Data are beginning to show that entry-level workers are being replaced by AI. There is, however, a clear path forward for junior workers feeling the pinch! Read on:
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Filtering by Category: SuperDataScience
Future-Proofing Your Career in the AI Era, feat. Sheamus McGovern
Feel like A.I. is transforming your role so rapidly you can't keep up? Fear no more! Today, Sheamus McGovern — founder of the world's biggest data-science conference — has solutions for you.
More on Sheamus:
Ten years ago founded the world-leading Open Data Science Conference (ODSC) — don't miss ODSC AI West in San Francisco next week!
Also serves as Venture Partner and Head of A.I. at Cortical Ventures.
Prior to ODSC, was a data engineer, software architect and A.I. expert., particularly in finance, including quant hedge funds.
Holds an electrical engineering degree from Northeastern University and a graduate computer science degree from Boston University.
Today's episode is accessible to anyone keen to thrive in the A.I. era. Hands-on practitioners like data scientists, software developers and A.I. engineers will find it particularly valuable.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Should You Build or Buy Your AI Solution? With Larissa Schneider
Larissa Schneider's startup Unframe AI has raised $50m to bring A.I. solutions to businesses of all sizes. In today's wildly informative episode, she reveals exactly when you should build versus buy A.I.
More on Larissa:
Co-Founder and COO of Unframe, leading global strategy and operations.
Decade of experience in enterprise tech, having driven strategic growth and partnerships for fast-scaling organizations through IPO and M&A.
Today's episode is an exceptional one that you shouldn't miss! Whatever your role, if you are interested in building commercially successful A.I. systems, you will be delighted you did.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
How We 10X'd Our Podcast's YouTube Watch Time in 3 Months
Today, my podcast's YouTube hit 100,000 subscribers. I'm way more excited, however, about this chart: We 10X'ed our watch time from ~100 hours per day to >1000 hours per day in 3 months. Here's how:
Read MoreBoost Your Profits with Mathematical Optimization, feat. Jerry Yurchisin
Mathematical Optimization (unlike A.I., Machine Learning or Statistics!) is *uniquely* capable of solving real-world problems like maximizing profit. In today's episode, guru Jerome Yurchisin explains how.
More on Jerry:
• Over a decade of experience in operations research and data science.
• Specializes in enhancing commercial/industrial decision-making.
• Before joining Gurobi Optimization, worked in consulting (OnLocation and Booz Allen Hamilton).
• Prior to that, taught math at the University of North Carolina at Chapel Hill.
Today's episode will be particularly appealing to hands-on practitioners but, leveraging his extensive education background, Jerry excels at explaining complex topics so anyone looking to understand how Mathematical Optimization can make your business more profitable should listen in.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
In Case You Missed It in September 2025
The guests we had on my show in September were *extra* extraordinary. ICYMI, today's episode highlights the best parts of my convos with them:
1. Aurélien Géron, the bestselling ML author of all time, on why AGI may resist human control.
2. Shirish Gupta and Ishan Shah on how to make an A.I. hardware purchase that will still be relevant five years from now.
3. Renowned University of Oxford economics professor Carl Benedikt Frey on whether A.I. could allow for a billion-dollar company with a single employee.
4. David Loker on how CodeRabbit makes A.I. code-reviews more secure than with humans alone.
5. Graph guru Amy Hodler on the future of graph networks, including causal and multimodal functionality.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Dragon Hatchling: The Missing Link Between Transformers and the Brain, with Adrian Kosowski
What do dragons, macarons and potato latkes have in common? They've sparked a revolutionary model that's poised to replace the Transformer. Today, Adrian Kosowski reveals this big breakthrough.
Adrian:
• Chief Scientific Officer and co-founder of Pathway.
• Theoretical computer scientist, quantum physicist and mathematician.
• Earned his PhD at 20 years old and went on to serve as a tenured researcher at Inria at 23 and associate professor at École Polytechnique.
• Has authored more than 100 scientific papers spanning graph algorithms, distributed systems, quantum information and A.I.
