Best Shirley Lin Podcasts (2025)

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Inside Nano Banana 🍌 and the Future of Vision-Language Models with Oliver Wang - #748 1:03:39

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1d ago1:03:39

1:03:39

Today, we’re joined by Oliver Wang, principal scientist at Google DeepMind and tech lead for Gemini 2.5 Flash Image—better known by its code name, “Nano Banana.” We dive into the development and capabilities of this newly released frontier vision-language model, beginning with the broader shift from specialized image generators to general-purpose m…

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S5E2 Reflections on Failing then Passing the NAVLE with Dr Nicole Iarusci 24:54

2d ago24:54

24:54

Join Dr Shannon Gowland as she chats with OVC Graduate Dr Nicole Iarusci. Nicole shares her insights about the challenging experience of failing the NAVLE exam, finding the support and inspiration to start studying again and the approach she used to pass on her second attempt. It is a reassuring listen for anyone who has worried about failing the e…

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Is It Time to Rethink LLM Pre-Training? with Aditi Raghunathan - #747 58:26

8d ago58:26

58:26

Today, we're joined by Aditi Raghunathan, assistant professor at Carnegie Mellon University, to discuss the limitations of LLMs and how we can build more adaptable and creative models. We dig into her ICML 2025 Outstanding Paper Award winner, “Roll the dice & look before you leap: Going beyond the creative limits of next-token prediction,” which ex…

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Building an Immune System for AI Generated Software with Animesh Koratana - #746 1:05:11

16d ago1:05:11

1:05:11

Today, we're joined by Animesh Koratana, founder and CEO of PlayerZero to discuss his team’s approach to making agentic and AI-assisted coding tools production-ready at scale. Animesh explains how rapid advances in AI-assisted coding have created an “asymmetry” where the speed of code output outpaces the maturity of processes for maintenance and su…

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S5E1 Canine Mast Cell Tumors with Dr. Paul Woods 58:21

16d ago58:21

58:21

Welcome back to a new season of Vet Sessions! Thank you listeners for continuing to support us, we can't believe we are starting Season 5! This week, we are joined by special guest Dr. Paul Woods, a leading veterinary oncologist and professor at the Ontario Veterinary College. A graduate of the Ontario Veterinary College, Dr. Woods has built an imp…

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Autoformalization and Verifiable Superintelligence with Christian Szegedy - #745 1:11:48

23d ago1:11:48

1:11:48

In this episode, Christian Szegedy, Chief Scientist at Morph Labs, joins us to discuss how the application of formal mathematics and reasoning enables the creation of more robust and safer AI systems. A pioneer behind concepts like the Inception architecture and adversarial examples, Christian now focuses on autoformalization—the AI-driven process …

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Multimodal AI Models on Apple Silicon with MLX with Prince Canuma - #744 1:10:20

1M ago1:10:20

1:10:20

Today, we're joined by Prince Canuma, an ML engineer and open-source developer focused on optimizing AI inference on Apple Silicon devices. Prince shares his journey to becoming one of the most prolific contributors to Apple’s MLX ecosystem, having published over 1,000 models and libraries that make open, multimodal AI accessible and performant on …

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Genie 3: A New Frontier for World Models with Jack Parker-Holder and Shlomi Fruchter - #743 1:01:01

1M ago1:01:01

1:01:01

Today, we're joined by Jack Parker-Holder and Shlomi Fruchter, researchers at Google DeepMind, to discuss the recent release of Genie 3, a model capable of generating “playable” virtual worlds. We dig into the evolution of the Genie project and review the current model’s scaled-up capabilities, including creating real-time, interactive, and high-re…

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Closing the Loop Between AI Training and Inference with Lin Qiao - #742 1:01:11

1M ago1:01:11

1:01:11

In this episode, we're joined by Lin Qiao, CEO and co-founder of Fireworks AI. Drawing on key lessons from her time building PyTorch, Lin shares her perspective on the modern generative AI development lifecycle. She explains why aligning training and inference systems is essential for creating a seamless, fast-moving production pipeline, preventing…

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Context Engineering for Productive AI Agents with Filip Kozera - #741 46:01

