Dr. Bratin Saha is the Vice President of Machine Learning and AI services at AWS where he leads all the ML and AI services and helped build one of the fastest growing businesses in AWS history. He is an alumnus of Harvard Business School (General Management Program), Yale University (PhD Computer Science), and Indian Institute of Technology (BS Computer Science). He has more than 70 patents granted (with another 50+ pending) and more than 30 papers in conferences/journals. In 2022 Harvard Business School wrote three case studies on how he built the machine learning business at AWS. Prior to Amazon he worked at Nvidia and Intel leading different product groups spanning imaging, analytics, media processing, high performance computing, machine learning, and software infrastructure. Bratin received the Distinguished Alumnus Award from the Indian Institute of Technology and an Executive Fellow at the Harvard Business School.

Bryan Catanzaro is vice president of Applied Deep Learning Research at NVIDIA, where he leads a team finding new ways to use AI to improve projects ranging from language understanding to computer graphics and chip design. Bryan's research at NVIDIA led to the creation of CUDNN, and more recently, he helped lead the team that invented DLSS 2.0. Prior to NVIDIA, he worked at Baidu to create next-generation systems for training and deploying end-to-end, deep learning-based speech recognition. Bryan received his PhD in Electrical Engineering and Computer Sciences from the University of California, Berkeley.

Cack partners with entrepreneurs building category-leading businesses in AI, cloud, data, security, and web3 infrastructure.

Distinguished Leader who founded and scaled critical infrastructure including LLVM, Clang, MLIR, Cloud TPUs and the Swift programming language. Chris built AI and core systems at multiple world leading technology companies including Apple, Google, SiFive and Tesla.

Leads the PyTorch team at Meta. In the past I've worked on compilers, static analysis, programming languages, virtual machines and developer tools.

Dave Munichiello is a General Partner at GV (Google Ventures) where he coleads the firm’s Digital Investing Team, spanning its Enterprise Software, Consumer Tech, and Frontier (DeepTech) practice areas. Dave’s decade-plus at GV has included a focus on developer platforms, data-centric systems, and companies building both “for AI” and “with AI”. His exited investments include Ahana (sold to IBM), Bugsnag (sold to SmartBear), CoreOS (sold to RedHat), DeterminedAI (sold to HPE), GitLab (NASDAQ: GTLB), Jet.com (sold to Walmart), Lattice.io (sold to Apple), Pixie (sold to NewRelic), Segment (sold to Twilio), and Slack (NYSE: WORK, sold to Salesforce). Dave’s active investments include Cockroach, Modular, RedPanda, SambaNova, Snorkel, Upbound, and Wonder. Prior to his Google Ventures role, Dave built and led enterprise software product, sales, and operations teams for highly-technical products under pressure in rapidly-changing markets. An early exec at Kiva Systems, he grew the enterprise-enabling robotics and software platform from pre-PMF to $120 million in annual revenue before it was purchased by Amazon, becoming Amazon Robotics. Dave is a combat veteran and former paratrooper who served as a Captain in the U.S. military’s most elite units before his startup career. Dave earned his bachelors degree in mathematics and computer science from Emory University and his MBA from Harvard Business School.

At General Catalyst, Deep has the opportunity to continue working with a new generation of world class founders, and help guide a transformational change in technology and investing. The current generation has learned hard lessons about unintended consequences of technological change, and now we need to make responsible innovation the standard for the next generation of entrepreneurs and companies.

Product leader who has built and scaled AI applications and infrastructure. Eric led the TensorFlow API, Compiler, and Runtime teams at Google Brain and Core Systems, including the founding of TFRT and the productionization of JAX. He holds an MBA from Wharton and Computer Science MS from Penn and loves soccer, fitness, and the great outdoors.

Kari Briski is vice president of product management for AI and HPC software development kits at NVIDIA, where she oversees strategy, roadmaps and requirements for the company's AI software products.

Kelsey Szot is a cofounder at Adept, an AI lab building useful general intelligence. Before Adept, Kelsey led product for Google’s large model infra and production efforts. Kelsey has also worked as a management consultant at McKinsey & Company, and she holds a BS and an MS in computational mathematics from Stanford.

AI researcher working on autonomous vehicles, human-robot interaction, and machine learning at MIT and beyond. Host of the Lex Fridman podcast.

Mostafa is a seasoned engineering leader in high-performance computing. During his tenure at NVIDIA, he served as Engineering Director and led teams to develop optimized deep learning libraries like cuDNN and CUTLASS, revolutionizing GPU-accelerated AI. At SiFive, as VP of Software, Mostafa assumed a leadership role guiding teams in the development of an MLIR/LLVM-based software stack for SiFive Intelligence & performance cores. His contributions also extend to optimizing Intel GPU hardware/software features, playing a pivotal role in developing the AVX1/2 SIMD ISA for Intel CPUs, and contributing to the GNU C Compiler. Mostafa holds a Master of Science in Electrical Engineering from the Technion, with a specialization in compiler optimizations. His unwavering passion for innovation continues to drive advancements in the field of high-performance computing.

