A few Fridays ago, in Episode #896, I made the case that AI probably isn’t going to take your job anytime soon. AI is, however, being quite disruptive as more and more tasks are automated and there are examples of industries being so disrupted by AI that some folks within the industry need to take note now because, if they don’t adapt, their role — maybe even their whole company — could be at risk.
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Filtering by Tag: SuperDataScience
Landing $200k+ AI Roles: Real Cases from the SuperDataScience Community, with Kirill Eremenko
As we approach episode #900, the original SuperDataScience Podcast host Kirill Eremenko returns to reflect on what leads to the highest-paying opportunities in AI. This is a special one; enjoy!
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 is ideal for anyone looking to advance their data science or A.I. career — or looking to break into a career in this field for the first time.
In today’s episode, Kirill details:
Why employers are still testing A.I. engineers on basic machine learning fundamentals — even for LLM-focused roles.
The surprising reason why staying in data science (as opposed to developing an A.I. specialization) could be the right career move for you.
How one developer discovered the hidden age bias in tech recruiting — and the simple hack to beat it.
The two critical skill areas that separate amateur A.I. engineers from the pros commanding huge salaries.
Why the "back to office" movement could give you a competitive advantage in landing a top A.I. role.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
How to Enable Enterprise AI Transformation, with Strategy Consultant Diane Hare
People, not technical capability, are holding back A.I.'s impact in organizations. In today's episode, Diane Hare explains how to overcome friction and enable strategic A.I. transformation.
Diane:
Founder and CEO of the New York-based strategic consulting firm BizLove, which has been mobilizing key stakeholders to deliver on enterprise-wide priorities (like A.I. initiatives!) at Fortune 100 companies for seven years.
Prior to her seven years leading BizLove, spent seven years at EY, the global professional services giant (they have nearly 400,000 employees) formerly known as Ernst & Young.
Board Member at NANO Nuclear Energy Inc. (NASDAQ: NNE)
Holds and MBA and was captain of a semi-professional women’s soccer team in New York City!
Today’s episode is well-suited to anyone looking to make an impact with A.I. and automation, which I suspect is about every listener to my podcast!
In today’s episode, Diane details:
Why people, not technical capability, are holding back A.I.’s transformative power in organizations.
How to prioritize the items on an enterprise A.I. roadmap.
Why storytelling is essential for gaining buy-in from stakeholders on an A.I. initiative.
Her top five tips for enabling A.I. transformation.
This was a super-cool episode for me because Diane's consultancy, BizLove, is a formal partner of my own consultancy, Y Carrot 🥕. While Y Carrot brings rich technical expertise on A.I. (from development through to production deployment), BizLove naturally complements us with their deep experience enabling digital and A.I. transformations of enterprises. Together, we offer every service organizations need to make lasting, impactful improvements with A.I.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
AI (Probably) Isn’t Taking Your Job (At Least Anytime Soon)
Is AI actually taking jobs? Spoiler alert: the data suggest it's not happening yet, despite all the anxiety out there.
Read MoreWe’re In The AI “Trough of Disillusionment” (and that’s Great!)
Today we're diving into a shift happening in the AI landscape right now — one that might surprise you (and perhaps even be worrying!) given all the hype we've been hearing. While tech giants continue pouring billions into AI infrastructure, many organizations are hitting a wall when it comes to actually implementing AI — particularly generative AI — in meaningful ways. Let's explore what the heck is going on.
Read MoreThe “State of AI” Report 2025
In today’s Five-Minute Friday episode, I’ll cover the five biggest takeaways from the 2025 edition of the renowned AI Index Report, which was published a few weeks ago by the Stanford University Institute for Human-Centered AI. Every year this popular report — often called the “State of AI” report — covers the biggest technical advances, new achievements in benchmarking, investment flowing into AI and more. Here’s a link to the colossal full report in the show notes; today’s episode will cover the five most essential items.
Read MoreManus, DeepSeek and China’s AI Boom
Today, we're diving into the fascinating AI boom that's been sweeping across China since early 2025, examining what this means for the global AI landscape and markets.
