On this episode, we’re joined by Brandon Duderstadt, Co-Founder and CEO of Nomic AI . Both of Nomic AI’s products, Atlas and GPT4All, aim to improve the explainability and accessibility of AI. We discuss: - (0:55) What GPT4All is and its value proposition. - (6:56) The advantages of using smaller LLMs for specific tasks. - (9:42) Brandon’s thoughts on the cost of training LLMs. - (10:50) Details about the current state of fine-tuning LLMs. - (12:20) What quantization is and wha...
Jul 27, 2023•1 hr 1 min•Transcript available on Metacast On this episode, we’re joined by Soumith Chintala , VP/Fellow of Meta and Co-Creator of PyTorch. Soumith and his colleagues’ open-source framework impacted both the development process and the end-user experience of what would become PyTorch. We discuss: - The history of PyTorch’s development and TensorFlow’s impact on development decisions. - How a symbolic execution model affects the implementation speed of an ML compiler. - The strengths of different programming languages in various developme...
Jul 13, 2023•1 hr 9 min•Transcript available on Metacast On this episode, we’re joined by Andrew Feldman , Founder and CEO of Cerebras Systems . Andrew and the Cerebras team are responsible for building the largest-ever computer chip and the fastest AI-specific processor in the industry. We discuss: - The advantages of using large chips for AI work. - Cerebras Systems’ process for building chips optimized for AI. - Why traditional GPUs aren’t the optimal machines for AI work. - Why efficiently distributing computing resources is a significant challeng...
Jun 22, 2023•1 hr•Transcript available on Metacast On this episode, we’re joined by Harrison Chase , Co-Founder and CEO of LangChain . Harrison and his team at LangChain are on a mission to make the process of creating applications powered by LLMs as easy as possible. We discuss: - What LangChain is and examples of how it works. - Why LangChain has gained so much attention. - When LangChain started and what sparked its growth. - Harrison’s approach to community-building around LangChain. - Real-world use cases for LangCha...
Jun 01, 2023•52 min•Transcript available on Metacast On this episode, we’re joined by Jean Marc Alkazzi , Applied AI at idealworks . Jean focuses his attention on applied AI, leveraging the use of autonomous mobile robots (AMRs) to improve efficiency within factories and more. We discuss: - Use cases for autonomous mobile robots (AMRs) and how to manage a fleet of them. - How AMRs interact with humans working in warehouses. - The challenges of building and deploying autonomous robots. - Computer vision vs. other types of localization technol...
May 18, 2023•58 min•Transcript available on Metacast On this episode, we’re joined by Stella Biderman , Executive Director at EleutherAI and Lead Scientist - Mathematician at Booz Allen Hamilton. EleutherAI is a grassroots collective that enables open-source AI research and focuses on the development and interpretability of large language models (LLMs). We discuss: - How EleutherAI got its start and where it's headed. - The similarities and differences between various LLMs. - How to decide which model to use for your desired outcome. - The benefit...
May 04, 2023•57 min•Transcript available on Metacast On this episode, we’re joined by Aidan Gomez , Co-Founder and CEO at Cohere . Cohere develops and releases a range of innovative AI-powered tools and solutions for a variety of NLP use cases. We discuss: - What “attention” means in the context of ML. - Aidan’s role in the “Attention Is All You Need” paper. - What state-space models (SSMs) are, and how they could be an alternative to transformers. - What it means for an ML architecture to saturate compute. - Details around data constraints ...
Apr 20, 2023•52 min•Transcript available on Metacast Jonathan Frankle , Chief Scientist at MosaicML and Assistant Professor of Computer Science at Harvard University, joins us on this episode. With comprehensive infrastructure and software tools, MosaicML aims to help businesses train complex machine-learning models using their own proprietary data. We discuss: - Details of Jonathan’s Ph.D. dissertation which explores his “Lottery Ticket Hypothesis.” - The role of neural network pruning and how it impacts the performance of ML models. - Why transf...
Apr 04, 2023•1 hr 2 min•Transcript available on Metacast About This Episode Shreya Shankar is a computer scientist, PhD student in databases at UC Berkeley, and co-author of "Operationalizing Machine Learning: An Interview Study", an ethnographic interview study with 18 machine learning engineers across a variety of industries on their experience deploying and maintaining ML pipelines in production. Shreya explains the high-level findings of "Operationalizing Machine Learning"; variables that indicate a successful deployment (velocity, validation, and...
Mar 03, 2023•55 min•Transcript available on Metacast Sarah Catanzaro is a General Partner at Amplify Partners, and one of the leading investors in AI and ML. Her investments include RunwayML, OctoML, and Gantry. Sarah and Lukas discuss lessons learned from the "AI renaissance" of the mid 2010s and compare the general perception of ML back then to now. Sarah also provides insights from her perspective as an investor, from selling into tech-forward companies vs. traditional enterprises, to the current state of MLOps/developer tools, to large languag...
