Category: Machine Learning
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GPT-5: Peak or Plateau? A Literature Review of Progress in Large Language Models
Is GPT-5 a revolutionary step toward greater AI intelligence, or a sign of diminishing returns in scaling large language models? This work presents a comprehensive analysis of literature and reports from the last several years to answer that question. We review the development from GPT-3 through GPT-4 and into GPT-5, highlighting how earlier leaps in…
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“Compute as Teacher”: How AI Models Learn by Teaching Themselves
One of the big challenges in training AI language models is the need for high-quality supervision — in other words, showing the model what the “right” answers look like. Traditionally, this is done with large datasets of human-written answers or by having humans provide feedback on the AI’s outputs (as in Reinforcement Learning from Human Feedback, RLHF).…