Part 10/12:
Looking forward, Chi foresees a landscape of specialized, efficient models tailored for discrete tasks—potentially replacing monolithic giants for specific workflows. He emphasizes the importance of cost efficiency, capability expansion, and system robustness in scaling autonomous agent platforms.
He points out that the exponential progress of the past year—from GPT-3 to GPT-4—demonstrates the rapid pace of AI evolution, which makes maintaining flexibility and modularity crucial. The ongoing development of smaller, specialized language models, combined with larger general models, promises a future where AI agents are more capable, adaptable, and cost-effective.