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.

Avsnitt(778)

Accelerating AI Training and Inference with AWS Trainium2 with Ron Diamant - #720

Accelerating AI Training and Inference with AWS Trainium2 with Ron Diamant - #720

Today, we're joined by Ron Diamant, chief architect for Trainium at Amazon Web Services, to discuss hardware acceleration for generative AI and the design and role of the recently released Trainium2 c...

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π0: A Foundation Model for Robotics with Sergey Levine - #719

π0: A Foundation Model for Robotics with Sergey Levine - #719

Today, we're joined by Sergey Levine, associate professor at UC Berkeley and co-founder of Physical Intelligence, to discuss π0 (pi-zero), a general-purpose robotic foundation model. We dig into the m...

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AI Trends 2025: AI Agents and Multi-Agent Systems with Victor Dibia - #718

AI Trends 2025: AI Agents and Multi-Agent Systems with Victor Dibia - #718

Today we’re joined by Victor Dibia, principal research software engineer at Microsoft Research, to explore the key trends and advancements in AI agents and multi-agent systems shaping 2025 and beyond....

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Speculative Decoding and Efficient LLM Inference with Chris Lott - #717

Speculative Decoding and Efficient LLM Inference with Chris Lott - #717

Today, we're joined by Chris Lott, senior director of engineering at Qualcomm AI Research to discuss accelerating large language model inference. We explore the challenges presented by the LLM encodin...

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Ensuring Privacy for Any LLM with Patricia Thaine - #716

Ensuring Privacy for Any LLM with Patricia Thaine - #716

Today, we're joined by Patricia Thaine, co-founder and CEO of Private AI to discuss techniques for ensuring privacy, data minimization, and compliance when using 3rd-party large language models (LLMs)...

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AI Engineering Pitfalls with Chip Huyen - #715

AI Engineering Pitfalls with Chip Huyen - #715

Today, we're joined by Chip Huyen, independent researcher and writer to discuss her new book, “AI Engineering.” We dig into the definition of AI engineering, its key differences from traditional machi...

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Evolving MLOps Platforms for Generative AI and Agents with Abhijit Bose - #714

Evolving MLOps Platforms for Generative AI and Agents with Abhijit Bose - #714

Today, we're joined by Abhijit Bose, head of enterprise AI and ML platforms at Capital One to discuss the evolution of the company’s approach and insights on Generative AI and platform best practices....

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Why Agents Are Stupid & What We Can Do About It with Dan Jeffries - #713

Why Agents Are Stupid & What We Can Do About It with Dan Jeffries - #713

Today, we're joined by Dan Jeffries, founder and CEO of Kentauros AI to discuss the challenges currently faced by those developing advanced AI agents. We dig into how Dan defines agents and distinguis...

16 Dec 20241h 8min

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