2M ago46:01

46:01

In this episode, Filip Kozera, founder and CEO of Wordware, explains his approach to building agentic workflows where natural language serves as the new programming interface. Filip breaks down the architecture of these "background agents," explaining how they use a reflection loop and tool-calling to execute complex tasks. He discusses the current…

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Infrastructure Scaling and Compound AI Systems with Jared Quincy Davis - #740 1:13:02

2M ago1:13:02

1:13:02

In this episode, Jared Quincy Davis, founder and CEO at Foundry, introduces the concept of "compound AI systems," which allows users to create powerful, efficient applications by composing multiple, often diverse, AI models and services. We discuss how these "networks of networks" can push the Pareto frontier, delivering results that are simultaneo…

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Building Voice AI Agents That Don’t Suck with Kwindla Kramer - #739 1:13:02

2M ago1:13:02

1:13:02

In this episode, Kwindla Kramer, co-founder and CEO of Daily and creator of the open source Pipecat framework, joins us to discuss the architecture and challenges of building real-time, production-ready conversational voice AI. Kwin breaks down the full stack for voice agents—from the models and APIs to the critical orchestration layer that manages…

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Distilling Transformers and Diffusion Models for Robust Edge Use Cases with Fatih Porikli - #738 1:00:29

3M ago1:00:29

1:00:29

Today, we're joined by Fatih Porikli, senior director of technology at Qualcomm AI Research for an in-depth look at several of Qualcomm's accepted papers and demos featured at this year’s CVPR conference. We start with “DiMA: Distilling Multi-modal Large Language Models for Autonomous Driving,” an end-to-end autonomous driving system that incorpora…

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Building the Internet of Agents with Vijoy Pandey - #737 56:13

3M ago56:13

56:13

Today, we're joined by Vijoy Pandey, SVP and general manager at Outshift by Cisco to discuss a foundational challenge for the enterprise: how do we make specialized agents from different vendors collaborate effectively? As companies like Salesforce, Workday, and Microsoft all develop their own agentic systems, integrating them creates a complex, pr…

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LLMs for Equities Feature Forecasting at Two Sigma with Ben Wellington - #736 59:31

3M ago59:31

59:31

Today, we're joined by Ben Wellington, deputy head of feature forecasting at Two Sigma. We dig into the team’s end-to-end approach to leveraging AI in equities feature forecasting, covering how they identify and create features, collect and quantify historical data, and build predictive models to forecast market behavior and asset prices for tradin…

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Zero-Shot Auto-Labeling: The End of Annotation for Computer Vision with Jason Corso - #735 56:45

4M ago56:45

56:45

Today, we're joined by Jason Corso, co-founder of Voxel51 and professor at the University of Michigan, to explore automated labeling in computer vision. Jason introduces FiftyOne, an open-source platform for visualizing datasets, analyzing models, and improving data quality. We focus on Voxel51’s recent research report, “Zero-shot auto-labeling riv…

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S4E15 Hill's Pet Nutrition Weight Care Program with Shoshana Verton-Shaw RVT and Dr. Adronie Verbrugghe 46:43

4M ago46:43

46:43

Have that one patient who can't seem to lose weight no matter what you try? This week we have two guests, RVT Shoshana Verton-Shaw and Dr. Adronie Verbrugghe to talk about OVC's new Hill's Pet Nutrition Weight Care Program! The Ontario Veterinary College is launching a holistic referral weight care clinic, encompassing both physical rehabilitation …

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Grokking, Generalization Collapse, and the Dynamics of Training Deep Neural Networks with Charles Martin - #734 1:25:21

4M ago1:25:21

1:25:21

Today, we're joined by Charles Martin, founder of Calculation Consulting, to discuss Weight Watcher, an open-source tool for analyzing and improving Deep Neural Networks (DNNs) based on principles from theoretical physics. We explore the foundations of the Heavy-Tailed Self-Regularization (HTSR) theory that underpins it, which combines random matri…

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Google I/O 2025 Special Edition - #733 26:21

4M ago26:21

26:21

Today, I’m excited to share a special crossover edition of the podcast recorded live from Google I/O 2025! In this episode, I join Shawn Wang aka Swyx from the Latent Space Podcast, to interview Logan Kilpatrick and Shrestha Basu Mallick, PMs at Google DeepMind working on AI Studio and the Gemini API, along with Kwindla Kramer, CEO of Daily and cre…

