Critical context on the new Anthropic blog: 1, AGI is *harder* than RSI (as used below). AGI: machine can do anything human can do, autonomo…

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. 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. https://www.anthropic.com/inst…

Source: Gary Marcus (X) | 2026-06-05