Although we like to think about ML workflows as straight-line narratives from experiment to training to production, and then finally monitoring; the reality for large companies is that all the steps are happening at one time in concert with other models, with shifting data, and, sometimes, misaligned key feature inputs. Moreover, regulated firms are required

Mingsheng Hong, is CEO and co-founder (along with Zheng Shao) of Bluesky. He is a thought leader for machine learning and has built data infrastructure to support some of the world’s most challenging workloads. Most recently, Mingsheng was at Google, where he led teams to build storage and querying stacks that power Google’s $100 billion

Show host: Jordi Mon Companys Guest: Dan Lorenc

In this episode we talk with Varun Badhwar, Founder and CEO of Endor Labs. Show host: Sean Falconer Transcript

Show Host: Jordi Mon Companys Guest: Sam Alba Transcript

As applications grow in size and complexity, and as they increasingly move to microservice architectures, it becomes harder for individual developers to perform end-to-end tests of an entire application stack. Connecting development services to production services is off limits. Test environments are limited to automated tests. Staging environments are woefully inadequate with the amount of

Show Host: Jordi Mon Companys Heather Meeker Scott Jenson Pablo Ruiz-Múzquiz Transcript

Transcript

Silicon Valley has many investors and Venture Capital firms, but most are not trying to solve hard technical problems. Engineering Capital partners with companies that are taking a technical risk. These are the companies who have some innovation where there is a doubt on whether it can even be built. Ideally, the market for this

We do it every day. We search on the internet for some information. Many ask, why is that easy? And yet doing the same thing at my company is hard sometimes, not even possible. And when you do get the data, it’s unclear where it’s from or the degree you can trust it or use