Machine Learning

Datacast Episode 128: Building Trust with Founders, VC Funding for the Cloud, and The Next Platform for Data Apps with Jason Risch

Datacast Episode 128: Building Trust with Founders, VC Funding for the Cloud, and The Next Platform for Data Apps with Jason Risch

Jason Risch is an investor on the enterprise team at Greylock - investing in security, AI/ML, data, infrastructure, and developer tools. Before joining Greylock, he incubated ML companies at AI Fund and was a management consultant at McKinsey. Jason is a Bay Area native, graduated from Stanford, and when not working, can be found reading, hiking, playing Age of Empires, and cheering on Stanford Football.

Datacast Episode 124: The Open-Source Cloud Playbook, The Modular Future of Data and AI Infrastructure, and Meta-Learning as a VC with Casber Wang

Datacast Episode 124: The Open-Source Cloud Playbook, The Modular Future of Data and AI Infrastructure, and Meta-Learning as a VC with Casber Wang

Casber Wang is Partner at Sapphire Ventures. He focuses primarily on security, enterprise infrastructure, and data analytics.

He is on the boards of Huntress, JumpCloud, StarTree, Tetrate, Upytcs, and Zesty. For his work, Insider listed Casber as an Enterprise VC Rising Star Investor and as an emerging investor charting the industry’s future on the 2022 EVC List.

Prior to Sapphire, he was part of the technology investment banking group at Bank of America Merrill Lynch, where he worked on a number of high-profile IPO and M&A transactions. He also spent time at Wish, a leading mobile commerce platform in North America and Europe.

Datacast Episode 109: Developer Productivity, Real-Time Data Infrastructure, and The Fat-Tailed Nature of Enterprise Software with Nnamdi Iregbulem

Datacast Episode 109: Developer Productivity, Real-Time Data Infrastructure, and The Fat-Tailed Nature of Enterprise Software with Nnamdi Iregbulem

Nnamdi Iregbulem, a Partner at Lightspeed Venture Partners, is a self-taught programmer and lifelong technology nerd. His mission is to increase total software output by supporting entrepreneurs building technical tools for technical people. He focuses on investments in technical enterprise software such as developer tools, application infrastructure, and machine learning.

Datacast Episode 108: Computer Vision, Product Management, and Enterprise Investing with Tom Rikert

Datacast Episode 108: Computer Vision, Product Management, and Enterprise Investing with Tom Rikert

Tom Rikert is the co-founder and CEO of Masterful AI, the training platform for computer vision that helps developers build models faster and with much less labeling. He is a former VC and invested in enterprise software and AI/ML at Andreessen Horowitz. Before VC, he held product management roles at Wildfire (acquired by Google), YouTube, and Autodesk. He began his AI/ML journey at MIT and started his career as an engineer at Silicon Graphics. Tom lives in the Bay Area with his wife and daughter and loves going fast, whether on a mountain bike or flying racing drones.

Datacast Episode 107: Investing At The Nexus of Computational Sciences with Grace Isford

Datacast Episode 107: Investing At The Nexus of Computational Sciences with Grace Isford

Grace Isford is a Partner based in Lux Capital's New York City office. She invests in companies innovating at the nexus of the computational sciences – data, AI and ML infrastructure, network and compute infrastructure, and cutting-edge technological applications, especially in healthcare and financial services. She focuses on data and machine-learning startups that are hyper-personalizing user experiences and transforming legacy industries, as well as fintech and blockchain infrastructure companies building the next-gen developer stack and payment rails.

Datacast Episode 102: Early-Stage Investing, Modern Venture Capital, and Trends in Enterprise Infrastructure with Astasia Myers

Datacast Episode 102: Early-Stage Investing, Modern Venture Capital, and Trends in Enterprise Infrastructure with Astasia Myers

Astasia Myers is a Partner on Quiet Capital's enterprise team leading investments in ML, data infrastructure, open-source, developer tools, and security. She focuses on pre-seed, seed, and Series A.

Prior to joining Quiet, Astasia was an investor in Redpoint's early-stage enterprise team, where she partnered with Dremio, LaunchDarkly, Solo.io, Preset, Hex, Cyral, among others. Before that, she worked at Cisco Investments, where she focused on cloud-infrastructure M&A and investments, including Cohesity, Datos IO, Elastifile, Guardicore, Springpath, and the funding of internal stealth projects.

Datacast Episode 97: Escaping Poverty, Embracing Digital Learning, Benchmarking ML Systems, and Advancing Data-Centric AI with Cody Coleman

Datacast Episode 97: Escaping Poverty, Embracing Digital Learning, Benchmarking ML Systems, and Advancing Data-Centric AI with Cody Coleman

Cody Coleman is the Founder and CEO of Coactive AI. He is also a co-creator of DAWNBench and MLPerf and a founding member of MLCommons. His work spans from performance benchmarking of hardware and software systems to computationally efficient methods for active learning and core-set selection. He holds a Ph.D. in Computer Science from Stanford University, where Professors Matei Zaharia and Peter Bailis advised him, and an MEng and BS from MIT.

What I Learned From Tecton's apply() 2022 Conference

What I Learned From Tecton's apply() 2022 Conference

Back in May, I attended apply(), Tecton’s second annual virtual event for data and ML teams to discuss the practical data engineering challenges faced when building ML for the real world. There were talks on best practice development patterns, tools of choice, and emerging architectures to successfully build and manage production ML applications.

This long-form article dissects content from 14 sessions and lightning talks that I found most useful from attending apply(). These talks cover 3 major areas: industry trends, production use cases, and open-source libraries. Let’s dive in!

Datacast Episode 89: Observable, Robust, and Responsible AI with Alessya Visnjic

Datacast Episode 89: Observable, Robust, and Responsible AI with Alessya Visnjic

Alessya Visnjic is the CEO and co-founder of WhyLabs, the AI Observability company on a mission to build the interface between AI and human operators. Prior to WhyLabs, Alessya was a CTO-in-residence at the Allen Institute for AI (AI2), where she evaluated the commercial potential for the latest advancements in AI research.

Earlier in her career, Alessya spent nine years at Amazon, leading Machine Learning adoption and tooling efforts. She was a founding member of Amazon’s first ML research center in Berlin, Germany. Alessya is also the founder of Rsqrd AI, a global community of 1,000+ AI practitioners who are committed to making AI technology Robust & Responsible.