AI Portfolio Podcast
The AI Portfolio Podcast showcases Experts, Companies, and Communities that can accelerate your journey of taking machine learning products to market.
If you are a practitioner, investor, or data leader, you will get something from the show by becoming exposed to great companies to invest in or join and learn how experts navigate their careers.
My goal is to open doors and increase your sense of the possibility of what can be done with machine learning. Connect with me, share the show, and let me know how I can add value.
AI Portfolio Podcast
Mike Tamir: LLM for Teams, RAG, Leadership and Enterprise vs Open Source LLMs - AI Portfolio
In this episode, Mike shares his extensive expertise in building and leading high-performance machine learning teams, delivering cutting-edge data products, and leveraging state-of-the-art technologies for various real-world applications. His contributions in text comprehension using large language models (LLMs), image recognition, Graph Neural Networks (GNNs), learned representation-based recommender systems, targeted advertising, time series forecasting, user understanding, and customer analytics are nothing short of awe-inspiring.
📲 Mike Tamir Socials:
LinkedIn: https://www.linkedin.com/in/miketamir/
Twitter: https://twitter.com/MikeTamir
📲 Mark Moyou, PhD Socials:
LinkedIn: https://www.linkedin.com/in/markmoyou/
Twitter: https://twitter.com/MarkMoyou
📗 Chapters
00:00 Inro
02:29 Shift in LLM Paradigm
08:50 First Impression of ChatGPT
15:00 LLM Fad
21:00 Mastering LLM
26:48 Test & Evaluation
35:08 Hallucinations
37:40 Retrieval-Augmented Generation (RAG)
40:41 Large vs Small Model & Enterprise vs Open Source Models
52:44 LLM Strategy for Teams
58:01 Evolution of Instructions tailored towards agent
59:52 Prediction Hypothesis
01:01:52 Startup
01:09:50 Advice for VCs
01:13:12 Differences in Data Science Culture
01:16:38 Approach for Leading Teams
01:18:18 Reading
01:19:20 Succeeding as a Team
01:21:07 Small vs Big Teams
01:23:06 What makes you really good at your job?
01:25:52 PhD and Teaching
01:31:22 Research Papers
01:32:35 Career Optimization Function
01:34:45 Book Recommendations
01:37:15 Rapid Round