An Agentic Mixture of Experts for DevOps with Sunil Mallya - #708

An Agentic Mixture of Experts for DevOps with Sunil Mallya - #708

Today we're joined by Sunil Mallya, CTO and co-founder of Flip AI. We discuss Flip’s incident debugging system for DevOps, which was built using a custom mixture of experts (MoE) large language model (LLM) trained on a novel "CoMELT" observability dataset which combines traditional MELT data—metrics, events, logs, and traces—with code to efficiently identify root failure causes in complex software systems. We discuss the challenges of integrating time-series data with LLMs and their multi-decoder architecture designed for this purpose. Sunil describes their system's agent-based design, focusing on clear roles and boundaries to ensure reliability. We examine their "chaos gym," a reinforcement learning environment used for testing and improving the system's robustness. Finally, we discuss the practical considerations of deploying such a system at scale in diverse environments and much more. The complete show notes for this episode can be found at https://twimlai.com/go/708.

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Mojo: A Supercharged Python for AI with Chris Lattner - #634

Mojo: A Supercharged Python for AI with Chris Lattner - #634

Today we’re joined by Chris Lattner, Co-Founder and CEO of Modular. In our conversation with Chris, we discuss Mojo, a new programming language for AI developers. Mojo is unique in this space and simp...

19 Juni 202357min

Stable Diffusion and LLMs at the Edge with Jilei Hou - #633

Stable Diffusion and LLMs at the Edge with Jilei Hou - #633

Today we’re joined by Jilei Hou, a VP of Engineering at Qualcomm Technologies. In our conversation with Jilei, we focus on the emergence of generative AI, and how they've worked towards providing thes...

12 Juni 202340min

Modeling Human Behavior with Generative Agents with Joon Sung Park - #632

Modeling Human Behavior with Generative Agents with Joon Sung Park - #632

Today we’re joined by Joon Sung Park, a PhD Student at Stanford University. Joon shares his passion for creating AI systems that can solve human problems and his work on the recent paper Generative Ag...

5 Juni 202346min

Towards Improved Transfer Learning with Hugo Larochelle - #631

Towards Improved Transfer Learning with Hugo Larochelle - #631

Today we’re joined by Hugo Larochelle, a research scientist at Google Deepmind. In our conversation with Hugo, we discuss his work on transfer learning, understanding the capabilities of deep learning...

29 Maj 202338min

Language Modeling With State Space Models with Dan Fu - #630

Language Modeling With State Space Models with Dan Fu - #630

Today we’re joined by Dan Fu, a PhD student at Stanford University. In our conversation with Dan, we discuss the limitations of state space models in language modeling and the search for alternative b...

22 Maj 202328min

Building Maps and Spatial Awareness in Blind AI Agents with Dhruv Batra - #629

Building Maps and Spatial Awareness in Blind AI Agents with Dhruv Batra - #629

Today we continue our coverage of ICLR 2023 joined by Dhruv Batra, an associate professor at Georgia Tech and research director of the Fundamental AI Research (FAIR) team at META. In our conversation,...

15 Maj 202343min

AI Agents and Data Integration with GPT and LLaMa with Jerry Liu - #628

AI Agents and Data Integration with GPT and LLaMa with Jerry Liu - #628

Today we’re joined by Jerry Liu, co-founder and CEO of Llama Index. In our conversation with Jerry, we explore the creation of Llama Index, a centralized interface to connect your external data with t...

8 Maj 202341min

Hyperparameter Optimization through Neural Network Partitioning with Christos Louizos - #627

Hyperparameter Optimization through Neural Network Partitioning with Christos Louizos - #627

Today we kick off our coverage of the 2023 ICLR conference joined by Christos Louizos, an ML researcher at Qualcomm Technologies. In our conversation with Christos, we explore his paper Hyperparameter...

1 Maj 202333min

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