Andriy Burkov's ML books are mega-bestsellers and his newsletter has a wild 900,000 subscribers. He seldom does interviews so don't miss today's episode, in which he takes compelling, contrarian views on LLMs and agents.

More on Dr. Burkov:

His indispensable "100-Page Machine Learning Book" seems to be on *every* data scientist / ML engineer's bookshelf.
He also wrote "ML Engineering" and his latest book, "The 100-Page Language Model Book", was released this year to rave reviews.
His "Artificial Intelligence" newsletter is subscribed to by 900,000 people on LinkedIn.
He's the Machine Learning Lead at TalentNeuron, a global labor-market analytics provider.
He runs his own book-publishing company, True Positive Inc.
Previously held data science / ML roles at Gartner, Fujitsu and more.
Holds a PhD in Computer Science (A.I.) from Université Laval in Quebec, where his doctoral dissertation focused on multi-agent decision-making — 15 years ago!

Despite Dr. Burkov being such a technical individual, most of today’s episode should appeal to anyone interested in A.I. (although some parts here and there will be particularly appealing to hands-on machine-learning practitioners).

In today’s episode, Andriy details:

Why he believes AI agents are destined to fail.
How he managed to create a chatbot that never hallucinates — by deliberately avoiding LLMs.
Why he thinks DeepSeek AI crushed Bay Area A.I. leaders like OpenAI and Anthropic.
What makes human intelligence unique from all other animals and why A.I. researchers need to crack this in order to attain human-level intelligence in machines.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.