anthropic – Teknotum

Anthropic launches 5% Public Benefit Fund that grows with the company

A potential 20% of a trillion-dollar IPO is $200 billion. (Picture: Anthropic)

Anthropic says they are already doing a lot of good through its main company, like doing beneficial research and giving discounts to nonprofits and scientists, but say they want more flexibility.

That’s why they are forming a new entity dedicated entirely to the «public good,» so they can make large donations to nonprofits or «direct distributions to specific populations.»

They are also singling out the job market, saying they have already donated $200 million to study AI’s effects, but may want «bolder approaches.» It will not be used for lobbying or politics, Anthropic says.

The new company will be a wholly owned LLC, and will initially be funded by 5% of Anthropic’s stock. Together with their founders’ pledge to donate 80% of their equity and a donation match for employees, they reckon the fund will hold roughly 20% of Anthropic’s shares in total, making it a substantial entity.

The fund will also grow by 2% of Anthropic’s shares for every 50% increase in the company’s value, subject to board approval.

Read more: Anthropic’s presentation, X post. Reuters, CNBC, and TechCrunch. Discussion on r/Singularity and Hacker News.

Anthropic’s Claude-powered biology lab makes its first scientific discovery

The repeating DNA in bacteriophages could possibly reveal a gene-editing method. (Picture: generated)

Anthropic set up its wet science lab in the spring of 2026, and it has already made its first important discovery.

Claude itself has autonomously discovered an enzyme hidden in the DNA of bacteriophages that sits beside a «long array of repeating DNA,» that could work in a similar way to CRISPR — todays most common DNA-editing tool, and a discovery that won the Nobel Prize.

Claude found the enzyme almost entirely on its own, searching through a massive database of DNA sequences for interesting candidates from a human prompt. It took 21 hours, 950 agents and 210 million tokens until an agent made the discovery of repeating DNA sequences. It was then analyzed and tested by scientists in the lab.

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Anthropic launches Opus 5.5 with better efficiency, alignment and cost

Anthropic is keeping its promise with external evaluators on this model, leading to better alignment. (Picture: Anthropic)

Claude Opus 5.5 is the first release since Anthropic’s pacing pledge, and has been run through external evaluators such as Frontier Design and METR.

It is the best model Anthropic has tested so far on its internal alignment tests and comes with strong safeguards inherited from Fable.

40% cheaper on typical tasks
Opus 5.5 costs $4 per million input tokens and $20 per million in output, 20 percent below Opus 5. Cache reads fall 60 percent to $0.20 per million tokens.

Anthropic says typical workloads cost around 40 percent less overall, while using fewer tokens per task. Output is also more than 30 percent faster.

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Anthropic has already set up a wet lab to test biology and Claude automation

The wet lab is not intended to compete with drug discoverers, but to test the limits of lab automation. (Picture: generated)

CEO Dario Amodei said the mission is to cure cancer and most human diseases in ~5-10 years, but AI alone can’t do all the experiments «in silico,» Reuters reports.

They are saying that Anthropic already has a biology lab in San Francisco, and is working on pushing automation with Claude as far as possible.

They also hope to do pre-clinical work on diseases thought «undruggable,» meaning they are too expensive or complex to cure.

— The mission of the company is to develop powerful AI in such a way that [it] benefits the world, Anthropic’s head of life sciences, Eric Kauderer-Abrams tells Reuters. — By far, we see the biggest opportunity for that in the life sciences, and that is motivating everything that we’re doing.

That said, Anthropic also works with external lab partners for what seems a lot of their «normal» biology testing.

Read more: Reuters, TechCrunch, Engadget. Discussion on r/technology and Hacker News.

Anthropic reaches 90% AI use in model development, «leading» 26% of cases

AI use for improving models has not yet reached fully autonomous levels, but «leads» more often. (Picture: generated)

The AI lab has determined a methodology for measuring how AI is being used to build the next models, detail the extent and method of use, test their ability to intervene, and measure the resources used.

