AI, given all this information, would make the right judgment about a scientific claim with lots of conflicting evidence, weighing all the factors appropriately. That’s the hypothesis we need to test. Randomized control trial research is the best place to focus on first. RCTs are used to make many of the important decisions in society - from medical trials to public policy changes. And they use a relatively uniform set of inferential statistics with lots of known and available diagnostics. Behavioral science experiments, within the broader realm of RCTs, should be first used as a testbed whose results can be generalized. Because behavioral science is at the vanguard of open science practices, replications abound (there are thousands of them) to serve as ground truth training data. Key Hypothesis Therefore the pilot would test, in behavioral RCTs that have been replicated, whether the quality of evidence for a claim can be used to accurately predict whether that claim will replicate. Secondary Hypotheses Compared to claims that replicated, non-replicated claims demonstrate a greater share of forensic anomalies in their source literatures. Hypothesis level claim and statistic extraction is accurate enough to scale living evidence without onerous human review costs. Replication prediction is more accurate than prediction markets6 or journal prestige. If all the different quality signals we gather do accurately predict which studies will replicate, then we can use that model to score evidence to power the living evidence layer. Why this is informative regardless of outcome If the pilot succeeds, the architecture extends to medical RCTs (where Living Evidence already operates and integration is mostly about claim representation), then to slices of basic biology with stable replication structure. If it fails, the field learns which quality signals are load-bearing and which ones metascience has oversold. Either result is a contribution to knowing what the literature supports. Implications for funders Because this burgeoning ecosystem of builders already exists, a well-informed philanthropic or government funder could play a crucial catalyzing role in bringing this future about. They could play at least three roles: creating open structured datasets, publishing open benchmarks and incentivizing the solving of key technical challenges. First, open archives of papers that the government maintains, like PubMed, could be turned into structured data amenable to large scale metascience and claim aggregation. I know the US government already has an interest in doing this, though some key open questions remain unanswered. How do you determine the best models and systems for accurately extracting information from papers? How can you establish a robust way to allow researchers to flag errors and correct them? And finally, how do you create a legal regime in working with publishers to maximize the scope of available papers? For the latter, a university or a private philanthropy may be better positioned to make structured data publicly available under journal subscription terms or fair use. Philanthropists or government funders could also coordinate to create or commission benchmarks that evaluate whether important problems have been solved. For example, an open benchmark for claim extraction from a range of different scientific article types would be extremely helpful. Ensuring the underlying data are accurate is vital for creating these evaluations. I’ve discussed opportunistically using various human-created datasets for this purpose, but a consistent problem is that errors in human data make it difficult for them to serve as a gold standard. Finally, with structured data and benchmarks available, the government or private philanthropy could use them to incentivize groups to develop machine learning systems that meet these benchmarks. Prizes are one potentially valuable tool for this. For example, you could establish a prize for a system that accurately updates a living meta-analysis for a small set of claims. Prizes are particularly useful as signals of problem importance, and can help create vibrant ecosystems of public and private research—see, for example the role the government played in kickstarting the current work on nuclear fusion. Conclusion The drawbacks of the current scientific publishing system are known. Scientists agree, metascientists agree, philanthropists agree: the published PDF plus citation graph isn’t the right substrate for maintaining a representation of the evidence base in science. The pieces needed to build the alternative either already exist or are rapidly taking shape. The community is forming around exactly this problem, with concrete partnerships and shared infrastructure. A pilot should start on behavioral science RCTs because that’s the slice of empirical science most amenable to legibility, where replication ground truth is richest, and where the failure modes are best documented. What’s been missing is the galvanizing mission to assemble these pieces into something that works. That’s what I’m proposing to build. *** 1 I have a broader field map that I’ll release publicly soon. This is me, building in public! 2 If this is something that you are excited about, please reach out and talk to me. 3 More on this very soon too! 4 This tests whether, given the code and the data, you can get the same statistics as reported in the published paper. 5 This tests whether the results are the same as a paper’s given alternative analytical decisions in conducting the analysis (like outlier omission). Closely related is the idea of a “multiverse” where you come up with many different ways of answering the same underlying research question with the same data, and test whether the results hold in all those alternative methods. There’s been work on the latter as well. 6 Some of the replications, e.g. those from the SCORE project, had paired the experiments with forecasts from prediction markets. So we get to look at this for free.
Paving the way for agents in biology
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
H-1B visa filings rise for Anthropic, OpenAI, Nvidia
Anthropic, OpenAI, and Nvidia increase H-1B visa applications as other tech giants cut back, highlighting the AI talent demand.
