Episode description
Episode description
Join us this week for a fascinating conversation on the What’s AI podcast, where Yotam Azriel, co-founder of TensorLeap, shares his fascinating journey, insights, and vision for the future of Explainable AI. Discover what the power of passion, curiosity, and focus can accomplish! Yes, I didn’t mention school or university voluntarily, as Yotam is a successful data scientist… without any formal university degree!
►Yotam Azriel: https://www.linkedin.com/in/yotam-azriel-01a953142/
►Listen on Spotify: https://open.spotify.com/show/4rKRJXaXlClkDyInjHkxq3
►Listen on Apple podcasts: https://podcasts.apple.com/ca/podcast/whats-ai-by-louis-bouchard/id1675099708
►Twitter: https://twitter.com/tensorleap, https://twitter.com/Whats_AI
►Support me on Patreon: https://www.patreon.com/whatsai
►My Newsletter (A new AI application explained weekly to your emails!): https://www.louisbouchard.ai/newsletter/
►Join Our AI Discord: https://discord.gg/learnaitogether
How to start in AI/ML - A Complete Guide: ►https://www.louisbouchard.ai/learnai/
Chapters:
0:00 Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff, I promise.
00:26 Who are you and what’s your background?
04:39 And how did you find that job?
06:14 What would you recommend to someone from a different background who wants to get into the field?
08:23 So would you recommend having some sort of incentive to learn?
10:05 Why do you assume you’re not cut off for academia if you like writing and reading papers?
15:00 What is Tensorleap and what do you do there?
21:28 What is Explainability AI and please give an example of a technique?
27:35 Could you give an example of how an explainability AI technique could help improve or understand the SAM model?
31:39 Would the same explainability AI technique work for different architectures?
36:30 Can we do anything to understand the results of the model better when we work with pre-trained models?
40:20 What are the basics for someone new to the field who wants to get into explainability AI and use it to better understand their model and its results?
42:48 Should everyone creating AI models also be familiar with explainability and be able to understand the decisions of the models they create?
45:21 If the model's explanation is right or not you might need an expert in the specific field?
52:20 Is there a way to better understand models that are used through API’s, their decisions and why they answer the way they did?
56:15 Is the ultimate goal for explainability AI to do anything it can to understand the AI model?
58:50 Did you search into neurosciences and try to implement some of their ideas on artificial networks and vice versa?
01:01:20 How do you see the explainability AI field in 5 years?
01:03:27 What are the possible risks with explainability AI?
01:04:56 Who should use Tensorleap and why?