sinanuozdemir/oreilly-agi
Explore the evolution of AGI through historical context, reasoning models, and agent systems, while gaining hands-on experience with cutting-edge models like Claude 4, DeepSeek-R1, and OpenAI's o3. Learn to critically evaluate AGI benchmarks, understand their limitations, and identify where current models excel or struggle in reasoning tasks.
It provides practical guidance for integrating and extending AGI models, demonstrating how to add short-term memory to OpenAI agents and enable reasoning models to control a laptop. The project includes extensive benchmarking notebooks that run various AGI models against datasets like Humanity's Last Exam and MMLU, alongside case studies on applying reinforcement learning (GRPO) with models like Qwen. It also covers advanced prompt engineering techniques for DeepSeek-R1, leveraging few-shot learning and vector databases.
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Feb 11, 2026
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