How are data and next-generation computing technologies transforming our world? Who are the inventors, the business leaders, and the rebels and scientists at the heart of the AI revolution? On Numerically Speaking, we dive into data, quantitative computing, and business and entrepreneurship as we speak to creators of cutting-edge open-source tools and look at their impact on research in every domain. We're excited to bring you insights about data, science, and the people that make it all happen.
End users who are not schooled in hardware can often default to, “just give me something that works.” David Liu, Staff AI Engineer, Strategy & Vision for Data Science and AI Products at Intel, understands this thinking but also believes that end users can be educated on the advantages of configuring their computer hardware to suit their specific needs.
David advocates for using the right hardware for a given task—and that may mean different configurations and/or different machines for different tasks, rather than a one-size-fits-all solution.
Past Episodes
Machine learning (ML) has reached an exciting phase of development, a phase that Vicki Boykis, Senior ML Engineer at Duo Security* has characterized as the “steam-powered days.” In this episode of Numerically Speaking: The Anaconda Podcast, Vicki talks about the state of the industry and where she sees things heading.
*At the time of the interview, Vicki Boykis was an ML Engineer working on Tumblr at Automattic.
Joining us for this episode is James Cham, Partner at Bloomberg Beta. Bloomberg Beta runs several seed-stage investment funds, with a particular interest in low-code/no-code/WebAssembly startups.
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