Beyond Raw Power: AI's Three Crucial Frontiers

Michael Gerstenhaber, VP at Google Cloud, identifies three critical frontiers in AI development: raw intelligence, response time, and cost-effective scalability. He explains that while intelligence is vital for complex tasks like code generation, rapid response times are essential for interactive applications such as customer support. The third frontier, cost, becomes a deciding factor for deploying AI at massive, unpredictable scales, as seen in large-scale content moderation.

Gerstenhaber observes that the widespread adoption of agentic AI systems is progressing slower than expected due to a lack of essential infrastructure. Key challenges include establishing patterns for auditing agent actions and authorizing data access. He notes that production environments, which are always a trailing indicator of technological capability, require more development time for these patterns to mature.

He also highlights Google's unique advantage in vertical integration, encompassing everything from data centers and custom chips to AI models and inference layers. This comprehensive control allows Google to build and deploy AI solutions more effectively. Gerstenhaber suggests that developing robust, low-risk implementation patterns, similar to those used in software engineering, is necessary for agentic AI to gain broader traction across various professions.