In today's highly technical episode, Adrian demonstrates how the Pathway team have brought devised the Baby Dragon Hatching (BDH) architecture, thereby allowing attention in LLMs to function more like the way the biological brain functions. This is revolutionary because (relative to the today-ubiquitous Transformer architecture) BDH allows:
• Reasoning to be generalized across more complex and extended reasoning patterns, approximating a more human-like approach to problem-solving.
• Saving time/compute/money through sparse activation at inference time.
• Allowing for more interpretability.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
The “Lethal Trifecta”: Can AI Agents Ever Be Safe?
The "Lethal Trifecta": There are three factors in agentic A.I. systems that may mean they will never be safe in production. I summarize them and provide potential solutions below.
Read MoreAutomating Code Review with AI, feat. CodeRabbit’s David Loker
Today, enjoy hearing from the super-intelligent engineer David Loker on how A.I. transforming software development by dramatically accelerating code reviews and automatically improving code bases. It's a great one!
(He also, like me, is a big fan of GPT-5... hear why later in the episode.)
More on David:
• Director of A.I. at CodeRabbit (who've raised $88m in venture capital including a $60m Series B a couple weeks ago, congrats!)
• Previously Lead Data Scientist, ML Engineer and Senior Software Engineer at firms like Netflix and Amazon.
• Holds a Master of Mathematics in Computer Science from the University of Waterloo.
Today's episode will be particularly appealing to software developers and other hands-on practitioners (data scientists, ML engineers, etc.) but David is an outstanding communicator of complex info so any interested listener will enjoy it.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
AI is Disrupting the Legal Industry: Are Paralegals Doomed?
In recent months, I had popular episodes on how A.I. is automating and disrupting the advertising and journalism industries. Today, I'm giving the legal profession the treatment.
Read More95% of Enterprise AI Projects Fail (Per MIT Research)
According to a recent study by researchers at MIT, 95% of enterprise A.I. projects fail. Why? And how can we be amongst the 5% that succeed?
Read MoreGraph Algorithms, GraphRAG and Causal Graphs, with Graph Guru Amy Hodler
For *years*, I'd been trying to get Amy Hodler on my show. Finally she's here! A graph-network guru, Amy fills us in on graph algorithms and cutting-edge applications like GraphRAG and Causal Graphs. Enjoy!
More on Amy:
Graph-tech evangelist and co-author of O'Reilly books on Graph Algorithms and Knowledge Graphs.
Decades of experience in emerging tech at companies like HP, Hitachi, Neo4j, and Cray.
Founder of GraphGeeks.org, a community for people passionate about graphs and connected data.
Today's episode will probably appeal most to hands-on data/AI practitioners but Amy is such a tremendous communicator that anyone who wants to know the latest on graph networks (and their powerful real-world use-cases!) will enjoy it.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
AI for Manufacturing and Industry, with Hugo Dozois-Caouette
Today's episode is all about the *vast* opportunities for applying A.I. to industrial applications such as manufacturing. Our guide is Hugo Dozois-Caouette, co-founder and CTO of MaintainX.
Hugo:
Co-founded MaintainX, a CMMS ("Computerized Maintenance Management System") back in 2018, steering the firm to tremendous success, including a recent $2.5 billion valuation and a total of over $250m in venture capital raised.
Previously served as Lead Software Engineer at Autodesk and Fujitsu.
Holds a B.Eng. in Computer Engineering from the Université de Sherbrooke in Quebec.
Today's episode is mostly high-level and so should be fascinating to any listener. I was blown away by the data volumes created by manufacturing and how untapped A.I. applications are there.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
NPUs vs GPUs vs CPUs for Local AI Workloads, with Dell’s Ish Shah and Shirish Gupta
Double the laughs in today's episode, with *two* hardware experts from Dell joining me to explain when you should process A.I. workloads locally with a CPU, GPU or Neural Processing Unit (NPU).
Guest #1, Ishan Shah, is:
Technologist in the Office of the CTO for Dell Technologies’ Client Solutions Group.
Was previously founding member of Dell's Chief A.I. Office.
Holds an MBA from the Massachusetts Institute of Technology.
Guest #2, Shirish Gupta:
Director of A.I. Product Management at Dell, where he's been for 20+ years!
