Building with continuously trainable AI, Alternative to Pre-trained Deep Learning – Ali Al Ebrahim

Описание к видео Building with continuously trainable AI, Alternative to Pre-trained Deep Learning – Ali Al Ebrahim

Session presented during the Virtual AI Safety Unconference 2024

Speaker: Ali Al Ebrahim

Session Description: Presented by aolabs.ai | AI systems struggle with edge cases and understanding local context despite increasing model sizes. From our research at UC Berkeley into the evolution of intelligence from simple organisms, we’ve discovered the missing link is continuous learning. Models built with our framework learn through customizable parameters similar to animal instincts, allowing for AI grounded with built-in memory and reasoning. We’ve grown to a community of 160+ developers and researchers building general intelligence from the bottom-up from places like Berkeley, NYU, Imperial College, and Google.

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