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Article · 2026-08-02 · 6 moments

Open letters about AI development

Open letters about AI development I wrote this summary of the past few weeks of open letters as a section of my sponsors-only newsletter but I've decided to share it here as well. Open Weights and American AI Leadership was shepherded by Microsoft, dated July 24th, and signed by 235 AI-adjacent companies including NVIDIA, Amazon, Y Combinator, The Linux Foundation and (a later signer) OpenAI. It's clearly an argument designed to counter any instincts by the current US government to ban or lim ✦ AI generated

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Anthropic, notably absent from the open-weights letter's signatures, published its own response three days later in which CEO Dario Amodei warned of authoritarian governments building AI models more powerful than those of the US and of models being misused for cyberattacks or biological attacks, called for a crackdown on industrial-scale distillation operations, and stated that Anthropic has never advocated for a ban on open-weights models.

The author notes Anthropic declined to sign and instead published 'Our position on open-weights models,' in which Amodei warned about authoritarian regimes building more powerful AI and models being misused for cyber or biological attacks, called for a crackdown on industrial-scale distillation, and denied that Anthropic ever advocated a ban on open-weights models.

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the author: Notably absent from the signatures: Anthropic, who published their own response Our position on open-weights models three days later. CEO Dario Amodei doubled down on the risk of authoritarian governments building "AI models that are more powerful than those built by the US", and models being "misused to carry out cyberattacks or biological attacks", and called for "a crack down on industrial-scale distillation operations", while also stating that "Anthropic has never advocated for a ban on open-weights models".

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Open Weights and American AI Leadership is an open letter shepherded by Microsoft, dated July 24th, and signed by 235 AI-adjacent companies including NVIDIA, Amazon, Y Combinator, The Linux Foundation and (as a later signer) OpenAI.

The author introduces the 'Open Weights and American AI Leadership' letter: shepherded by Microsoft, dated July 24th, and signed by 235 AI-adjacent companies including NVIDIA, Amazon, Y Combinator, The Linux Foundation and OpenAI.

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the author: Open Weights and American AI Leadership was shepherded by Microsoft, dated July 24th, and signed by 235 AI-adjacent companies including NVIDIA, Amazon, Y Combinator, The Linux Foundation and (a later signer) OpenAI.

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Policymakers should not conflate legitimate model-development techniques with misappropriation: distillation, the practice of using one model's outputs to help train or improve another, is a widely used technique for model improvement, evaluation, and validation that reflects a long tradition of learning from and building upon existing technologies.

The author flags the letter's surprising pro-distillation stance and quotes its argument: distillation is a widely used, legitimate technique rooted in the open-source software tradition, and policymakers should not conflate it with misappropriation.

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the Open Weights and American AI Leadership letter: In shaping this ecosystem, policymakers should be careful not to conflate legitimate model-development techniques with misappropriation. Distillation, or the practice of using one model's outputs to help train or improve another, is a widely used technique for model improvement, evaluation, and validation. It reflects a long tradition of learning from, building upon, and improving existing technologies, a tradition that has helped drive innovation since the rise of the open-source software movement.

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Relying solely on closed models is not inherently safe — they can be breached, misused, or fail in ways outsiders cannot detect — and concentrating advanced AI capabilities behind a small number of closed models compounds that risk into single points of failure, weakened competition, and control by a few providers, whereas open weight models allow a broad community to examine their behavior, identify vulnerabilities, develop safeguards, and improve them over time.

The author lays out the open-weights letter's core argument: it is designed to counter US government instincts to ban or limit open weight models on safety grounds, because closed-only ecosystems are not inherently safe and open weights enable community scrutiny and improvement.

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the author: It's clearly an argument designed to counter any instincts by the current US government to ban or limit open weight models over "safety" concerns - a reasonable consideration given what happened to Claude Fable 5! Relying solely on closed models is not inherently safe: they can be breached, misused, or fail in ways that outsiders cannot detect. And concentrating advanced AI capabilities behind a small number of closed models compounds that risk. It results in a small number of single points of failure, weakens competition, and leaves critical technology in the hands of a few providers. Open weight models, on the other hand, allow a broad community of researchers and developers to examine their behavior, identify vulnerabilities, develop safeguards, and improve them over time.

