Interview

Exclusive interview with Google DeepMind CEO Demis Hassabis

Good morning, AI enthusiasts. Google’s Gemini 3 is finally here, and it looks like a release that lives as much as the huge hype with latest leaderboard-topping capabilities across the board.We got a probability...

Easy methods to Crack Machine Learning System-Design Interviews

system design interviews are a core a part of the hiring process at firms like Meta, Apple, Reddit, Amazon, Google, Snap, and lots of others. These interviews vary widely — some focus more on software architecture,...

Exclusive interview: Sam Altman on Dev Day and AI’s future

Good morning, AI enthusiasts. Sam Altman just painted an image of the long run, and it's weirder than you think that (but won't feel that way within the moment).Between AI agents working autonomously for...

How I Used ChatGPT to Land My Next Data Science Role

Up to now, I wrote about how recent AI developments are changing data science interview loops from a hiring manager’s perspective.  I went through several interviews myself. Job hunting is at all times stressful....

Exclusive interview: Inside Meta’s AI glasses master plan

Good morning, AI enthusiasts. Meta just unveiled its most ambitious AI glasses lineup yet — including a brand new computing interface: Ray-Ban Displays with an internal screen and a Neural Band controller.We sat down...

“My biggest lesson was realizing that domain expertise matters greater than algorithmic complexity.“

You latterly won $10,000 in a machine learning competition — congratulations! What was the largest lesson you took away from that have, and the way has it shaped your approach to real-world ML problems? My...

“I feel of analysts as data wizards who help their product teams solve problems”

You’ve written extensively about agentic AI and frameworks like smolagents and LangGraph. What excites you most about this emerging space? I first began exploring generative AI largely out of curiosity and, admittedly, a little bit...

Rethinking Data Science Interviews within the Age of AI

AI is rewriting the day-to-day of knowledge scientists. , data scientists must learn improve productivity and unlock recent possibilities with AI. Meanwhile, this transformation also poses a challenge to hiring managers: find...

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