Y Carrot

For this episode #1001 special, the tables are turned: SuperDataScience founder Kirill Eremenko takes the host’s chair and Jon Krohn is the guest. They trace Jon Krohn’s path from an Oxford neuroscience PhD to a New York hedge fund to founding the AI consulting firm Y Carrot, why he regrets leaving academia and how tools like Claude Code erased his hard-won technical moat and why that makes skilled engineers more valuable than ever. Along the way: whether AI is a bubble, Jevons paradox and the data-center boom, the RICE framework for choosing AI projects, the single biggest reason AI projects fail and how a well-built AI agent could give anyone “Christopher Nolan–like” focus. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.superdatascience.com/1001⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (03:42) From an Oxford neuroscience PhD to AI consulting (17:25) Defining AGI and why consciousness isn’t required (30:39) Are we in an AI bubble? Why we benefit either way (46:32) Jevons paradox: why cheaper AI means more data centers (01:08:31) The RICE framework for prioritizing AI projects (01:15:08) The number-one reason AI projects fail in production (01:31:50) AI, attention, and protecting your wellbeing

Jon Krohn

Chief Data Scientist

UntaptSuperDataScienceYCY Carrot

Jon Krohn joins us for a year-end episode about 2020’s biggest data science breakthroughs and for a big podcast announcement for 2021. In this episode you will learn: Global warming [4:37] Our big podcast announcement [6:57] Who is Jon Krohn? [12:14] Top 3 technological breakthroughs of the year [21:28] AlphaFold [23:33]• GPUs [45:51] GPT-3 [1:00:26] Wrap up [1:26:40] Additional materials: www.superdatascience.com/429

Jon Krohn

Chief Data Scientist

Untapt

Jon Krohn joins me to discuss his work at untapt in designing models for HR purposes. We also discuss the power of data science across fields of medicine and epidemiology, as well as the future of deep learning. In this episode you will learn: Coronavirus update in New York City [2:36] What brought Jon to New York? [5:38] Data science and coronavirus [12:50] Jon’s work at untapt [18:09] Techniques used to design models in untapt [22:02] untapt’s approach to explainability and bias [30:19] Jon’s other contributions to data science [38:10] Jon’s book and visual teaching styles [44:32] LinkedIn Q&A [52:05] Jon’s recommendation for becoming best at deep learning [1:13:09] Additional materials: www.superdatascience.com/365

Jon Krohn

Chief Data Scientist

Untapt