Today we continue our AI Trends 2024 series with a conversation with Thomas Dietterich, distinguished professor emeritus at Oregon State University. As you might expect, Large Language Models figured prominently in our conversation, and we covered a vast array of papers and use cases exploring current research into topics such as monolithic vs. modular architectures, hallucinations, the application of uncertainty quantification (UQ), and using RAG as a sort of memory module for LLMs. Lastly, don’t miss Tom’s predictions on what he foresees happening this year as well as his words of encouragement for those new to the field.
The complete show notes for this episode can be found at twimlai.com/go/666.
Enabling Clinical Automation: From Research to Deployment with Devin Singh - #428
Pixels to Concepts with Backpropagation w/ Roland Memisevic - #427
Fighting Global Health Disparities with AI w/ Jon Wang - #426
Accessibility and Computer Vision - #425
NLP for Equity Investing with Frank Zhao - #424
The Future of Education and AI with Salman Khan - #423
Why AI Innovation and Social Impact Go Hand in Hand with Milind Tambe - #422
What's Next for Fast.ai? w/ Jeremy Howard - #421
Feature Stores for MLOps with Mike del Balso - #420
Exploring Causality and Community with Suzana Ilić - #419
Decolonizing AI with Shakir Mohamed - #418
Spatial Analysis for Real-Time Video Processing with Adina Trufinescu
How Deep Learning has Revolutionized OCR with Cha Zhang - #416
Machine Learning for Food Delivery at Global Scale - #415
Open Source at Qualcomm AI Research with Jeff Gehlhaar and Zahra Koochak - #414
Visualizing Climate Impact with GANs w/ Sasha Luccioni - #413
ML-Powered Language Learning at Duolingo with Burr Settles - #412
Bridging The Gap Between Machine Learning and the Life Sciences with Artur Yakimovich - #411
Understanding Cultural Style Trends with Computer Vision w/ Kavita Bala - #410
That's a VIBE: ML for Human Pose and Shape Estimation with Nikos Athanasiou, Muhammed Kocabas, Michael Black - #409
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