Software Engineering lead with over 15 years of experience working at Google, Microsoft and a handful of startups. Nick has contributed to many technologies in Machine Learning such as TensorFlow.js, TensorFlow Lite/Micro, and ONNX/ONNXRuntime. Nick enjoys spending his free time with family and enjoying the Minnesotan outdoors.

Swyx is Editor of Latent.Space, which has been documenting the Rise of the AI Engineer as a top 10 US Tech podcast. He is also cofounder of the AI.Engineer Summit and previously headed developer experience for AWS, Airbyte and Temporal.

Repeat Entrepreneur and Product Leader. Tim helped build, found and scale large parts of Google's AI infrastructure at Google Brain and Core Systems from APIs (TensorFlow), Compilers (XLA & MLIR) and runtimes for server (CPU/GPU/TPU) and TF Lite (Mobile/Micro/Web), Android ML & NNAPI, large model infrastructure & OSS for billions of users and devices. Loves running, building and scaling products to help people, and the world.

Vijay is a Partner at Mayfield and focuses on investments in AI. He brings over a decade of inception and early-stage investing experience in from Clear Ventures and Intel Capital. Vijay has invested across the AI stack from silicon, systems, infrastructure software, data, middleware & tools and applications. A Kauffman Fellow, Vijay received his MBA from the University of Chicago Booth School of Business and has a BS & MS in Electrical and Computer Engineering.

Vivek is a AI executive at Snowflake. He formerly cofounded and was CTO at Neeva AI (acquired by Snowflake) and lead engineering for YouTube monetization at Google.

Expert in machine learning, compilers, programming languages, and accelerated computing. Before Modular, Abdul led the development of AI compilers for GPUs at Microsoft Research and the Mathematica Compiler at Wolfram Research. Abdul has developed open-source tools for accelerating real-world applications to optimize their performance across the hardware and software stack.

As a hands-on technical leader, Adin is passionate about building products and technologies that challenge the status quo. He previously co-founded GridCentric which was acquired by Google, where he worked on problems at scale for nine years across Google and Google Cloud. He has spent the last two decades solving problems across the infrastructure stack — from hypervisors and operating systems to containers and security.

Dan has over 15 years of software engineering experience in a wide variety of fields and roles. Before Modular, Dan worked in teams such as Google Brain and TensorFlow, where he co-authored AutoGraph, led improvements to system architecture, graph representations and APIs, developed ML and TensorFlow training material, and collaborated with ML researchers. Dan is passionate about developing next generation programming languages for machine learning. Dan enjoys hiking, stargazing and traveling around the world.

Jack started his career optimizing autonomous truck software for leading mining companies, including BHP and Caterpillar. Most recently he was designing computer vision software, putting AI inference pipelines into production for IDVerse. He is enormously passionate about the developer community, having been a Rust, Go, Python and C++ developer for over a decade. Jack enjoys making complicated topics simple and fun to learn, and he’s dedicated to teaching the world about Mojo 🔥.

Compiler Engineer, MLIR Developer, and former Robotics Hacker. Jeff studied Mechatronics Engineering at the University of Waterloo where he explored his passion for Robotics before falling in love with MLIR and Compilers while at Google, where he worked making TensorFlow faster and better for everyone. Jeff is now developing MLIR-based compilers at Modular to make AI better for the World.

Software Engineering lead with a strong background in mathematics, optimization, and team management. Matthew comes to Modular with over 7 years of experience working on AI models and Compilers at large companies like Intel and small startups working on technologies like TVM. He's a total coding nerd, and loves picking up new programming languages and tracking down bugs. Matthew enjoys spending his free time hiking in the Wasatch Mountains, and loves to bake delicious breads and pizzas for his family.

Shashank is an engineer, educator and doodler. He writes and talks about machine learning, specialized machine learning hardware (AI Accelerators) and AI Infrastructure in the cloud. He previously worked at Meta, AWS, NVIDIA, MathWorks (MATLAB) and Oracle in developer relations and marketing, product management, and software development roles and hold an M.S. in electrical engineering.

Leader in compilers, programming models, and AI systems. Before joining Modular, Tatiana led CPU and GPU compiler infrastructure for Google ML, co-founded MLIR, and was a Principal Engineer and Director of Programming Systems Research at Intel Labs. Tatiana has published ~40 research papers, holds ~50 US and international patents, and has served on numerous research conference programming committees, including being Co-Chair of CGO 2022.