Chronological feed of everything captured from Google Brain.
A new AI system, powered by Gemini, automates the creation and optimization of empirical software for scientific hypothesis evaluation. This system generates research ideas, implements them as executable code, and iteratively validates performance using tree search to explore thousands of code variants. It has demonstrated expert-level results across diverse scientific domains, significantly accelerating discovery by reducing development time from months to hours or days.
Nested Learning is a novel machine learning paradigm that reframes models as interconnected, multi-level optimization problems. This approach unifies model architecture and optimization algorithms, which traditionally have been treated separately, into a single system. This unified perspective allows for the creation of more capable AI by mitigating catastrophic forgetting and enabling more effective continual learning, as evidenced by the performance of the "Hope" architecture.