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.

Episoder(780)

Explainable AI for Biology and Medicine with Su-In Lee - #642

Explainable AI for Biology and Medicine with Su-In Lee - #642

Today we’re joined by Su-In Lee, a professor at the Paul G. Allen School of Computer Science And Engineering at the University Of Washington. In our conversation, Su-In details her talk from the ICML ...

14 Aug 202338min

Transformers On Large-Scale Graphs with Bayan Bruss - #641

Transformers On Large-Scale Graphs with Bayan Bruss - #641

Today we’re joined by Bayan Bruss, Vice President of Applied ML Research at Capital One. In our conversation with Bayan, we covered a pair of papers his team presented at this year’s ICML conference. ...

7 Aug 202338min

The Enterprise LLM Landscape with Atul Deo - #640

The Enterprise LLM Landscape with Atul Deo - #640

Today we’re joined by Atul Deo, General Manager of Amazon Bedrock. In our conversation with Atul, we discuss the process of training large language models in the enterprise, including the pain points ...

31 Jul 202337min

BloombergGPT - an LLM for Finance with David Rosenberg - #639

BloombergGPT - an LLM for Finance with David Rosenberg - #639

Today we’re joined by David Rosenberg, head of the machine learning strategy team in the Office of the CTO at Bloomberg. In our conversation with David, we discuss the creation of BloombergGPT, a cust...

24 Jul 202336min

Are LLMs Good at Causal Reasoning? with Robert Osazuwa Ness - #638

Are LLMs Good at Causal Reasoning? with Robert Osazuwa Ness - #638

Today we’re joined by Robert Osazuwa Ness, a senior researcher at Microsoft Research, Professor at Northeastern University, and Founder of Altdeep.ai. In our conversation with Robert, we explore wheth...

17 Jul 202348min

Privacy vs Fairness in Computer Vision with Alice Xiang - #637

Privacy vs Fairness in Computer Vision with Alice Xiang - #637

Today we’re joined by Alice Xiang, Lead Research Scientist at Sony AI, and Global Head of AI Ethics at Sony Group Corporation. In our conversation with Alice, we discuss the ongoing debate between pri...

10 Jul 202337min

Unifying Vision and Language Models with Mohit Bansal - #636

Unifying Vision and Language Models with Mohit Bansal - #636

Today we're joined by Mohit Bansal, Parker Professor, and Director of the MURGe-Lab at UNC, Chapel Hill. In our conversation with Mohit, we explore the concept of unification in AI models, highlightin...

3 Jul 202348min

Data Augmentation and Optimized Architectures for Computer Vision with Fatih Porikli - #635

Data Augmentation and Optimized Architectures for Computer Vision with Fatih Porikli - #635

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, touch...

26 Jun 202352min

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