Don’t Fear Going Deeper: Let NVIDIA’s Will Ramey Demystify Deep Learning


you private to search out out about deep studying.

From cell apps on the fingertips of billions to pudgy endeavor applications powering the arena’s biggest companies to a brand current generation of cutting-edge research instruments, deep studying has change into ubiquitous.

That makes spending an hour or in an effort to receive oriented a extra worthwhile investment than ever.

That is where Will Ramey, senior director and worldwide head of developer applications at NVIDIA, and the host of a GTC Digital session called “Deep Finding out Demystified,” is accessible in.

Ramey’s a technologist with a knack for making the basic ideas of deep studying, and its historical past, accessible to other americans whose expertise lies in quite about a fields. And that’s perfect the make of alternative americans who can profit from inserting it to work now.

Ramey spoke with AI Podcast host Noah Kravitz about how NVIDIA developed into an AI firm on story of the invention of the parallel computing platform CUDA, as successfully as the broader articulate of deep studying this day.

Key Parts From This Episode:

  • Ramey offered an outline of the actions readily accessible to developers at GTC Digital, including seven paunchy-day workshops and 15 immediate applications by the first episode — the most streamed to this level — three years within the past to discuss the historical past of the AI improve and the basics of deep studying.
  • Ramey explains how deep studying is extinct to pork up self-riding autos. As a replacement of spending a long time accumulating staunch-world riding records, deep studying permits for simulations that can per chance well even be mosey in parallel, accelerating coaching time.

Learn extra about the developer community that Ramey supports.


“Deep neural networks, they’re a lot increased, they’re deeper — that method they private got heaps extra layers — and require plenty extra records to put together. Being ready to withhold out that work in a purposeful length of time requires something take care of a GPU parallel accelerator.” — Will Ramey [9:31]

“[Deep learning] has made this expertise readily accessible to many, many extra other americans with a lot less domain-particular materials expertise.” — Will Ramey [15:29]

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