RSI
RSI at Beyond Market Intelligence is a file of 2 stories. The newest of them: “Can next-token prediction truly evolve into open-ended intelligence?” and “Explore how current AI agents approach open-ended research challenges.”. Most conversations about AI assume AGI is inevitable, only debating what comes after. A new paper challenges a comforting assumption: recursive self-improvement isn't imminent because today's agents can't handle open-ended ML research. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every RSI story on Beyond Market Intelligence, newest first.
Can next-token prediction truly evolve into open-ended intelligence?
Most conversations about AI assume AGI is inevitable, only debating what comes after. But that skips the real question: can next-token prediction actually produce general intelligence? One Reddit user is asking for a mechanistic case grounded in computational learning theory and first principles, not trend lines. It's the right question. We don't need philosophical debates about definitions. We need to understand whether today's learning mechanisms can scale to open-ended intelligence.
Explore how current AI agents approach open-ended research challenges.
A new paper challenges a comforting assumption: recursive self-improvement isn't imminent because today's agents can't handle open-ended ML research. The researchers tested Codex, GPT-5.6 Sol, and OpenClaw against accepted but unpublished NeurIPS work, and the original authors graded the agents' efforts. They failed. That's a meaningful result, even if the conclusion feels like a relief. It suggests progress hinges on broader capabilities, not just scaling.