
#438 – Elon Musk: Neuralink and the Future of Humanity
Lex Fridman Podcast
The Role of Compute, Data, and Post-Training in AI Systems
The effectiveness of AI systems hinges on a balance of compute power, data quality, and post-training efficiency. Compute serves as the engine driving performance, where greater horsepower can lead to superior outcomes regardless of operator skill. The efficiency of utilizing this training compute and conducting inference relies heavily on human talent. Access to unique and timely data boosts AI performance, with real-time information presenting a significant advantage. Tesla's Optimus robots are poised to become a primary source of data, leveraging their ability to gather information from the real world at an unprecedented scale. This capacity greatly surpasses the data collection methods of humans, emphasizing AI's potential to glean insights from practical, everyday interactions. The scale of data gathered by these robots can provide rich, contextual learning that is invaluable for AI development.