Scholars Debate Scaling Laws: Are Models Less General Despite Growing Stronger?
davidmanheim · x · 2026-07-31
A recent discussion on X has sparked debate over whether AI progress is hitting a wall. @arannayebi shared and commented on a bearish take by @RealAdamHunt.
@RealAdamHunt argued that the thesis of achieving broad new capabilities simply by scaling up models is flawed, observing that recent models have become less general, with degraded language outputs. In contrast, @arannayebi suggested this is a statement about pretraining data rather than the underlying methods (like RL and SSL), which remain sufficiently general.
More from AGI Musings
- Frequent AI Lab Founder Departures: Three Lessons for Aspiring Entrepreneurs — nathanbenaich · 2026-07-31
- Slate Essay: AI Writing Detectors Are Sparking a New Wave of False Accusations — ArtificialOther · 2026-07-31
- Cognitive Scientist Debates: Can AI Truly Understand Without a Vulnerable Body? — rp_tiago · 2026-07-31
- Is the Brain a Computer? Cognitive Scientist Argues Computation Doesn't Equal Mind — rp_tiago · 2026-07-31
- Altman on AGI Wealth: Cluster Owners Take the Lion's Share — r0ck3t23 · 2026-07-31
- KOL Predicts AGI by 2027-28, Citing Recursive Self-Improvement — haider1 · 2026-07-31