The Thing
The Thing
Madisen and Renee @ The Thing
Episode 1- Efficient LLM training with Unsloth.ai Co-Founder
19 minutes Posted Jan 31, 2024 at 12:12 pm.
Introduction to the Podcast
Understanding Unsloth: The AI Training System
Daniel's Journey from NVIDIA to Unsloth
The Power of OpenAI's Triton Language
The Magic Behind Unsloth's Fine-Tuning Process
Community Engagement and Use Cases of Unsloth
Working with Family in the AI Space
The Role of Autonomous Agents in AI Development
Challenges of Using Language Models for Math
Unsloth's Vision for Democratizing AI
Misconceptions and Best Practices in Working with LLMs
Understanding Retrieval Augmented Generation (RAG)
Staying Updated in the AI Space
Supporting Unsloth's Open Source Initiative
Conclusion: The Future of AI with Unsloth
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Show notes
Episode 1!!!
Today we chat about AI Training with (un)Supervised Learning and Daniel from Unsloth.ai
The good stuff- Unsloth
https://www.unsloth.ai
https://ko-fi.com/unsloth
https://github.com/unslothai
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.
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