Proprietary model builders are getting squeezed from both sides. In this AI on AIR cut from Redpoint AI’s interview, River AI co-founder and former @xai co-founder Igor Babuschkin explains why bigger models no longer guarantee a stronger moat: ▷ Training is hitting diminishing returns. Each step forward demands more GPUs, more high-quality data, and more effort. ▷ Frontier models may become too capable for labs to want, or be allowed, to release. ▷ Open models keep getting stronger, leaving proprietary builders less room to defend their lead. His conclusion: scale alone is not a way out. OpenAI, Anthropic, and other frontier labs need new ideas that make models more useful, open new domains, and create real impact. Capability gains may be slowing. The pressure to innovate is not. 🪁