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S4E14 Cancer Biomarkers for Early Detection with Dr. Geoffrey Wood 41:26

4M ago41:26

41:26

Ever wonder how the tests we perform on patients came to be? Join Dr. Omar Khan and Dr. Geoffrey Wood as they discuss microRNA's and ground-breaking investigation into their use in developing tests for osteosarcoma and hemangiosarcoma in dogs. Dr. Wood is the Assistant Co-Director at the Institute for Comparative Cancer Investigation and a board ce…

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RAG Risks: Why Retrieval-Augmented LLMs are Not Safer with Sebastian Gehrmann - #732 57:09

4M ago57:09

57:09

Today, we're joined by Sebastian Gehrmann, head of responsible AI in the Office of the CTO at Bloomberg, to discuss AI safety in retrieval-augmented generation (RAG) systems and generative AI in high-stakes domains like financial services. We explore how RAG, contrary to some expectations, can inadvertently degrade model safety. We cover examples o…

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From Prompts to Policies: How RL Builds Better AI Agents with Mahesh Sathiamoorthy - #731 1:01:25

4M ago1:01:25

1:01:25

Today, we're joined by Mahesh Sathiamoorthy, co-founder and CEO of Bespoke Labs, to discuss how reinforcement learning (RL) is reshaping the way we build custom agents on top of foundation models. Mahesh highlights the crucial role of data curation, evaluation, and error analysis in model performance, and explains why RL offers a more robust altern…

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How OpenAI Builds AI Agents That Think and Act with Josh Tobin - #730 1:07:27

5M ago1:07:27

1:07:27

Today, we're joined by Josh Tobin, member of technical staff at OpenAI, to discuss the company’s approach to building AI agents. We cover OpenAI's three agentic offerings—Deep Research for comprehensive web research, Operator for website navigation, and Codex CLI for local code execution. We explore OpenAI’s shift from simple LLM workflows to reaso…

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CTIBench: Evaluating LLMs in Cyber Threat Intelligence with Nidhi Rastogi - #729 56:18

5M ago56:18

56:18

Today, we're joined by Nidhi Rastogi, assistant professor at Rochester Institute of Technology to discuss Cyber Threat Intelligence (CTI), focusing on her recent project CTIBench—a benchmark for evaluating LLMs on real-world CTI tasks. Nidhi explains the evolution of AI in cybersecurity, from rule-based systems to LLMs that accelerate analysis by p…

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Generative Benchmarking with Kelly Hong - #728 54:17

5M ago54:17

54:17

In this episode, Kelly Hong, a researcher at Chroma, joins us to discuss "Generative Benchmarking," a novel approach to evaluating retrieval systems, like RAG applications, using synthetic data. Kelly explains how traditional benchmarks like MTEB fail to represent real-world query patterns and how embedding models that perform well on public benchm…

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Exploring the Biology of LLMs with Circuit Tracing with Emmanuel Ameisen - #727 1:34:06

5M ago1:34:06

1:34:06

In this episode, Emmanuel Ameisen, a research engineer at Anthropic, returns to discuss two recent papers: "Circuit Tracing: Revealing Language Model Computational Graphs" and "On the Biology of a Large Language Model." Emmanuel explains how his team developed mechanistic interpretability methods to understand the internal workings of Claude by rep…

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S4E13 Spaying and Neutering Pets with OVC Theriogenologist Dr. Michelle Caissie 27:04

5M ago27:04

27:04

Ever wonder when you should be spaying or neutering an animal? Well look no further as who better to ask than OVC's own Theriogenologist, Dr. Michelle Caissie! After graduating from AVC in 2015, Michelle completed a large animal rotating internship at OVC. During this time, her passion for reproduction (theriogenology) flourished and she continued …

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Teaching LLMs to Self-Reflect with Reinforcement Learning with Maohao Shen - #726 51:45

6M ago51:45

51:45

Today, we're joined by Maohao Shen, PhD student at MIT to discuss his paper, “Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search.” We dig into how Satori leverages reinforcement learning to improve language model reasoning—enabling model self-reflection, self-correction, and exploration of a…