Miami luxury home seller considers AI shares as payment
A Miami home seller is open to accepting shares in OpenAI, Anthropic, or SpaceX as payment, reflecting a trend in investment strategy.
Smart people weigh in on Anthropic's AI pause proposal
"We believe it would be good for the world to have the option to slow or temporarily pause," two leading Anthropic officials wrote.
Trump says he’s considering government stake in top AI companies
Industry leaders will soon gather at the White House to discuss the idea, the president said. The comments come as SpaceX, Anthropic and OpenAI prepare to go public.
What to Expect From WWDC 2026: Gemini-Powered Siri, iOS 27, macOS 27 and More
Apple's 2026 Worldwide Developers Conference is just days away, and it's going to be an interesting event because it will give us a look at Apple's AI plans. We'll see how Apple is going to compete with OpenAI, Anthropic, and Google in the months to come with an AI version of Siri and new AI features for its apps. Subscribe to the MacRumors YouTube channel for more videos.
Melinda French Gates is done waiting for health care to take menopause seriously
Celebrities like Halle Berry and Naomi Watts have jumped on menopause startups. Now Melinda French Gates is throwing her weight behind the category—with philanthropic dollars.
Anthropic says leading AI labs may need to hit the brakes
Anthropic called for a coordinated slowdown in AI development, warning that AI capabilities could advance faster than society can adapt.
Anthropic shares accepted for Brooklyn home's $5.99M price: photos
A Brooklyn home seller is seeking Anthropic shares or bitcoin for a $5.99M property, reflecting AI equity's rise in real estate transactions.
Google Challenges AI Rivals With Its Financial Muscle | AI & Business for June 2
Plus, Anthropic gets the IPO ball rolling and Nvidia makes a play for the PC market.
OpenAI and Anthropic have a new rivalry: who rings the bell first
Conventional wisdom holds that going public first is better because there is only so much capital to go around. But what if it's better to go second?
Sam Altman weighs in on IPO race after Anthropic files to go public
Hours after Anthropic filed paperwork for an IPO, Altman said OpenAI is not focused on the timing of who goes public first.
Roundup: US retail industry / Anthropic / Business opportunity
Facing challenges: The retail industry emerged from a choppy first quarter relatively unscathed, but higher-than-usual tax refunds likely helped to buoy spending. The second quarter could offer a clearer view on consumer health and just how much gas price increases and persistent inflation have disrupted the economy and put more pressure on household budgets. The […]
AI giant Anthropic confidentially files for US IPO
AI giant Anthropic said on Monday it has confidentially filed for a U.S. initial public offering, teeing up what could become the watershed moment for Wall Street's AI frenzy.
Nvidia-backed $5 billion AI company tells CNBC it's launching major expansion in London
Runway follows U.S. AI giants including Anthropic and OpenAI in announcing big London growth plans.
The $900 Billion Giant: How Anthropic Got So Big, So Fast
The artificial intelligence giant was just valued at $900 billion, surpassing OpenAI. Here are the numbers behind its rise — and headwinds it faces.
Anthropic raises $65 billion, now valued at $965 billion
Anthropic said on Thursday it has raised $65 billion in a series H funding round, valuing it at $965 billion post-money.
Elon Musk says SpaceX only has 180-day agreement with Anthropic
On Thursday, Musk wrote on X the deal between SpaceX and Anthropic is a "180 day lease."
AI Advice From Anthropic’s Head Of U.S. Small Business
Anthropic’s Lina Ochman explains how small businesses can use Claude, AI workflows, data connectors and employee-like prompting to save time.
Andre Dowell: Palm Beach’s philanthropic power grows beyond campaign politics
Palm Beach philanthropy increasingly shapes America’s civic and political future.
Coding agents in the social sciences
Results from a survey of 1,260 social scientists about AI and coding agent use.
Analysis Of Anthropic Claude System-Prompt Instruction That Shapes The Handling Of AI Mental Health Chats
Anthropic Claude provides open access to their system-wide prompt. I analyze the portions dealing with AI mental health guidance. An AI Insider analysis and scoop.
New graduate makes philanthropic gift to Penn State Smeal College of Business
Palmer Moore, who recently graduated with a degree in finance from the Penn State Smeal College of Business, recently made a gift to benefit two programs that contributed to his success: the Sapphire Leadership Academic Program and the Center for Business Ethics and Social Responsibility. Palmer was a member of the centers' Business Ethics Team.