Feb 02, 2023•1 hr 16 min•Transcript available on Metacast Cristóbal Valenzuela is co-founder and CEO of Runway ML, a startup that's building the future of AI-powered content creation tools. Runway's research areas include diffusion systems for image generation. Cris gives a demo of Runway's video editing platform. Then, he shares how his interest in combining technology with creativity led to Runway, and where he thinks the world of computation and content might be headed to next. Cris and Lukas also discuss Runway's tech stack and research. Show notes...
Jan 19, 2023•40 min•Transcript available on Metacast Jeremy Howard is a co-founder of fast.ai, the non-profit research group behind the popular massive open online course "Practical Deep Learning for Coders", and the open source deep learning library "fastai". Jeremy is also a co-founder of #Masks4All, a global volunteer organization founded in March 2020 that advocated for the public adoption of homemade face masks in order to help slow the spread of COVID-19. His Washington Post article "Simple DIY masks could help flatten the curve." went viral...
Jan 05, 2023•1 hr 13 min•Transcript available on Metacast Jerome Pesenti is the former VP of AI at Meta, a tech conglomerate that includes Facebook, WhatsApp, and Instagram, and one of the most exciting places where AI research is happening today. Jerome shares his thoughts on Transformers-based large language models, and why he's excited by the progress but skeptical of the term "AGI". Then, he discusses some of the practical applications of ML at Meta (recommender systems and moderation!) and dives into the story behind Meta's development of PyTorch....
Dec 22, 2022•53 min•Transcript available on Metacast D. Sculley is CEO of Kaggle, the beloved and well-known data science and machine learning community. D. discusses his influential 2015 paper "Machine Learning: The High Interest Credit Card of Technical Debt" and what the current challenges of deploying models in the real world are now, in 2022. Then, D. and Lukas chat about why Kaggle is like a rain forest, and about Kaggle's historic, current, and potential future roles in the broader machine learning community. Show notes (transcript and link...
Dec 01, 2022•1 hr•Transcript available on Metacast Emad Mostaque is CEO and co-founder of Stability AI, a startup and network of decentralized developer communities building open AI tools. Stability AI is the company behind Stable Diffusion, the well-known, open source, text-to-image generation model. Emad shares the story and mission behind Stability AI (unlocking humanity's potential with open AI technology), and explains how Stability's role as a community catalyst and compute provider might evolve as the company grows. Then, Emad and Lukas d...
Nov 15, 2022•1 hr 10 min•Transcript available on Metacast Jehan Wickramasuriya is the Vice President of AI, Platform & Data Services at Motorola Solutions, a global leader in public safety and enterprise security. In this episode, Jehan discusses how Motorola Solutions uses AI to simplify data streams to help maximize human potential in high-stress situations. He also shares his thoughts on augmenting synthetic data with real data and the challenges posed in partnering with startups. Show notes (transcript and links): http://wandb.me/gd-jehan-wickr...
Oct 06, 2022•1 hr•Transcript available on Metacast Will Falcon is the CEO and co-founder of Lightning AI, a platform that enables users to quickly build and publish ML models. In this episode, Will explains how Lightning addresses the challenges of a fragmented AI ecosystem and reveals which framework PyTorch Lightning was originally built upon (hint: not PyTorch!) He also shares lessons he took from his experience serving in the military and offers a recommendation to veterans who want to work in tech. Show notes (transcript and links): http://...
Sep 15, 2022•45 min•Transcript available on Metacast Aaron Colak is the Leader of Core Machine Learning at Qualtrics, an experiment management company that takes large language models and applies them to real-world, B2B use cases. In this episode, Aaron describes mixing classical linguistic analysis with deep learning models and how Qualtrics organized their machine learning organizations and model to leverage the best of these techniques. He also explains how advances in NLP have invited new opportunities in low-resource languages. Show notes (tr...
Aug 26, 2022•50 min•Transcript available on Metacast Jordan Fisher is the CEO and co-founder of Standard AI, an autonomous checkout company that’s pushing the boundaries of computer vision. In this episode, Jordan discusses “the Wild West” of the MLOps stack and tells Lukas why Rust beats Python. He also explains why AutoML shouldn't be overlooked and uses a bag of chips to help explain the Manifold Hypothesis. Show notes (transcript and links): http://wandb.me/gd-jordan-fisher --- ⏳ Timestamps: 00:00 Intro 00:40 The origins of Standard AI 08:30 G...
Aug 04, 2022•58 min•Transcript available on Metacast Drago Anguelov is a Distinguished Scientist and Head of Research at Waymo, an autonomous driving technology company and subsidiary of Alphabet Inc. We begin by discussing Drago's work on the original Inception architecture, winner of the 2014 ImageNet challenge and introduction of the inception module. Then, we explore milestones and current trends in autonomous driving, from Waymo's release of the Open Dataset to the trade-offs between modular and end-to-end systems. Drago also shares his thoug...