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Waymo's Foundation Model for Autonomous Driving with Drago Anguelov - #725 1:09:07

6M ago1:09:07

1:09:07

Today, we're joined by Drago Anguelov, head of AI foundations at Waymo, for a deep dive into the role of foundation models in autonomous driving. Drago shares how Waymo is leveraging large-scale machine learning, including vision-language models and generative AI techniques to improve perception, planning, and simulation for its self-driving vehicl…

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S4E12 Developing Communication Skills for Veterinary Practice with Dr. Jane Shaw & Dr. Jason Coe 46:15

6M ago46:15

46:15

This week we have 2 special guests joining us on Vet Sessions! We have Dr. Jason Coe who some of you may remember from our podcast about the AVM value matrix. We also have Dr. Jane Shaw joining us from Colorado State University. Dr. Jane Shaw is an expert in veterinarian-client-patient interactions, Professor, University Distinguished Teaching Scho…

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Dynamic Token Merging for Efficient Byte-level Language Models with Julie Kallini - #724 50:32

6M ago50:32

50:32

Today, we're joined by Julie Kallini, PhD student at Stanford University to discuss her recent papers, “MrT5: Dynamic Token Merging for Efficient Byte-level Language Models” and “Mission: Impossible Language Models.” For the MrT5 paper, we explore the importance and failings of tokenization in large language models—including inefficient compression…

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Scaling Up Test-Time Compute with Latent Reasoning with Jonas Geiping - #723 58:38

6M ago58:38

58:38

Today, we're joined by Jonas Geiping, research group leader at Ellis Institute and the Max Planck Institute for Intelligent Systems to discuss his recent paper, “Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach.” This paper proposes a novel language model architecture which uses recurrent depth to enable “thinking in l…

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Imagine while Reasoning in Space: Multimodal Visualization-of-Thought with Chengzu Li - #722 42:11

7M ago42:11

42:11

Today, we're joined by Chengzu Li, PhD student at the University of Cambridge to discuss his recent paper, “Imagine while Reasoning in Space: Multimodal Visualization-of-Thought.” We explore the motivations behind MVoT, its connection to prior work like TopViewRS, and its relation to cognitive science principles such as dual coding theory. We dig i…

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S4E11 Blocked Cats with Dr. Matt Kornya 49:07

7M ago49:07

49:07

Dr. Matt Kornya is back with us this week to talk all about urinary obstructions in cats! Dr. Kornya breaks down the causes, symptoms, and most importantly, the treatments available for this serious condition through some cases presented by Dr. Gowland. Whether you’re a veterinary student or general practitioner, this episode is packed with expert …

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Inside s1: An o1-Style Reasoning Model That Cost Under $50 to Train with Niklas Muennighoff - #721 49:29

7M ago49:29

49:29

Today, we're joined by Niklas Muennighoff, a PhD student at Stanford University, to discuss his paper, “S1: Simple Test-Time Scaling.” We explore the motivations behind S1, as well as how it compares to OpenAI's O1 and DeepSeek's R1 models. We dig into the different approaches to test-time scaling, including parallel and sequential scaling, as well…

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Accelerating AI Training and Inference with AWS Trainium2 with Ron Diamant - #720 1:07:05

7M ago1:07:05

1:07:05

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 chip. We explore the architectural differences between Trainium and GPUs, highlighting its systolic array-based compute design, and how it balances per…

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S4E10 Otitis with Dr. Liz Goodale 39:21

7M ago39:21

39:21

In this episode, Dr. Liz Goodale explores veterinary otitis, a common ear issue affecting pets. Dr. Goodale discusses the different types of otitis in dogs and cats, how to spot the symptoms, and the best treatment options to ensure your furry friend stays comfortable. If you've ever wondered how to care for your pet’s ears or prevent ear infection…

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π0: A Foundation Model for Robotics with Sergey Levine - #719 52:30

7M ago52:30

52:30

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 model architecture, which pairs a vision language model (VLM) with a diffusion-based action expert, and the model training "recipe," emphasizing the ro…