Read MoreHow AI is Transforming Baseball (with Lessons For All of Us)
Baseball has always been a game of numbers. For decades, teams have pored over stats like batting averages and ERAs to gain an edge. But in recent years, artificial intelligence has taken baseball analytics to new heights. In today’s episode, we’ll explore how AI is revolutionizing baseball – from scouting and player performance to in-game strategy and even fan experience – and what that means for the future of sports and other industries.
Read MoreMicrosoft’s “Majorana 1” Chip Brings Quantum ML Closer
Microsoft’s Majorana 1 is a newly unveiled quantum computing chip that marks a major breakthrough in the quest for practical quantum computers. It’s the world’s first quantum processor built on a so-called Topological Core architecture – meaning it uses topological qubits (based on exotic Majorana particles that I’ll dig into more shortly) instead of the fragile qubits found in today’s machines. Microsoft believes this innovation could accelerate the timeline for solving real-world, industrial-scale problems with quantum computing from “decades” to just a few years.
Read MoreOpenAI’s “Deep Research”: Get Days of Human Work Done in Minutes
What does Deep Research do?
Read MoreIn Case You Missed It in February 2025
February was another insane month on my podcast. In addition to having stunning smiles, all four guests I hosted are fascinating, highly knowledgeable experts. Today's episode features highlights of my convos with them.
The specific conversation highlights included in today's episode are:
Professional-athlete-turned-data-engineer Colleen Fotsch on how DBT simplifies data modeling and documentation.
Engineer-turned-entrepreneur Vaibhav Gupta on the new programming language, BAML, he created for AI applications. He details how BAML will save you time and a considerable amount of money when calling LLM APIs.
Professor Frank Hutter on how TabPFN, the first deep learning approach to become the state of the art for modeling tabular data (i.e., the structured rows and columns of data that, until now, deep learning was feeble at modeling).
The ebullient Cal Al-Dhubaib on the keys to scaling (and selling!) a thriving data science consultancy.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Bringing Back Extinct Animals like the Wooly Mammoth and Dodo Bird
For this week’s Five-Minute Friday-style episode, I’m diving into a biotechnology story I found mind-blowing: bringing back extinct animals like the wooly mammoth and the dodo bird.
Read MoreOpenAI’s o3-mini: SOTA reasoning and exponentially cheaper
Today’s episode will fill you in on everything you need to know about an important model OpenAI recently released to the public called o3-mini.
Read MoreAre You The Account Executive We’re Looking For?
We’ve never done an episode like today’s… instead of covering a specific data science-related topic, in today’s episode I’m letting you know about a critical role that we’re hiring for on the SuperDataScience Podcast. Perhaps you are the person we’re looking for or you know the person we are looking for!
Read MoreHappy Holidays from the SuperDataScience Podcast
2024 was unquestionably the fastest-moving year yet for A.I. innovation. In particular, we witnessed the meteoric rise of generative AI from its largely-proof-of-concept phase to being commercially indispensable. According to survey results, nearly two-thirds of organizations are now regularly using generative A.I. – a number that has almost doubled since a year earlier. From enhancing product development to facilitating medical breakthroughs, generative AI has become a cornerstone of innovation across industries. For those of who practice data science hands-on, GenAI has proved itself to be near-magical at composing functional code and debugging our errors.
Indeed, as we’ll discuss in detail in next Tuesday’s episode with Sadie St. Lawrence, this year GenAI models crossed reliability and accuracy thresholds, enabling it to power independently acting AI agents, even multi-agent systems that can tackle complex tasks without human supervision. 2025 looks set to be the year Agentic AI takes center stage, the next phase in A.I. transforming every industry and overhauling our way of life; if we get the tricky parts right, then for the better for all of us on this planet.
I hope you’ve enjoyed our exploration of these developments (and much more!) in depth over the course of the year through our podcast episodes, allowing you to hear directly from leading experts and practitioners like Andrew Ng, Bernard Marr and Sol Rashidi. Our discussions have covered a wide range of topics, from the industrialization of data science processes to the ethical considerations surrounding AI implementation.