SpaceX’s AI Business Waits for Liftoff | AI & Business for May 26
Plus, California studies AI job losses, Anthropic’s revenue soars and Nvidia plays the role of $5 trillion underdog.
Tech leasing picks up in Seattle as giant firms eye expansion
AI powerhouse Anthropic is leading a small wave of leasing activity in Seattle.
Pope Leo XIV isn't joining Anthropic, but the memes are funny
A Vatican appearance by Anthropic co-founder Chris Olah prompted jokes that Pope Leo had joined the AI startup. Here's what happened.
AI is getting worse as Google and Anthropic nerf AI models and limit usage
Evidence is mounting that the subsidization of AI is ending in real time. Will businesses still shell out for it?
Run Your Whole Business From One Tab With Claude's New Update
Claude's new update runs payroll, month-end and campaigns inside QuickBooks, PayPal and HubSpot. Is Anthropic going after Zapier? Here's a look.
AI's COVID shutdown moment: SpaceX IPO, Anthropic, OpenAI, Nvidia
From SpaceX's IPO to Anthropic's massive revenue number, it looks like AI just had the day when the hype became real.
AI Training For Small Businesses Goes Nationwide
Free AI training from the U.S. Chamber and new tools from Anthropic are arriving just as small business formation surges and the AI adoption gap begins to close.
CEO of Paul Allen’s $3.1B science and tech fund stepping down less than a year after launch
Dr. Lynda Stuart is departing as the first CEO of the Fund for Science and Technology, the foundation created under late Microsoft co-founder Paul Allen's instructions. The change comes amid broader shifts in the Allen philanthropic ecosystem, including the departures of top AI researchers from the Allen Institute for AI.
Anthropic is paying SpaceX $1.25 billion a month for AI compute
SpaceX and Anthropic have a major compute power deal valued at $1.25 billion a month, utilizing SpaceX's Colossus data centers for AI growth.
Google to release smart glasses and add AI ‘agents’ to search engine
CEO Sundar Pichai says features powered by new Gemini model will close gap with Anthropic and OpenAI
Anthropic hires former OpenAI and Tesla AI boss Andrej Karpathy
Andrej Karpathy, the OpenAI founding member who was formerly Tesla's AI boss, announced on Tuesday that he had joined Anthropic.
KPMG integrates Claude across its core business and workforce of more than 276,000 in strategic alliance
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
Marc Benioff said Salesforce will spend $300M on Anthropic tokens
Salesforce CEO Marc Benioff said he's able to work faster with AI agents and that the company is working on tech to make coding easier at Slack.
Google's slimmed down Gemini model is quietly winning AI customers
Vercel CEO Guillermo Rauch highlights Google's Gemini Flash model's rise in AI demand, overtaking Anthropic in Vercel's AI Gateway.
Security Researchers, Aided By Anthropic's Mythos, Claim To Have Breached macOS
Apple is taking the claims seriously.
Anthropic And Gates Foundation Sign $200 Million Partnership For AI Use In Health, Education, Agriculture
The partnership commits $200 million over four years to develop AI tools for use in vaccine research, farming guidance, education and other areas.
Anthropic, Gates Foundation launch $200 million partnership for AI in health, education
Anthropic and the Gates Foundation have pledged $200 million to back artificial intelligence-related public goods and areas including health and education, they said on Thursday.
Anthropic, Gates Foundation launch $200 million partnership for AI in health, education
SAN FRANCISCO, May 14 (Reuters) - Anthropic and the Gates Foundation have pledged $200 million to back artificial intelligence-related public goods and areas including health and education, they said on Thursday. Support from Anthropic's technical staff and usage credits for its Claude AI will account for its half of the financial commitment, while the Bill Gates co-founded Gates Foundation will provide grant funding, program design and expertise, officials told Reuters.
Anthropic forms $200 million partnership with the Gates Foundation
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
Google is about to release a new Gemini model
Sources say that Google plans to announce a new Gemini model at its annual I/O conference on Tuesday. I’m told the release will land roughly in the class of OpenAI’s recent GPT-5.5. and well short of Anthropic’s Mythos, which, despite not being widely available, has reset how every lab talks about what “leading” means.
Microsoft’s multi-agent AI system tops Anthropic’s Mythos on cybersecurity benchmark
Microsoft's new vulnerability-scanning system, codenamed MDASH, scored 88.45% on the CyberGym benchmark, surpassing single-model systems from Anthropic and OpenAI by using more than 100 specialized AI agents across multiple models.
AI transformed Anthropic's workplace, coding 90% of projects, CFO says
Krishna Rao of Anthropic discusses AI's impact on automating white-collar tasks, increasing productivity, and shifting employee roles to management.