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AI Trends 2025: AI Agents and Multi-Agent Systems with Victor Dibia - #718 1:44:59

8M ago1:44:59

1:44:59

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. In this episode, we discuss the unique abilities that set AI agents apart from traditional software systems–reasoning, acting, communicating, and ada…

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S4E9 Value Matrix with Dr. Jason Coe 38:40

8M ago38:40

38:40

Join us this week as we invite Dr. Jason Coe to dive into the Value Matrix, a powerful visual aid that’s transforming shared decision-making in veterinary practices! Dr. Coe is a professor at the Ontario Veterinary College and currently holds the VCA Canada Chair in Relationship-Centred Veterinary Medicine. In this episode, Dr. Coe explains how the…

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Speculative Decoding and Efficient LLM Inference with Chris Lott - #717 1:16:30

8M ago1:16:30

1:16:30

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 encoding and decoding (aka generation) and how these interact with various hardware constraints such as FLOPS, memory footprint and memory bandwidth to limit…

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Ensuring Privacy for Any LLM with Patricia Thaine - #716 51:33

8M ago51:33

51:33

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) and other AI services. We explore the risks of data leakage from LLMs and embeddings, the complexities of identifying and redacting personal informat…

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AI Engineering Pitfalls with Chip Huyen - #715 57:37

8M ago57:37

57:37

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 machine learning engineering, the common pitfalls encountered in engineering AI systems, and strategies to overcome them. We also explore how Chip defines …

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S4E8 Feeding Tubes with Dr. Sarah Abood 48:16

8M ago48:16

48:16

Curious as to how feeding tubes can help improve patient care? Join us this week on Vet Sessions as Dr. Omar Khan chats with Dr. Sarah Abood about all things tube feeding for cats and dogs! This is Dr. Abood's third time on our podcast, and she always gives a lot of excellent information on veterinary nutrition! Be sure to check out our other podca…

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Evolving MLOps Platforms for Generative AI and Agents with Abhijit Bose - #714 58:08

8M ago58:08

58:08

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. In this episode, we dig into the company’s platform-centric approach to AI, and how they’ve been evolving their existing MLOps and data platforms to …

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S4E7 Managing Diabetic Patients with Dr. Erin Phillips Part 2 44:45

9M ago44:45

44:45

Welcome back listeners! We hope everyone had a wonderful holiday season. This week, please join us for part 2 of the topic of managing diabetic patients with Dr. Erin Phillips. If you haven’t heard Part 1 yet, be sure to listen to that first! We hope you enjoy!By Tiffany Durzi

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Why Agents Are Stupid & What We Can Do About It with Dan Jeffries - #713 1:08:49

9M ago1:08:49

1:08:49

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 distinguishes them from other similar uses of LLM, explore various use cases for them, and dig into ways to create smarter agentic systems. Dan shared his “big …

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Automated Reasoning to Prevent LLM Hallucination with Byron Cook - #712 56:48

10M ago56:48

56:48

Today, we're joined by Byron Cook, VP and distinguished scientist in the Automated Reasoning Group at AWS to dig into the underlying technology behind the newly announced Automated Reasoning Checks feature of Amazon Bedrock Guardrails. Automated Reasoning Checks uses mathematical proofs to help LLM users safeguard against hallucinations. We explore…

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S4E6 Managing Diabetic Patients with Dr. Erin Phillips Part 1 27:09

10M ago27:09

27:09

This week we welcome back Dr. Erin Phillips! Our guest this episode has been on several previous episodes of Vet Sessions. Dr. Phillips is a board-certified specialist in Small Animal Internal Medicine, and is working toward a PhD in the RCVM@OVC lab. This episode, she talks about managing diabetic patients. This episode is intended to be a guide f…

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AI at the Edge: Qualcomm AI Research at NeurIPS 2024 with Arash Behboodi - #711 54:47

10M ago54:47

54:47

Today, we're joined by Arash Behboodi, director of engineering at Qualcomm AI Research to discuss the papers and workshops Qualcomm will be presenting at this year’s NeurIPS conference. We dig into the challenges and opportunities presented by differentiable simulation in wireless systems, the sciences, and beyond. We also explore recent work that …