Holds a Master's in Engineering from the University of Maryland.
Today's episode will appeal to all hands-on A.I. practitioners as well as anyone who makes hardware decisions for A.I. practitioners. It's also simply a ton of fun to listen to — Ish and Shirish play off each other very amusingly :)
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
In Case You Missed It in August 2025
ICYMI, today's episode provides the top moments from conversations I had with my podcast guests in August. Interestingly, in August all of these episodes took off on YouTube in an unprecedented way:
Julien Launay, co-founder and CEO of the wildly successful Adaptive ML, explains how LLMs are trained including the pre-training and the increasingly critical post-training phases.
Michelle Yi provides her brilliant take on shocking misalignment research from Anthropic, which showed that A.I. agents will frequently resort to blackmailing humans when its goals are threatened.
Kirill Eremenko, CEO of the learning platform SuperDataScience, describes what it takes to become an A.I. Engineer.
And Akshay Agrawal who explains how his rapidly-adopted marimo notebook can be converted into a full-blown, click-and-point web app in *seconds*.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Hopes and Fears of AGI, with All-Time Bestselling ML Author Aurélien Géron
Aurélien Géron is the best-selling author of ML books of all time. Today's episode is his first interview in a *decade*... and it's a stunner! He reveals his next book as well as his deep thoughts on AGI.
Aurélien:
Is the author of O'Reilly's "Hands-On Machine Learning" series of books. The fourth edition in the series will be on bookshelves in the coming months.
Was Co-Founder and CTO of Wifirst, an exceptionally successful French tech company.
Was previously a product manager at Google.
Holds an MEng in Computer Science from AgroParisTech.
The start of today's episode (on Aurélien's books) may appeal primarily to hands-on practitioners like data scientists and software developers. The bulk of the episode, however, will appeal to anyone looking to understand how Artificial General Intelligence (AGI) will overhaul work, life and society for humans.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Multi-Agent Systems with CrewAI
Today’s episode is a crisp overview of multi-agent systems and specifically CrewAI, an extremely popular framework for creating and managing multi-agent teams: I’ll cover what CrewAI is, how it works, a few concrete use cases, a quick comparison to earlier agent frameworks, and why it matters for your workflow. All right, let’s jump in!
Read More8 Steps to Becoming an AI Engineer, with Kirill Eremenko
The #1 fastest-growing role in many countries (including the US) is A.I. Engineer. Want to become one? ...or add the skillset into your existing role? Today, Kirill Eremenko provides an 8-step roadmap!
Many of you will already know Kirill:
Founder and CEO of SuperDataScience.com, the eponymous e-learning platform.
Founded the SuperDataScience Podcast nine years ago and hosted the show until he passed me the reins five years ago.
With over 3 million students, he’s the most popular data science and A.I. instructor on Udemy.
He holds a Master’s from The University of Queensland in Australia and a Bachelor’s in Applied Physics and Mathematics from the Moscow Institute of Physics and Technology.
Today's episode will be of primary interest to hands-on practitioners like data scientists and software developers.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
The 5 Key GPT-5 Takeaways
In today’s episode, I’m providing you with the five most important takeaways from the release of OpenAI’s long-anticipated GPT-5 model.
Read MoreHow to Jailbreak LLMs (and How to Prevent It), with Michelle Yi
Today, extraordinary Michelle Yi details LLM jailbreaking (as well as data poisoning, prompt stealing and slop squatting!) and how to prevent it. Scary content but she makes it funny and entertaining, enjoy!
When I say "extraordinary", I'm not exaggerating. Michelle:
Finished her undergrad at the same age as most folks finish high school.
While working full-time as an engineering lead at IBM on Jeopardy-playing Watson, she was also a professional violinist in the New York Philharmonic!
In the past decade, has held a impressive list of AI leadership roles at Bay Area startups.
Now is helping (startlingly underrepresented) women in tech startups and venture capital through co-founding Generationship, being a venture partner in (ironically named) The Tech Bros and a board member for Women In Data™️.
Today's episode skews a bit toward hands-on practitioners but Michelle does such a wonderful job of communicating complex concepts and making them relevant to modern global events that anyone might love this episode.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.