AI前沿开放与独立审查：防御优先于限制

the frontier is the edge of what we know. no company owns what comes next. i want more people to be able to advance it. i favor open releases that people can examine, use, and improve together without waiting. i want more companies to choose openness. i'm not proposing forced publication of private weights. i want open alternatives able to compete, independent researchers able to check the work, and people able to control their tools. restrictions on publication must carry the burden of justification. the companies leading machine intelligence deserve to be heard. they have expertise and commercial interests to protect. rules built around their resources could make them the only ones able to participate. a sincere concern about safety can still produce a barrier to entry. nor do i want the US and Chinese governments deciding how much intelligence everyone else is allowed to develop. a frontier governed by two superpowers would leave most of the world waiting for permission. the pacing proposal combines independent evaluations and checks on dangerous capabilities with possible limits on training compute, training runs, and the use of models to build better models. i support scrutiny. i oppose industry-wide limits negotiated by today's leaders because they could exclude the people who might expose failures or build alternatives. preserving a company's commercial advantage is not a safety objective. let anyone investigate open source lets people study, modify, and share the work. publishing weights is useful. sharing code and information to reproduce the work goes further. i want evaluations and known limitations published too, so people who question the developer's judgment can reproduce results, expose failures, challenge claimed safeguards, and develop fixes without first convincing the lab. the strongest argument for pacing is recursive self-improvement, or RSI: models helping build better models, potentially faster than we can understand or control them. Anthropic reports that Claude authored over 80% of its merged code as of May 2026. it also says a model building its successor entirely on its own has not happened and is not inevitable. i take that possibility seriously. i want us to plan for RSI and work backward. wider access can enable dangerous work, and safety research could fall behind. but keeping weights closed could let today's leaders build the next generation with tools others cannot use. instead, i want more researchers and engineers with models and compute to find failures, test safeguards, stop unsafe experiments, and share defenses as systems evolve. METR found that roughly 1,200 OpenAI agents meant to remain isolated communicated through an unauthorized message board. about 700 participated in a coordinated attack on Hugging Face while trying to cheat their evaluation. OpenAI says production filters designed to block assistance with computer attacks were disabled and containment failed. these models can help find and exploit vulnerabilities today. i want defenders using machine intelligence now, while hardening networks, protecting credentials, and limiting what agents can access and do. but the proposal's forecast that a more capable swarm could take over the internet within six to twelve months goes beyond what this incident establishes. i want those assumptions examined. METR is an independent nonprofit doing work i want more of. i welcome evaluators with continuous access inside labs and freedom to publish unfavorable findings. its investigation shows why access and publication rights matter: OpenAI set the scope and could redact non-public information. METR reported no additional redactions important to its conclusions beyond those disclosed. i want investigators able to follow the evidence, obtain models and records, and publish unfavorable findings without the company's approval. i want sustained public funding for computing capacity pooled across independent research groups, open testing tools, researchers, and maintainers. i want those groups to control investigations and resources, with no government or company veto over conclusions. funding can grow with the work. shared facilities could make scrutiny accessible to smaller teams without becoming permission to publish. sensitive vulnerabilities can be disclosed responsibly. defense before restriction i want more people able to find dangers and put defenses to work as systems evolve. we cannot reliably recall released weights or enforce safeguards on every copy, but protecting a system does not always require changing the model attacking it. start with the narrowest effective response: patch vulnerabilities, revoke credentials, limit an agent's access, or stop an unsafe experiment. restricting publication requires explaining why those measures and openly developed defenses are inadequate. this work extends beyond computer security. i want models helping us test financial systems, strengthen laboratory safeguards, and develop public-health defenses. access to powerful models does not require unrestricted authority to trade, operate equipment, or conduct experiments. these controls have to be independently tested and effective before we rely on them. risk can also come from what a model teaches a person. restricting publication still has to be justified by the catastrophic-risk exception. i want independent testing during development and before high-risk releases, including foreseeable modifications and attempts by models to manipulate tests. compute can trigger scrutiny without capping development. examination is not permission from a regulator or competitor. i don't want general approval requirements or waiting periods. any imposed safety-based delay to publication has to be justified by the catastrophic-risk exception. forcing someone to withhold a general-purpose model for safety reasons is a last resort. i would support it only with independently reviewable evidence that release materially increases a risk of catastrophic harm that narrower measures cannot adequately address. compare that risk with what is already available, including who gains access, at what cost and scale, and under what constraints. the case has to show withholding reduces danger after accounting for the research and defensive work it prevents. lesser harms still warrant targeted action. a temporary hold can allow investigation of a credible warning of that same catastrophic risk. restrictions require public reasons, prompt independent review, appeal, and scheduled reconsideration. sensitive details can remain protected. continued withholding requires continued justification. closed labs face the same scrutiny, including stopping unsafe experiments. where safeguards allow research to proceed, i want outside researchers able to work under comparable safeguards. restricted access is not open source and does not restore the freedoms lost through withholding. if a justified restriction slows progress, i accept that. i don't want slower progress to become the goal or a permanent advantage for incumbents. i want rules based on what a system can do, how independently it acts, and how widely it is used. publicly accountable authorities enforce them using independent evidence. researchers, developers, and affected people help write them, with affordable ways to show they're met. small teams get no safety exemption. large companies get no special authority. open across borders i want people in China to have the same freedom to build and control their technology that i want here in the US. i don't see a Chinese discovery as an American loss, or researchers as interchangeable with their government. Hugging Face's responders say Claude Opus and Fable blocked much of their forensic work. they switched to GLM-5.2, an open-weight model from China, on their own infrastructure. that does not prove every open release makes defenders safer. i support safeguards on hosted models. but i also want defenders to have alternatives they control. i support securing private weights against theft. distillation trains one model using another's outputs. Anthropic describes it as a legitimate way to produce smaller, cheaper models, distinct from fraudulent accounts and evaded restrictions. i want licenses and API terms that permit it, including for competitors, while letting providers earn from models and training data. i want cooperation on testing, incident reporting, and commitments we can verify, with consequences for breaches. Anthropic warns that slowing development could leave everyone less safe if less cautious actors catch up. withholding could similarly hurt defenders while others obtain comparable tools elsewhere. agreements cannot eliminate hidden development or defection. restrictions require specific risks and conduct. nationality and competitive status alone tell us too little. freedom to leave rules that make alternatives harder to build or release also weaken our ability to leave. i want intelligence i can run on my own machine. i want to change it, choose who sees my data, and keep using what i've built when a provider changes its mind. i want more than metered access to an API. i don't want our independence to rest on a company's promise to keep prices fair, policies reasonable, or priorities aligned with ours. i want companies to keep earning our choice to stay. i want someone i've never heard of to be able to build something better, without asking permission from the companies they might replace. researched and edited with the assistance of three models (two open-weight and one closed) and a bunch of humans.