- Search Transforms AI Capability: Integrating search into foundation models like GPT-4 can revolutionize their performance and utility, surpassing current limitations.
- Evidence from Chess AI: The evolution of chess engines, like Leela Chess Zero and Stockfish, demonstrates the profound impact of search on AI effectiveness.
- Immediate Applications: Search-enabled AI can automate research, offering near-term superintelligent capabilities without waiting for massive model scaling.
Impact
- Accelerated AI Research: Search can enable foundation models to conduct AI research autonomously, speeding up advancements.
- Improved AI Efficiency: Targeted compute allocation with search allows for more efficient use of resources, reducing the need for larger models.
- Broader AI Applications: Enhanced AI models can be applied immediately to critical fields like drug discovery, optimizing R&D processes.
- Economic Upside: Companies can achieve superintelligent capabilities today by investing in inference compute, bypassing the need for future massive model scaling.
- Self-Improving AI: Search-driven AI can iteratively improve its algorithms, leading to exponential advancements in AI capabilities.
Eksentricity 
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