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The historical context of deep learning provides important insights into this challenge. Successful AI milestones, like DeepMind's AlphaGo, relied heavily on curated datasets obtained from numerous human games, which facilitated its learning process. This illustrates the critical dependency on robust data collection methods.
Implications of Deep Seek’s Model for Tesla
Deep Seek's advancements primarily revolve around improving the efficiency of training neural networks and executing inference tasks. They have established groundbreaking methodologies for both, which could hold exciting potential for improving Tesla's systems. The ability to conduct more efficient inference directly impacts how well hardware can execute complex algorithms swiftly and with minimal power consumption.