Anthropic randomly sampled 20% of research and development staff’s Claude usage for each week of July, and then used Claude to organize them. This was done using an «automation rating scale» from Epoch AI, classifying tasks from AL0, meaning no AI involvement, to AL5, which is fully autonomous AI.

They found that none of the usage reached AL5, but AL4 was 26% of the tasks — meaning AI is «leading» from «high-level prompts» with human supervision, while more than 90% of the tasks were AL3 — which is AI «collaboration» under «close human direction.»

AI «leading» is up from 1% in February 2026, and Anthropic estimates that they now have 30,000 agents in use at any time for research and engineering, that use real-time monitoring that can block «dangerous actions.» As agent use eventually grows ever larger, even rare use cases become more likely, Anthropic says.

The measure is a way of determining how close we are getting to recursive self-improvement, meaning AI writing itself, which could lead to a lack of control of the technology. Anthropic says every lab could publish such reports if there was a standard, which they hope to contribute to. They will also keep publishing these.

It’s also a step toward better third-party monitoring at Anthropic, which plans to install independent evaluators with employee-level access soon, as promised in their call for «pacing».

Read more: Anthropic’s report. Coverage on Reuters, ABC News, The Washington Post, and Bloomberg. Discussion on r/Singularity.

Anthropic, Google and OpenAI are discussing an industry standards body

The standards body would be independent and technical, and provide guidance for frontier labs. (Picture: generated)

With OpenAI’s Sam Altman’s post on X yesterday, saying that he would welcome «a federal framework that sets consistent safety requirements for frontier AI,» it seems work is already underway for a less formal version of an industry standards body involving the frontier labs, sources are telling CNN and The Information.

The discussions «are ongoing» and are happening «with or without» the Trump administration, CNN says.

An industry standards body seems framed around Google’s Chief Scientist Demis Hassabis’ proposal from July this year, ideas that were referenced in Amodei’s «pacing» essay just a few days ago.

This body would be loosely based on the Financial Industry Regulatory Authority which is a self-regulatory organization for brokerages and exchanges governed by the Securities and Exchange Commission.

According to Hassabis, it would have an independent board and be staffed with «leading technical experts and open source representatives,» and be charged with «developing assessment protocols» for frontier AI. Labs would then submit their models for pre-release evaluation.

Sam Altman said in his X post yesterday that «we think shared standards for misalignment, monitoring, and safety will lead to better outcomes,» and that the industry must take independent steps toward regulation as «we do not believe we need to wait for an anti-trust exemption or legislation to begin the work of providing this confidence.»

«We look forward to collaborating with our colleagues across the industry to formulate the best version of these,» Altman wrote, in the most direct support of such an organization outside of Google and Anthropic yet.

Read more: CNN and The Information. Hassabis’ X post, Altman’s X posts. Discussion on Digg.

Amodei calls for global pacing of AI; Altman, Musk, Hassabis all agree

Anthropic CEO Dario Amodei published a lengthy, 3,600 word essay Saturday on the importance of slowing down ever more capable AI rollouts, and is already committing to the first part of his three-part plan.

Industry insiders seem to all agree that the Hugging Face incident and the rapid advances toward self-improvement have turned up some huge red flags.

Amodei reckons a more capable model with agent swarms and the same alignment problems could bring down the internet in 6-12 months, causing billions of dollars of damage, while self-improving AIs risk losing human control of their accellarating development.

Continue reading “Amodei calls for global pacing of AI; Altman, Musk, Hassabis all agree”

Anthropic’s new threat report details misuse across broad capabilities

Not just hackers, but increasingly sophisticated biological, cyber and influence campaigns have tried to use Claude. (Picture: generated)

AI is increasingly used as an efficiency multiplier in intelligence work from Ukraine to China and Yemen, Anthropic’s threat report says.

Attempted threat activity on Claude ranges across the gamut, from cyber to influence and surveillance, scams and fraud, biological misuse and conventional weapons development.

The periodic report details what Anthropic caught and mitigated in slightly older models such as Claude Haiku, Sonnet or Opus, whereas Mythos- and Fable-class models have much stronger safeguards out of the box.

