Today we kick off our coverage of the 2023 CVPR conference joined by Fatih Porikli, a Senior Director of Technology at Qualcomm. In our conversation with Fatih, we covered quite a bit of ground, touching on a total of 12 papers/demos, focusing on topics like data augmentation and optimized architectures for computer vision. We explore advances in optical flow estimation networks, cross-model, and stage knowledge distillation for efficient 3D object detection, and zero-shot learning via language models for fine-grained labeling. We also discuss generative AI advancements and computer vision optimization for running large models on edge devices. Finally, we discuss objective functions, architecture design choices for neural networks, and efficiency and accuracy improvements in AI models via the techniques introduced in the papers.
Controlling Fusion Reactor Instability with Deep Reinforcement Learning with Aza Jalalvand - #682
GraphRAG: Knowledge Graphs for AI Applications with Kirk Marple - #681
Teaching Large Language Models to Reason with Reinforcement Learning with Alex Havrilla - #680
Localizing and Editing Knowledge in LLMs with Peter Hase - #679
Coercing LLMs to Do and Reveal (Almost) Anything with Jonas Geiping - #678
V-JEPA, AI Reasoning from a Non-Generative Architecture with Mido Assran - #677
Video as a Universal Interface for AI Reasoning with Sherry Yang - #676
Assessing the Risks of Open AI Models with Sayash Kapoor - #675
OLMo: Everything You Need to Train an Open Source LLM with Akshita Bhagia - #674
Training Data Locality and Chain-of-Thought Reasoning in LLMs with Ben Prystawski - #673
Reasoning Over Complex Documents with DocLLM with Armineh Nourbakhsh - #672
Are Emergent Behaviors in LLMs an Illusion? with Sanmi Koyejo - #671
AI Trends 2024: Reinforcement Learning in the Age of LLMs with Kamyar Azizzadenesheli - #670
Building and Deploying Real-World RAG Applications with Ram Sriharsha - #669
Nightshade: Data Poisoning to Fight Generative AI with Ben Zhao - #668
Learning Transformer Programs with Dan Friedman - #667
AI Trends 2024: Machine Learning & Deep Learning with Thomas Dietterich - #666
AI Trends 2024: Computer Vision with Naila Murray - #665
Are Vector DBs the Future Data Platform for AI? with Ed Anuff - #664
Quantizing Transformers by Helping Attention Heads Do Nothing with Markus Nagel - #663
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