Energy Star Ratings for AI Models with Sasha Luccioni - #687

Energy Star Ratings for AI Models with Sasha Luccioni - #687

Today, we're joined by Sasha Luccioni, AI and Climate lead at Hugging Face, to discuss the environmental impact of AI models. We dig into her recent research into the relative energy consumption of general purpose pre-trained models vs. task-specific, non-generative models for common AI tasks. We discuss the implications of the significant difference in efficiency and power consumption between the two types of models. Finally, we explore the complexities of energy efficiency and performance benchmarking, and talk through Sasha’s recent initiative, Energy Star Ratings for AI Models, a rating system designed to help AI users select and deploy models based on their energy efficiency. The complete show notes for this episode can be found at http://twimlai.com/go/687.

Episoder(783)

Chronos: Learning the Language of Time Series with Abdul Fatir Ansari - #685

Chronos: Learning the Language of Time Series with Abdul Fatir Ansari - #685

Today we're joined by Abdul Fatir Ansari, a machine learning scientist at AWS AI Labs in Berlin, to discuss his paper, "Chronos: Learning the Language of Time Series." Fatir explains the challenges of...

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Powering AI with the World's Largest Computer Chip with Joel Hestness - #684

Powering AI with the World's Largest Computer Chip with Joel Hestness - #684

Today we're joined by Joel Hestness, principal research scientist and lead of the core machine learning team at Cerebras. We discuss Cerebras’ custom silicon for machine learning, Wafer Scale Engine 3...

13 Mai 202455min

AI for Power & Energy with Laurent Boinot - #683

AI for Power & Energy with Laurent Boinot - #683

Today we're joined by Laurent Boinot, power and utilities lead for the Americas at Microsoft, to discuss the intersection of AI and energy infrastructure. We discuss the many challenges faced by curre...

7 Mai 202449min

Controlling Fusion Reactor Instability with Deep Reinforcement Learning with Aza Jalalvand - #682

Controlling Fusion Reactor Instability with Deep Reinforcement Learning with Aza Jalalvand - #682

Today we're joined by Azarakhsh (Aza) Jalalvand, a research scholar at Princeton University, to discuss his work using deep reinforcement learning to control plasma instabilities in nuclear fusion rea...

29 Apr 202442min

GraphRAG: Knowledge Graphs for AI Applications with Kirk Marple - #681

GraphRAG: Knowledge Graphs for AI Applications with Kirk Marple - #681

Today we're joined by Kirk Marple, CEO and founder of Graphlit, to explore the emerging paradigm of "GraphRAG," or Graph Retrieval Augmented Generation. In our conversation, Kirk digs into the GraphRA...

22 Apr 202447min

Teaching Large Language Models to Reason with Reinforcement Learning with Alex Havrilla - #680

Teaching Large Language Models to Reason with Reinforcement Learning with Alex Havrilla - #680

Today we're joined by Alex Havrilla, a PhD student at Georgia Tech, to discuss "Teaching Large Language Models to Reason with Reinforcement Learning." Alex discusses the role of creativity and explora...

16 Apr 202446min

Localizing and Editing Knowledge in LLMs with Peter Hase - #679

Localizing and Editing Knowledge in LLMs with Peter Hase - #679

Today we're joined by Peter Hase, a fifth-year PhD student at the University of North Carolina NLP lab. We discuss "scalable oversight", and the importance of developing a deeper understanding of how ...

8 Apr 202449min

Coercing LLMs to Do and Reveal (Almost) Anything with Jonas Geiping - #678

Coercing LLMs to Do and Reveal (Almost) Anything with Jonas Geiping - #678

Today we're joined by Jonas Geiping, a research group leader at the ELLIS Institute, to explore his paper: "Coercing LLMs to Do and Reveal (Almost) Anything". Jonas explains how neural networks can be...

1 Apr 202448min

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