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Training 2x per week = produces excellent results with full recovery and maximum growth.Training 3x per week = often works but you’re leaving potential on the table by not allowing complete supercompensation.Training 4x per week = rarely optimal; recovery suffers and intensity drops.Training 5x or more = almost always a very dumb decision that leads to overtraining, stalled progress, and burnout.
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Karpathy's prediction about RL is coming true now!He called reward functions unreliable and argued that a single reward number is too low-dimensional to teach an agent what "good" means for complex tasks. To solve this, Agents need a knowledge-guided review as a higher-dimensional feedback channel.Every major AI lab trains models with RL today (OpenAI, Anthropic, DeepSeek).And their key bottleneck has always been the reward functions.GRPO by DeepSeek worked well for math and code because the env
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