Jul 14, 2022•1 hr 9 min•Transcript available on Metacast James Cham is a co-founder and partner at Bloomberg Beta, an early-stage venture firm that invests in machine learning and the future of work, the intersection between business and technology. James explains how his approach to investing in AI has developed over the last decade, which signals of success he looks for in the ever-adapting world of venture startups (tip: look for the "gradient of admiration"), and why it's so important to demystify ML for executives and decision-makers. Lukas and J...
Jul 07, 2022•1 hr 6 min•Transcript available on Metacast Check out this report by Boris about DALL-E mini: https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-mini-Generate-images-from-any-text-prompt--VmlldzoyMDE4NDAy https://wandb.ai/_scott/wandb_example/reports/Collaboration-in-ML-made-easy-with-W-B-Teams--VmlldzoxMjcwMDU5 https://twitter.com/weirddalle Connect with Boris: 📍 Twitter: https://twitter.com/borisdayma --- 💬 Host: Lukas Biewald 📹 Producers: Cayla Sharp, Angelica Pan, Sanyam Bhutani, Lavanya Shukla --- Subscribe and listen to our po...
Jun 17, 2022•36 min•Transcript available on Metacast Tristan Handy is CEO and founder of dbt Labs. dbt (data build tool) simplifies the data transformation workflow and helps organizations make better decisions. Lukas and Tristan dive into the history of the modern data stack and the subsequent challenges that dbt was created to address; communities of identity and product-led growth; and thoughts on why SQL has survived and thrived for so long. Tristan also shares his hopes for the future of BI tools and the data stack. Show notes (transcript and...
Jun 09, 2022•1 hr 1 min•Transcript available on Metacast Johannes Otterbach is VP of Machine Learning Research at Merantix Momentum, an ML consulting studio that helps their clients build AI solutions. Johannes and Lukas talk about Johannes' background in physics and applications of ML to quantum computing, why Merantix is investing in creating a cloud-agnostic tech stack, and the unique challenges of developing and deploying models for different customers. They also discuss some of Johannes' articles on the impact of NLP models and the future of AI r...
May 12, 2022•45 min•Transcript available on Metacast Mircea Neagovici is VP, AI and Research at UiPath, where his team works on task mining and other ways of combining robotic process automation (RPA) with machine learning for their B2B products. Mircea and Lukas talk about the challenges of allowing customers to fine-tune their models, the trade-offs between traditional ML and more complex deep learning models, and how Mircea transitioned from a more traditional software engineering role to running a machine learning organization. Show notes (tra...
Apr 21, 2022•46 min•Transcript available on Metacast Jensen Huang is founder and CEO of NVIDIA, whose GPUs sit at the heart of the majority of machine learning models today. Jensen shares the story behind NVIDIA's expansion from gaming to deep learning acceleration, leadership lessons that he's learned over the last few decades, and why we need a virtual world that obeys the laws of physics (aka the Omniverse) in order to take AI to the next era. Jensen and Lukas also talk about the singularity, the slow-but-steady approach to building a new marke...
Mar 03, 2022•49 min•Transcript available on Metacast Peter Welinder is VP of Product & Partnerships at OpenAI, where he runs product and commercialization efforts of GPT-3, Codex, GitHub Copilot, and more. Boris Dayma is Machine Learning Engineer at Weights & Biases, and works on integrations and large model training. Peter, Boris, and Lukas dive into the world of GPT-3: - How people are applying GPT-3 to translation, copywriting, and other commercial tasks - The performance benefits of fine-tuning GPT-3- - Developing an API on top of GPT-...
Feb 10, 2022•44 min•Transcript available on Metacast Ion Stoica is co-creator of the distributed computing frameworks Spark and Ray, and co-founder and Executive Chairman of Databricks and Anyscale. He is also a Professor of computer science at UC Berkeley and Principal Investigator of RISELab, a five-year research lab that develops technology for low-latency, intelligent decisions. Ion and Lukas chat about the challenges of making a simple (but good!) distributed framework, the similarities and differences between developing Spark and Ray, and ho...
Jan 20, 2022•54 min•Transcript available on Metacast Stephan Fabel is Senior Director of Infrastructure Systems & Software at NVIDIA, where he works on Base Command, a software platform to coordinate access to NVIDIA's DGX SuperPOD infrastructure. Lukas and Stephan talk about why having a supercomputer is one thing but using it effectively is another, why a deeper understanding of hardware on the practitioner level is becoming more advantageous, and which areas of the ML tech stack NVIDIA is looking to expand into. The complete show notes (tra...
Jan 06, 2022•52 min•Transcript available on Metacast Chris Padwick is Director of Computer Vision Machine Learning at Blue River Technology, a subsidiary of John Deere. Their core product, See & Spray, is a weeding robot that identifies crops and weeds in order to spray only the weeds with herbicide. Chris and Lukas dive into the challenges of bringing See & Spray to life, from the hard computer vision problem of classifying weeds from crops, to the engineering feat of building and updating embedded systems that can survive on a farming ma...
Dec 23, 2021•1 hr 1 min•Transcript available on Metacast 