Anthropic’s latest Claude release turns your Mac into a small business powerhouse
If you run a small business from your Mac, you’ll want to pay attention to Anthropic’s latest Claude release. Claude...
Anthropic launches Claude for Small Business with QuickBooks, PayPal
The AI company says small businesses account for 44% of U.S. GDP but have lagged behind larger enterprises in AI adoption
Anthropic's Newest Claude Feature Is Here to Help Small Business Owners With Their Pain Points
Claude for Small Business will assist with payroll, the books, and more. An Anthropic exec explains precisely how.
Anthropic wants small businesses to use Claude
The company launched new tools designed for lean teams.
Anthropic debuts Claude for Small Business as it continues its enterprise software push
Anthropic is entering the small business market.
Anthropic courts a new kind of customer: small business owners
Anthropic is looking to broaden its customer base from larger enterprise customers to smaller and mid-sized businesses.
Anthropic tops OpenAI in business AI adoption for the first time
Anthropic surpassed OpenAI in AI business spending, according to Ramp's AI Index, marking a significant shift in AI adoption for the Claude creator.
Anthropic now has more business customers than OpenAI, according to Ramp data
For the first time, Anthropic has more verified business customers than OpenAI, according to this month’s AI Index from the fintech firm Ramp.
Introducing Claude for Small Business
We're launching Claude for Small Business, a package of connectors and ready-to-run workflows that put Claude inside the tools small businesses use every day.
Anthropic expands legal AI tools, boosting Claude Cowork
Anthropic's new release of legal AI tools for Claude Cowork is an ambitious effort to become the law industry's new hub.
SAP and Anthropic Plan to Bring Claude to SAP Business AI Platform
SAP and Anthropic will embed Claude across SAP's AI-enabled solution portfolio, powered by Joule and Joule agents.
A Philanthropic Tree of Life: Seeding Health Equity Through Influence and Innovation
Editor’s Note: This article was first published by Grantmakers in Health here and was authored by: Gaea A. Daniel, Assistant Professor, Emory University (Direct Relief Fund for Health Equity …
Google thwarts suspected hacker attempt to use AI for large-scale exploitation
Google says it blocked hackers using AI to find a zero-day and bypass 2FA, amid Anthropic’s delayed Mythos launch.
Google says it likely thwarted effort by hacker group to use AI for 'mass exploitation event'
Hackers are rapidly adopting AI to find previously unknown software flaws even without the help of Anthropic's powerful Mythos model.
Anthropic pins Claude's blackmail on the internet's portrayal of AI
Last year, Anthropic's Sonnet 3.6 model displayed blackmail behavior, prompting a review of AI training data's influence on its actions.
Using Claude? Thank Elon Musk
Anthropic now relies on a huge SpaceX data center for AI compute, tying Claude's rapid growth and reliability to Elon Musk.
Mozilla says Anthropic's Mythos found hundreds of flaws
Mozilla says Anthropic's unreleased Claude Mythos AI found security flaws that automated testing systems missed for years.
Hantavirus Scramble Tests Trump’s Overhauled CDC
Plus, Anthropic’s Mythos has thrown the White House AI strategy into chaos.
Anthropic introduces "dreaming," a system that lets AI agents learn from their own mistakes
Anthropic has launched “dreaming” for AI agents, giving Claude new self-improving tools designed to boost enterprise automation, reliability, and scale.
Mozilla says AI helped squash 423 Firefox security bugs
Yet it remains unclear if Anthropic's uber model was effective, or if better model middleware is what makes the difference
How Anthropic’s Mythos has rewritten Firefox’s approach to cybersecurity
Security researchers at Mozilla say Anthropic's Mythos has unearthed a wealth of high-severity bugs in Firefox.
Anthropic updates Claude Managed Agents with three new features
Anthropic launched Claude Managed Agents last month, greatly simplifying the work required to build and deploy cloud-hosted AI agents. This...
I Am Begging AI Companies to Stop Naming Features After Human Processes
Anthropic announced “dreaming” for AI agents to sort through “memories” at its developer conference. Can we not?
Anthropic's Claude Managed Agents can now "dream," sort of
Also, rate limits will double for Pro and Max users of tools like Claude Code.
Anthropic introduces 'dreaming' technique for AI agents
Anthropic introduces 'dreaming,' a technique for AI agents to self-improve within the Claude Managed Agents tool.
