Episode 1!!! š
Today we chat about AI Training with (un)Supervised Learning and Daniel from Unsloth.ai
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The good stuff- Unsloth
ā https://www.unsloth.aiā
ā https://ko-fi.com/unslothā
ā https://github.com/unslothaiā
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In this episode of Unsupervised Learning, host Renee interviews Daniel, the co-founder of Unsloth, an AI training system that fine-tunes language models 30 times faster. They discuss Daniel's beginnings at Nvidia, his passion for making AI accessible and efficient, and his ultimate vision of creating a personal ChatGPT for everyone that operates on local machines. Daniel explains the concept of Retrieval Augmented Generation (RAG) as a knowledge injection system and elaborates on the current uses and future plans for Unsloth. The episode also touches on the issues with representing maths in language models and the misconceptions people have about working with large language models.
Have something to say? feedback, love notes or recommend a mate to join the pod @ [email protected]
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00:00 Introduction to the Podcast
00:26 Understanding Unsloth: The AI Training System
00:58 Daniel's Journey from NVIDIA to Unsloth
02:15 The Power of OpenAI's Triton Language
02:38 The Magic Behind Unsloth's Fine-Tuning Process
03:42 Community Engagement and Use Cases of Unsloth
05:03 Working with Family in the AI Space
05:35 The Role of Autonomous Agents in AI Development
06:57 Challenges of Using Language Models for Math
09:03 Unsloth's Vision for Democratizing AI
09:56 Misconceptions and Best Practices in Working with LLMs
14:21 Understanding Retrieval Augmented Generation (RAG)
17:29 Staying Updated in the AI Space
18:26 Supporting Unsloth's Open Source Initiative
19:29 Conclusion: The Future of AI with Unsloth
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