What is a deep learning architect and the interview process. With Adam Grzywaczewski (NVIDIA)

Here's an interview with Adam Grzywaczewski, the senior deep learning architect at NVIDIA. In this interview, we talk about his role, and the interview process to get into such a role, and we learn more about NVIDIA and more interesting insights from Adam.

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Adam's GTC events:
The Possibilities for Natural Language Processing and Large Language Models in Finance: Insights from Deutsche Bank [S51160]: https://www.nvidia.com/gtc/session-catalog/?ncid=ref-inpa-477072&?tab.catalogallsessionstab=16566177511100015Kus&search=#/session/1666078863989001bkfy
Connect with the Experts: Deep Learning, Machine Learning, and Data Science [CWES52118]: https://www.nvidia.com/gtc/session-catalog/?ncid=ref-inpa-477072&?tab.catalogallsessionstab=16566177511100015Kus&search=#/session/1670255843552001iaMr

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Chapters:
0:00 Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff, I promise.
00:58 Academic background
07:55 You were trying to scale models, but the hardware didn’t allow you?
09:25 Did you really want a Ph.D. or was it just to work on the project you had in mind?
10:14 Did you already have a goal in mind? Like getting a good job
12:41 How are you assessing the candidate’s capabilities before and during the interview?
14:43 If you have a lot of resumes, are there any projects or degrees that are more interesting than others?
17:41 What is the shape and format of the interview?
20:08 What is a deep learning architect?
21:55 Other than scaling. In what areas are you working on?
23:36 Are you part of a team that supports companies using Nvidia’s products?
24:40 Could you go over the details of a specific project you’ve had?
26:41 Which complicated challenges require your help?
28:15 How do people that work with you deal with large models or data sets?
30:47 So the current challenge is mainly to find which tool to use and how to do it in a cost-effective way?
32:30 Will you talk in GTC about how to scale and deploy NLP models?
33:30 What is your day-to-day like at Nvidia?
37:20 Would you say that AI technology is now more insane than it was in 2017?
38:10 How do you keep up with this fast rate of progress?
39:08 As the field is maturing, would you say that you have to be more specific on what you’re doing compared to 5-6 years ago?
40:06 Is the need for specific knowledge more challenging than when you had to have broader knowledge?
42:54 What is your favorite tool to use?
43:04 What internal tools are you using?
47:00 Are you surprised by the fact that open-source technologies are so powerful?
50:16 What is the biggest challenge in just deploying models?
53:33 So the main challenges come with the complexity of the solution and the randomness?

#ai #dlarchitect #nvidia