🎥 Random Samples
Random Samples is a weekly seminar series that airs live on our Red Hat YouTube page.
📹 Grounding Feedback is All You Need: Aligning Small Vision-Language Models
👤 Speaker: Giorgio Giannone
📹 On scalable RL in the era of agentic LLMs
👤 Speaker: Aldo Pareja
📹 LLM Meets Cache: From Application to Architecture
👤 Speaker: Shuhang Lin
📹 Accelerating LLM Knowledge Learning and Unlearning Research via Unified Frameworks
👤 Speaker: Wenlong Zhao
📹 Towards Combinatorial Interpretability of Neural Computation
👤 Speaker: Nir Shavit
📹 Synthetic Data Generation via SDG-Hub
👥 Speakers: Abhishek Bhandwaldar, Shivchander Sudalairaj, Akash Srivastava
📹 Continual Post-Training
👥 Speakers: Nikhil Nayak, Krishnateja Killamsetty
📹 State of LLM Compression from Research to Production
👤 Speaker: Mark Kurtz
🎙️ No Math AI
No Math AI is a monthly podcast designed for the AI community and enthusiasts who want to better understand how AI research translates into real-world business impact—without the complex equations.
Hosted by Dr. Akash Srivastava (Red Hat) and Isha Puri (MIT), this series distills critical AI concepts into practical takeaways to help practitioners, businesses, and curious minds accelerate adoption with confidence.
📹 Inference Time Scaling for Enterprises
👥 Guests: Matt Hicks (Red Hat CEO), Chris Wright (Red Hat CTO)
📹 Generative Optimization in Engineering Design
👤 Guest: Dr. Faez Ahmed
📹 Inference-time scaling: How small models beat the big ones
👥 Guests: Shivchander Sudalairaj, GX Xu, Kai Xu