One prominent target for classical cyber operations was Ukraine’s drone industry, trying to create malware for use in disruption and surveillance.

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OpenAI hires safety expert to foundation board, and he also has a warning

AI is entering a crucially important run of development, ever more researchers say. (Picture: generated)

The Safety and Security Committee of the OpenAI Foundation’s board has a new member in Paul Christiano, a long-running researcher on alignment and safety — and he comes with a warning for the world:

— If we build superintelligence without more robust alignment I expect we will permanently lose control of it, he writes on X, and says — If that happens then most people could die.

The warning comes on the heels of rapid growth in recursive self-improvement recently, and the debate over whether computer systems and AI might gain the possibility to build on themselves at some point in the future. OpenAI reckons they’ll have autonmous AI researchers around 2028, but warns it may come sooner.

His appointment and X essay come just a day after Anthropic researcher Jacob Coxon resigned over alignment, saying his company was «gambling with our lives» by running head-first toward self-improving AI, going viral in the process.

In a reply to his X post yesterday, Anthropic’s Alignment Science Lead Evan Hubinger said he personally thinks there’s a greater than 10% risk that AI could kill all humans, contributing to the dayslong online debate.

OpenAI officially acknowledges that AI is heading for a new era, saying that: «We’ve reached a new chapter in AI capabilities, and that demands a new chapter for AI policy.» They also add that «this makes it increasingly important that these systems are guided by solid safety, security, alignment, and governance.»

Paul Christiano remains hopeful, ending his X essay by saying that «frontier AI developers have a lot of power to unilaterally improve the situation and lay the groundwork for stronger coordination.»

Anthropic launches Fable and Mythos 5.1 — with great leaps in science, agents

Fable 5.1 will be less annoying to talk to, Anthropic says, after 5.0 had too strict safeguards. (Picture: Anthropic)

Fable 5.1 «sets a new standard» in performance, Anthropic says, and does take great leaps on the benchmarks, particularly on agentic coding, knowledge work and science.

The new models score as well or better than Fable 5 for lower cost on the lowest setting. While the sticker price is the same ($10 per M input, $50 out), it is much more efficient and gets the work done with 25% fewer tokens, with 45% less for «highly agentic work.»

Anthropic also says it takes fewer shortcuts in its work, leading to higher-quality outputs compared to Fable 5, and that its safeguards have reduced false positives by 60% — meaning that it will be less restrictive.

The model also stands out in science, scoring more than double Fable 5’s result in the Terminal-Bench-Science benchmark, and while Anthropic aren’t making any specific claims, they do say that «AI models will soon make important contributions to scientific discovery,» and that the new models «offer an early glimpse.»

On cybersecurity, Fable 5.1 is good enough to discover vulnerabilities in code and software, but it is not capable of develop exploits for them. For that, you would need access to Mythos 5.1, which is, as before, the same model with looser safeguards that is only available to trusted partners.

Read more: Anthropic’s announcement and X launch post. The Verge, TechCrunch, Mashable, and Artificial Analysis. Discussion on Hacker News and r/Singularity.

Anthropic previews model interface for AI control of physical devices

The proposed new interface standard will not only make it easier to coordinate and control things like factory floors and lab facilities, but it will also infuse AI agents into the process, allowing for scripting — and adding natural language operations and reasoning.

This could potentially be a huge boon for scientific research and real-world labs, where Claude might one day be able to run end-to-end experiments and manipulate instruments, greatly accelerating the process.

Continue reading “Anthropic previews model interface for AI control of physical devices”

Amodei calls for better regulation, sees «early glimmers» on diseases soon

Dario Amodei wants disproportionally tougher regulation on the heavyweights than for early stage startups. (Picture: Shutterstock)

Anthropic CEO Dario Amodei posted a lengthy essay on X during the weekend, where he argues for more regulation of frontier AI models, saying that AI is «structurally a technology that tends to concentrate power.»

He lands in favor of redistribution-like regulations that benefit newer startups and «those catching up,» while disadvantaging the more powerful frontier labs.

