OpenAI vs. DeepSeek Training: The $100M Dance Between ...
AI training isn’t alchemy — it’s a meticulously choreographed ballet of code and cognition. The real magic happens in the balance between human ingenuity and algorithmic brute force, a digital tightrope walk where every step matters. DeepSeek’s playlist is lean; OpenAI’s is a symphony. Both get the job done, but one burns a bigger hole in your pocket. DeepSeek R1 is making waves: it’s lean, efficient, and doesn’t throw money at every problem. But does that make it better?
Breaking Down AI Models’ Training Techniques
Let’s break down AI models’ training techniques, human vs. automated efforts, and most importantly — why DeepSeek’s approach is shaking things up. We’re going to talk about RLHF (or Reinforcement Learning from Human Feedback), Data Curation & Filtering, Hyperparameter Tuning, Fine-Tuning, Knowledge Distillation, Sparse Training & Mixture-of-Experts (MoE), Pruning, and more. Let’s get…
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AI models utilize various training techniques to enhance their performance. One such technique is Hyperparameter Tuning, which plays a crucial role in optimizing the model's parameters for quick and efficient decision-making.
