Gary Marcus 一针见血地拆解了 Anthropic 博客的过度乐观，做 AI 研究的团队和关注 AGI 进展的读者值得一看，避免被标题误导。
Gary Marcus 对 Anthropic 关于递归自我改进（RSI）的博客提出关键批评。他指出，博客中展示的成果属于 RSI（AI 作为人类可用的编码工具），而非 AGI（能自主完成人类所有工作的机器）。Marcus 强调，这些结果来自神经符号系统（如 Mythos 和 Claude Code），并非纯规模扩展的胜利，而是工具和符号系统的胜利。他认为，深度学习确实遇到了瓶颈，神经符号 AI 拯救了它，而实现 AGI 需要新思路，而非仅靠代码优化。因此，我们不必过度恐慌。
Critical context on the new Anthropic blog: 1, AGI is *harder* than RSI (as used below). AGI: mach...
Critical context on the new Anthropic blog: 1, AGI is *harder* than RSI (as used below). AGI: machine can do anything human can do, autonomously [not achieved] RSI (as used below): AI is a useful coding tool that humans can leverage [achieved]; it’s great at (some) code optimizations The results in the blog are about RSI, not AGI. Getting to AGI will require new ideas, not just new code optimizations. So we don’t need to panic yet. 2. Technical note: Mythos and Claude Code are neurosymbolic systems; this isn’t a victory for pure scaling per se, it’s victory for harnesses and symbolic tools. Deep learning did hit a wall; neurosymbolic AI rescued it.* The new results show progress on AI; they don’t show that that progress is general, and they don’t show that massive data centers will be critical. —— *My own claim was never that AI would hit a wall, or that deep learning should be abandoned, but that we would need to supplement it with neurosymbolic AI, in order to address the limitation of pure scaling. And that’s exactly what happened. Go back and reread my 2022 paper if you don’t believe me. Anthropic @AnthropicAI Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor. It’s happening faster than we thought, and the implications deserve greater attention. anthropic.com/institute/recu… 🔗 View Quoted Tweet 💬 4 🔄 1 ❤️ 13 👀 1553 📊 4 ⚡