September 15th, 2022 | Season 1 | 1 hr 45 mins
Hugo speaks with Mark Saroufim, an Applied AI Engineer at Meta who works on PyTorch where his team’s main focus is making it as easy as possible for people to deploy PyTorch in production outside Meta.
August 18th, 2022 | Season 1 | 1 hr 26 mins
Hugo speaks with Sarah Catanzaro, General Partner at Amplify Partners, about investing in data science and machine learning tooling and where we see progress happening in the space.
July 19th, 2022 | Season 1 | 1 hr 41 mins
Hugo speaks with Hamel Husain, Head of Data Science at Outerbounds, with extensive experience in data science consulting, at DataRobot, Airbnb, and Github.
May 16th, 2022 | Season 1 | 1 hr 5 mins
Hugo speaks with Peter Wang, CEO of Anaconda, about what the value proposition of data science actually is, data not as the new oil, but rather data as toxic, nuclear sludge, the fact that data isn’t real (and what we really have are frozen models), and the future promise of data science, Gifting economies with finite game economics thrust onto them.
They also dive into an experimental conversation around open source software development as a model for the development of human civilization, in the context of developing systems that prize local generativity over global extractive principles. If that’s a mouthful, which it was, or an earful, which it may have been, all will be revealed in the conversation.
May 1st, 2022 | Season 1 | 1 hr 2 mins
ai, data science, machine learning, python
Hugo speaks with Peter Wang, CEO of Anaconda, about how Python became so big in data science, machine learning, and AI. They jump into many of the technical and sociological beginnings of Python being used for data science, a history of PyData, the conda distribution, and NUMFOCUS.
April 4th, 2022 | Season 1 | 1 hr 27 mins
Hugo speaks with Jacqueline Nolis, Chief Product Officer at Saturn Cloud (formerly Head of Data Science), about all types of failure modes in data science, ML, and AI, and they delve into bullshit jobs in data science (yes, that’s a technical term, as you’ll find out) –they discuss the elements that are bullshit, the elements that aren’t, and how to increase the ratio of the latter to the former.
March 23rd, 2022 | Season 1 | 1 hr 48 mins
ai, data science, machine learning
Hugo speaks with Jim Savage, the Director of Data Science at Schmidt Futures, about the need for data science in executive training and decision, what data scientists can learn from economists, the perils of "data for good", and why you should always be integrating your loss function over your posterior.
March 9th, 2022 | Season 1 | 1 hr 44 mins
Hugo speaks with Heather Nolis, Principal Machine Learning engineer at T-mobile, about what data science, machine learning, and AI look like at T-mobile, along with Heather’s path from a software development intern there to principal ML engineer running a team of 15.
February 28th, 2022 | Season 1 | 1 hr 32 mins
Hugo speaks with Rachael Tatman about the democratization of natural language processing, conversational AI, and chatbots, including, among other things, the data scientist’s responsibility to end-users and stakeholders.
February 20th, 2022 | Season 1 | 1 hr 45 mins
Hugo talks with Jeremy Howard about the past, present, and future of data science, machine learning, and AI, with a focus on the democratization of deep learning.
February 16th, 2022 | Season 1 | 5 mins 29 secs
In this episode, Hugo introduces the new data science podcast Vanishing Gradients.