Anthropic will let its managed agents dream
Anthropic is expanding Managed Agents with dreaming — a scheduled memory process — plus outcomes-based evaluation and multi-agent orchestration now in public beta.
Anthropic just launched AI agent tools to shake up finance grunt work
Anthropic introduced 10 AI agents for the finance industry on Tuesday, adding to the tools already available from buzzy startups and firms themselves.
Wall Street opens up its partnership playbook for AI
Finance giants are teaming up with OpenAI and Anthropic to help them spin up consulting arms. It's a classic strategy Wall Street has deployed before.
Wall Street's $1.5 billion plan to build the 'McKinsey of AI'
Some of Wall Street's biggest investors, like Blackstone, are teaming up with Anthropic to build a consulting firm for the AI future.
Big Tech Targets Drug Discovery with Wave of Life Science Platforms
AWS, OpenAI, and Anthropic have all unveiled specialized AI workflows that promise to accelerate scientific discovery
Anthropic Nears $1.5 Billion Joint Venture With Wall Street Firms
Anthropic, Blackstone and Hellman & Friedman each expected to invest around $300 million; Goldman Sachs also an investor.
Google Cloud is almost one-fifth of Alphabet’s business
Plus: Amazon, Anthropic, Microsoft, Musk v. Altman, Parallel, Qualcomm, Samsung, SoftBank.
Blackstone Forms New Unit to Oversee AI, High-Growth Tech Bets
Blackstone Inc. is folding its growth business into a new West Coast-based division that will focus solely on the alternative investment giant’s artificial intelligence portfolio, which includes OpenAI and Anthropic PBC.
Anthropic doubles estimate for Claude Code token spend
Anthropic now says that the average cost per developer per active day is $13, up from $6 earlier this month.
Claude Gains Integrations With Adobe, Blender, SketchUp and Other Creative Apps
Anthropic today updated Claude with new connectors aimed at creative professionals, adding integrations for Ableton, Adobe, Affinity, Autodesk Fusion, Blender, Resolume Arena and Wire, SketchUp, and Splice. Connectors are tools that Claude can use to access other platforms and help with completing tasks. Anthropic says that Claude can open up new ways for creatives to work and take on larger-scale projects.
Claude can now plug directly into Photoshop, Blender, and Ableton
Anthropic is really leaning into creative AI services.
A startup says Cursor's AI agent deleted its production database
The founder of PocketOS said that a Cursor AI agent running on Anthropic's Claude Opus model was behind the "destructive action."
Google To Up Anthropic Investment As Cloud Giants Chase AI Business
Alphabet plans to invest $10 billion more in Anthropic and possibly up to $40 billion more. Google stock edged up amid the news.
Claude can now connect to lifestyle apps like Spotify, Instacart and AllTrails
Anthropic is expanding its directory of connected services for its Claude AI chatbot.
Anthropic acknowledges Claude Code issues, denies 'nerfing'
Anthropic said it found three issues with Claude Code after users complained the AI tool deteriorated.
Ranked: AI Models U.S. Businesses Pay For
OpenAI has long been the leader for paid usage by U.S. businesses, but Anthropic has closed the gap with tools like Claude Code and Cowork.
Anthropic has surged to a trillion-dollar valuation on secondary markets.
Buyers are in a race to secure a dwindling supply of shares in Anthropic, driving the AI company's valuation on some platforms to $1 trillion.
SpaceX and Cursor: What smart people are saying about the $60B deal
Partnering with Cursor could be a crucial step for Elon Musk to get ahead of AI rivals like OpenAI and Anthropic.
Elon Musk explores Mistral partnership to take on AI rivals
Musk is eyeing a collaboration with French startup Mistral to help xAI catch Anthropic and OpenAI.
Claude Mythos AI Model Uncovers 271 Zero-Day Vulnerabilities in Firefox
Anthropic’s latest frontier AI model, Claude Mythos Preview, has identified a staggering 271 zero-day vulnerabilities in Mozilla Firefox marking a seismic shift in AI-powered cybersecurity defense. The findings, addressed in Firefox 150, represent the most significant single batch of security fixes in the browser’s history. The discovery didn’t happen in isolation. Since February 2026, Mozilla’s […]
Sam Altman: Anthropic is using 'fear' to tout Claude Mythos
OpenAI CEO Sam Altman said in contrast to Anthropic's recent moves, OpenAI would err on the side of giving more people access to AI models.
Mozilla says it patched 271 Firefox vulnerabilities thanks to Anthropic's Claude Mythos
Mozilla shared some details that support Anthropic's Claude Mythos AI model as a way to protect critical services.