RICHARD FEYNMAN’S WHOLE LEARNING PHILOSOPHY… PACKED INTO ONE PROMPT I spent days engineering a meta-prompt that teaches you any topic using Feynman’s exact approach: simple analogies, ruthless clarity, iterative refinement, and guided self-explanation. It feels like having a Nobel-level tutor inside ChatGPT and Claude👇

Holy shit… Meta just dropped a paper that flips the “AI will improve itself and leave us behind” narrative on its head and the implications are massive 😳 Here’s the wild part: They argue the safest and fastest path to superintelligence isn’t self-improving AI at all. It’s co-improvement humans and AI doing AI research together as a joint system. Not “AI replaces researchers.” Not “AI rewrites itself in the dark.” But AI that’s explicitly built to collaborate with humans on ideation, benchmarks, experiments, error analysis, alignment work, and system design. And when you read the details, it becomes obvious why this matters: → Self-improvement vs co-improvement as two completely different worlds: Self-improvement cuts humans out. Co-improvement creates a loop where humans improve the AI, the AI improves human research, and both sides climb together. → Table 1 on page 3 breaks down what “AI research collaboration” actually means: co-designing benchmarks co-running experiments co-debugging failures co-developing safety methods co-writing papers co-building infra It’s literally the full research pipeline, but shared. → Every current self-improvement technique (synthetic data, self-reward, self-play, NAS, etc.) has blind spots: reward hacking, drift, brittleness, missing human priors, zero transparency. Co-improvement sidesteps the failure modes by keeping humans in the reasoning loop. The core idea hits hard: Self-improving AI races ahead unsupervised. Co-improving AI drags humanity upward with it. And the bigger claim: Co-superintelligence isn’t “AI becoming superintelligent.” It’s humans + AI together becoming superintelligent — because both sides are learning, accumulating tacit knowledge, and iterating inside the same research cycle. If this paradigm sticks, the future isn’t “AGI vs humanity.” It’s a merged research organism. A collective intelligence. This paper feels like the clearest blueprint yet for an AI future that doesn’t end in an alignment knife-edge. It argues we don’t need to outrun superintelligence. We need to co-evolve with it. And honestly? It makes way more sense than the alternatives.

ChatGPT vs DeepSeek vs Gemini Which one makes the best-looking website UIs? I tested them with this prompt: "Build an ecommerce site for premium laptop and mobile accessories using HTML5." Here's the result: