Is Fine Tuning Models Still a Waste of Time?
📋 Summary
What are the limitations of fine tuning AI models like Open AI’s GPT 4o? Today we explore new studies on fine tuning’s effect on model accuracy and hallucinations. We also preview innovative new RAG capabilities, including context caching, and their potential to transform AI development. Lastly, we touch on the influence of hype in machine learning and its various impacts on the field.
🔗 Show Links:
Previous video on Fine Tuning - • Fine Tuning ChatGPT is a Waste of You...
Fine Tuning Hallucinations paper - https://arxiv.org/abs/2405.05904
Anthropic Study - https://www.anthropic.com/news/mappin...
Anthropic Cache - https://docs.anthropic.com/en/docs/bu...
Gemini Caching - https://ai.google.dev/gemini-api/docs...
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🚩 Chapters
00:00 Introduction to Fine Tuning
00:43 New Studies on Fine Tuning
04:46 Mapping the LLM's Brain
07:43 Revolutionary RAG Capabilities
14:22 The Hype in Machine Learning
18:28 Conclusion and Final Thoughts
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