Reflections on AI at the End of 2025
13 hours ago
- #AI
- #LLMs
- #Future of Technology
- AI researchers previously claimed LLMs were stochastic parrots without meaning representation, but by 2025, this view largely faded.
- Chain of Thought (CoT) improves LLM output by enabling internal search and reinforcement learning for better token sequencing.
- Reinforcement learning with verifiable rewards has removed the scaling limit tied to token count, hinting at future breakthroughs.
- Programmers increasingly accept AI-assisted programming due to LLMs' improved code generation, despite occasional errors.
- Some AI scientists explore alternatives to Transformers, while others believe LLMs can achieve AGI without new paradigms.
- CoT hasn't fundamentally changed LLMs' architecture; they still operate on a next-token prediction basis.
- The ARC test, once seen as anti-LLM, now validates LLMs' capabilities, with models performing well on ARC-AGI tasks.
- The primary AI challenge for the next two decades is preventing extinction.