In this episode of ODSC’s Ai X Podcast, Jeff Boudier of Hugging Face joins us to discuss Hugging Face’s new “Hugs” service for deploying AI, among other new Hugging Face developments. He’ll also go into detail about fine-tuning for model performance, the evolution of AI agents, and the challenges faced when deploying AI models into production. Jeff Boudier is the Head of Product at Hugging Face, the #1 open platform for AI builders. Previously, Jeff was a co-founder of Stupeflix, acquired by GoPro, where he served as director of Product Management, Product Marketing, Business Development, and Corporate Development. Show Questions: - Details about Hugging Face’s new 'Hugs' service for deploying AI. - Hugging Face’s mission and how it is evolving with AI advancements. - How fine-tuning is helping enterprises improve model performance. - Gathering community feedback and managing fast-moving developments. - Staying ahead of rapid AI advancements in the open-source realm. - How Hugging Face is making it easier to fine-tune models. - Hugging Face’s support for Retrieval-Augmented Generation (RAG). - Challenges enterprises face when deploying AI models to production. - The evolution of AI agents alongside large language models. - Hugging Face’s integrations with other platforms and AI agents. - The importance of privacy in running AI models locally. - Concerns about models overfitting to academic benchmarks. - Shifting benchmarks toward real-world production performance. - Jeff’s upcoming session at ODSC West. - Where to follow Jeff Boudier and Hugging Face. Show Notes: - Jeff’s upcoming session at ODSC West, “How to Build Your Own AI with Open Source and Hugging Face”: https://odsc.com/speakers/how-to-build-your-own-ai-with-open-source-and-hugging-face/ - Jeff’s Twitter/X: https://x.com/jeffboudier - LinkedIn: https://www.linkedin.com/in/jeffboudier/ - HuggingChat: https://huggingface.co/chat/ - PEFT: State-of-the-art Parameter-Efficient Fine-Tuning: https://github.com/huggingface/peft - Hugging Face Spaces: https://huggingface.co/spaces - LLM Evaluation Guide: https://github.com/huggingface/evaluation-guidebook?tab=readme-ov-file - LoRA: Low-Rank Adaptation of Large Language Models: https://arxiv.org/abs/2106.09685 - DPO: Direct Preference Optimization: https://arxiv.org/abs/2305.18290 - Open LLM Leaderboard: https://huggingface.co/open-llm-leaderboard - LLM Guardrails: https://github.com/dottxt-ai/outlines This episode was sponsored by: Ai+ Training https://aiplus.training/ Home to hundreds of hours of on-demand, self-paced AI training, ODSC interviews, free webinars, and certifications in in-demand skills like LLMs and Prompt Engineering And created in partnership with ODSC https://odsc.com/ The Leading AI Training Conference, featuring expert-led, hands-on workshops, training sessions, and talks on cutting-edge AI topics and tools, from data science and machine learning to generative AI to LLMOps Never miss an episode, subscribe now!
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