Anthropic IPO 文件披露：数年内实现专家级 AI 自主工作
Anthropic 上市文件里写了自家判断：90% 代码已是 Claude 写的，还用 AI 发现了基因编辑工具，值得看看原文怎么说。
Anthropic 在 IPO 文件中预测，几年内 AI 将在多数专业和科学领域达到或超越顶尖人类专家水平，可连续自主工作数周并操控实验设备。文件称 9 月其代码库中超过 90% 的提交由 Claude 完成，模型已在参与训练数据生成、安全审计和研究代码编写。公司还披露用 Claude 发现了一种可能用于基因编辑的分子机器，尚处早期验证阶段。Anthropic 认为算力将长期供不应求，现有模型的能力经济界还远未用尽。
Anthropic expects AI that rivals top human experts, works autonomously for weeks and controls robots to become widely available within a few years.
Its IPO filing makes super exciting claims:
- Expert-level autonomous systems "within a few years": Anthropic expects AI to match or exceed leading human experts across most professional and scientific disciplines. These systems would work for hours, days or weeks, coordinate with other agents, and operate laboratory equipment and robots through digital interfaces.
- Millions of highly capable agents: Anthropic’s vision is "a country of geniuses in a data center". Vast numbers of agents working in parallel across software, physics, mathematics, biology, medicine and engineering. The company expects exponential progress in AI capabilities to continue.
- AI is already accelerating the development of its successors: Claude helps run experiments, generate and process training data, automate evaluations and safety audits, and write research code. Anthropic calls this "closing the loop": better models help discover improvements that make the next generation more capable. It says over 90% of September’s codebase contributions were written by Claude.
- Scientific progress could accelerate dramatically: Anthropic sees the potential for “compressing decades of scientific progress into years”. It also reports discovering a molecular machine with Claude that might become a new biotechnology tool, potentially for gene editing. That remains an early research finding requiring validation.
- Compute could remain the limiting factor: Anthropic expects increasingly capable models to unlock new categories of work, keeping demand ahead of available compute for the foreseeable future. It also argues that today’s models already have capabilities the wider economy has barely begun to use.