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The combination of intense competitive pressure and accelerated AI progress caused by automated AI research is a serious risk that people are taking more seriously now — evidenced by Anthropic producing 80% of its code with Claude Code, OpenAI's Sol reducing end-to-end serving costs by 20%, and Kimi K3 designing a chip to serve a nano model built on its own architecture.

The author explains the Pacing letter's underlying concern — competitive pressure plus automated AI research accelerating progress — and cites concrete evidence (Anthropic's 80% Claude Code usage, OpenAI's Sol cutting serving costs 20%, Kimi K3 designing its own chip) for why that risk is being taken seriously.

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the author: Their concern is intense competitive pressure combined with accelerated AI progress caused by automated AI research - and given that Anthropic produce 80% of their code with Claude Code, OpenAI had Sol reduce their end-to-end serving costs by 20%, and Kimi K3 designed a chip to serve a nano model built on its own architecture, you can see why people are taking that risk more seriously right now.

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The US government should support an international effort to develop the technical and governance tools needed to deliberately pace the frontier of automated AI development.

The author introduces 'Pacing the Frontier,' published July 28th with signatures from 1,324 employees of frontier AI companies (including Jakub Pachocki, Ilya Sutskever, Dario Amodei and Jack Clark), and quotes its core request: a US-backed international effort to deliberately pace the frontier of automated AI development.

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the Pacing the Frontier letter signatories: We request that the U.S. government support an international effort to develop the technical and governance tools needed to deliberately pace the frontier of automated AI development.

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Highlight slides
The pacing letter's core concern✦ from: The combination of intense competitive pressure and accelerated AI progress caused by automated AI research is a serious risk that people are taking more seriously now — evidenced by Anthropic producing 80% of its code with Claude Code, OpenAI's Sol reducing end-to-end serving costs by 20%, and Kimi K3 designing a chip to serve a nano model built on its own architecture.Closed-Only AI Is Not Inherently Safe✦ from: Relying solely on closed models is not inherently safe — they can be breached, misused, or fail in ways outsiders cannot detect — and concentrating advanced AI capabilities behind a small number of closed models compounds that risk into single points of failure, weakened competition, and control by a few providers, whereas open weight models allow a broad community to examine their behavior, identify vulnerabilities, develop safeguards, and improve them over time.AI is building AI: the evidence✦ from: The combination of intense competitive pressure and accelerated AI progress caused by automated AI research is a serious risk that people are taking more seriously now — evidenced by Anthropic producing 80% of its code with Claude Code, OpenAI's Sol reducing end-to-end serving costs by 20%, and Kimi K3 designing a chip to serve a nano model built on its own architecture.Concentration Compounds the Risk✦ from: Relying solely on closed models is not inherently safe — they can be breached, misused, or fail in ways outsiders cannot detect — and concentrating advanced AI capabilities behind a small number of closed models compounds that risk into single points of failure, weakened competition, and control by a few providers, whereas open weight models allow a broad community to examine their behavior, identify vulnerabilities, develop safeguards, and improve them over time.Why the risk is being taken seriously✦ from: The combination of intense competitive pressure and accelerated AI progress caused by automated AI research is a serious risk that people are taking more seriously now — evidenced by Anthropic producing 80% of its code with Claude Code, OpenAI's Sol reducing end-to-end serving costs by 20%, and Kimi K3 designing a chip to serve a nano model built on its own architecture.Open Weights Enable Community Oversight✦ from: Relying solely on closed models is not inherently safe — they can be breached, misused, or fail in ways outsiders cannot detect — and concentrating advanced AI capabilities behind a small number of closed models compounds that risk into single points of failure, weakened competition, and control by a few providers, whereas open weight models allow a broad community to examine their behavior, identify vulnerabilities, develop safeguards, and improve them over time.
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