What If A.I. Doesn't Get Better Than This?
11 days ago
- #AI
- #Scaling Laws
- #GPT-5
- OpenAI's 2020 paper 'Scaling Laws for Neural Language Models' suggested that larger language models improve performance aggressively, leading to GPT-3's success.
- Initial optimism about AI scaling laws led to predictions of rapid progress toward artificial general intelligence (AGI), but progress slowed after GPT-4.
- Post-training improvements became the new focus for AI companies after scaling laws showed diminishing returns, refining models like GPT-5 and Claude 4.
- GPT-5's release was met with mixed reviews, showing improvements in coding and reasoning but also limitations and underwhelming performance in some tasks.
- Critics argue that AI's economic impact may be overhyped, with some predicting a $50-100 billion market rather than a trillion-dollar revolution.
- Despite skepticism, AI continues to advance steadily, with potential disruptions in fields like programming and academia, but not necessarily massive job market upheaval.
- The AI industry's shift from scaling to post-training reflects a broader uncertainty about the future of AI development and its societal impact.