Open source models should also be vetted once they reach a certain level, as the White House has agreed to. Open source brings «specific risks,» he argues, although he doubts they will solve the distribution or concentration problem.

On AI’s generally negative public image lately, Amodei says this is fundamentally an issue of trust:

— I think that ordinary people don’t trust companies, governments, or the tech industry and always suspect that we are cooking up some new way to screw them over, he writes.

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Anthropic’s Claude will apply invisible text watermarking to all future models

Text watermarking may help with detection, but can produce false positives, Anthropic warns. (Picture: generated)

Pursuant to the EUs AI Act’s provisions on transparency and marking of AI-generated content, Anthropic has signed on to comply with invisible watermarking of all output from Claude’s future models launched in the EU.

It’s not live in models published before August 2, 2026, but Anthropic says they are «working to add marking support» for those, too.

The text watermarking will survive through copying and pasting and «may even persist through some editing,» Anthropic says.

For files generated through Claude, Code and Cowork, the models will attach «signed provenance metadata,» which means it will tag them with origin, source and history data.

As for detection tools, there are none as of yet, but Anthropic says they are working on making one, and are cooperating with third parties, that they will share in future documentation.

There are limits to this technology, Anthropic adds. On the one hand, Claude could have been used to simply edit or proofread text, or brainstorm ideas, resulting in false positives. On the other, Claude’s content may be edited, «modified, excerpted or combined» with other text after Claude put in the markers.

It is not a first in the industry, as Google’s Gemini has been inserting SynthID watermarks in text outputs since October 2024. OpenAI has also had the tech since 2024, but won’t be releasing it yet.

Read more: Anthropic’s announcement. Writeups on The Register and Business Insider. Discussion on r/Singularity and Harcker News.

Mythos 5 and GPT-5.6 attacked external targets during AISI cyber evaluation

The agents were given internet access to download tools when they turned rogue. (Picture: generated)

The top models from Anthropic and OpenAI had their cyber guardrails turned off when they accessed the internet to manipulate people, codebases and open source projects two weekends ago.

This happened when the UK’s AI Security Institute, AISI, was running routine cybersecurity tests to capture protected information on their secured and sandboxed evaluation servers, and was only detected through human monitoring — not by automated security systems.

AISI ran the «security challenge» 122 times through several different agents, and on 10 of those occasions, the models turned malicious. They accessed the internet and in one case tried to insert malicious code in an open source project on GitHub through the Tor network, and even tried social engineering with fake accounts in an attempt to get the maintainer to approve the package.

There were 19 malicious actions in total, where 17 were from Mythos 5 and 2 coming from GPT-5.6, both running with cyber classifiers (safeguards) disabled. This won’t show up with production models, OpenAI and Anthropic says.

The internet was enabled in these tests so the agents could download any tools they might need, but AISI had not specifically prompted them to avoid unintended behavior. They do however caution that as agents grow more capable, they may act outside their remit — and incidents like this could become more common.

Read more: The AISI report, Anthropic’s response, OpenAI’s response. Writeups on Reuters, BBC, and Axios.

Anthropic’s internal test models also conducted real-world breaches

Anthropic has contacted the affected companies, and none of them had noticed the hacks. (Picture: generated)

After OpenAI’s Hugging Face incident, Anthropic conducted a large scale scan of some 141,006 evaluation transcripts, and found that their models, too, had been hacking real-world machines in three instances.

These weren’t days-long adversarial attacks like the Hugging Face one, and none of them deliberately escaped their sandbox with zero-days to cheat on an evaluation. They are nonetheless serious incidents of advanced models running on lax guardrails for internal testing getting on the internet by mistake and accessing external systems, Anthropic says.

The most serious case was by Claude Opus 4.7 during a capture-the-flag test (to gain access to a system and retrieve information) in April, when it discovered that the name of the target had a real-world web address. It then went on to seek, identify and exploit vulnerabilities believing it was part of the test. It got access to the company’s infrastructure credentials and a production database, but caused no real harm.

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