Through exploring the tricky bits like ethics and equity alongside the breathtaking technological breakthroughs, I hope that overall we’ve left you feeling optimistic about our capacity as a species to get this tech revolution right and have it benefit all of us. This holiday season, I hope you’ll also be able to sit with these positive vibes, get some time away from your screened devices and enjoy the wonder of life — including how lucky we are to be alive at this extraordinary time in history — with your loved ones.
From all of us here at the SuperDataScience Podcast, happy holidays!
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Making Enterprise Data Ready for AI, with Anu Jain and Mahesh Kumar
Today's episode features execs (from fast-growing, VC-backed A.I. startups) Anu Jain and Mahesh Kumar elucidating how enterprises can prepare and manage their data for powerful A.I. applications.
In a bit more detail, today's guests are:
• Anu Jain — CEO of Nexus Cognitive.
• Mahesh Kumar — CMO (with an engineering background and he still writes code!) of Acceldata.
This episode was filmed live at Insight Partners' ScaleUp:AI conference in New York last month.
The episode features highlights of a session I hosted at ScaleUp:AI on "Managing Data to Embrace an A.I.-First Mindset for Enterprises”. It should be interesting to folks looking to make A.I. implementations effective in large organizations that have lots of data.
In the episode, Anu and Mahesh detail:
• How a tiny data error can lead to millions of dollars in losses for an enterprise.
• Why data storage isn't a major cost driver anymore (and what is!)
• What the heck data governance actually is and why it matters.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
In Case You Missed It in November 2024
We had a ton of laughs and I had some seriously mind-expanding moments thanks to my guests on the SuperDataScience Podcast last month. ICYMI, today's episode highlights the most riveting moments from November.
The specific conversation highlights included in today's episode are:
Deepali Vyas, Global Head of Data and A.I. at executive-search giant Korn Ferry, on how A.I. is transforming recruitment and how job-seekers can stay ahead of the curve.
Jess Ramos, data analyst and leading content creator on data careers, on where to start if you yourself are seeking a career in data.
Bryan McCann, co-founder and CTO of the rapidly-scaling A.I. platform You.com, on why machines will make much better scientists than humans... and how they will surpass human scientists surprisingly soon.
Martin Goodson, CEO of the prestigious British A.I. firm Evolution AI, on how the public figures who are speaking most loudly about A.I. are probably not the people we should be listening to.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Delicate Viticultural Robotics
I’ve been excited all year this year about the potential for AI to revolutionize agricultural robotics and help us feed the planet with high-quality nutrition. So, I’m jazzed today to be digging into an innovative application of computer vision and robotics in agriculture, specifically in viticulture — the delicate cultivation of super-expensive grapes for making wine. And, yeah, wine may not provide the world with high-quality nutrition, but the same technologies developed for delicate wine grapes will be transferrable to other plants as well.
Read MoreIn Case You Missed It in August 2024
We had a slew of eye-opening conversations in August on the SuperDataScience Podcast I host. ICYMI, today's episode highlights the most fascinating moments from my convos with them.
Specifically, conversation highlights include:
1. ChainML's Head of A.I. Education Shingai Manjengwa on how multiple, individual A.I. agents can come together to perform complex actions.
2. Renowned futurist and entrepreneur Dr. Daniel Hulme on how A.I. can help us become better and faster at our jobs by circumventing the traditional corporate hierarchies that today seem only to slow us down.
3. Mathematical-optimization guru Jerome Yurchisin (of Gurobi Optimization) on how continuing education will be vital in our increasingly automated work environment... and how this education will be streamlined by A.I.
4. Nick Elprin, Co-Founder and CEO of the wildly successful Domino Data Lab, on why it's essential for enterprises to clearly define their A.I. infrastructure in order for their A.I. deployments to prosper.
Check out today's episode (#818) to hear all these eye-opening conversations. The "Super Data Science Podcast with Jon Krohn" is available on all major podcasting platforms and a video version is on YouTube.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
The AI Scientist: Towards Fully Automated, Open-Ended Scientific Discovery
A team of researchers from Sakana AI, a Japanese AI startup founded last year by Google alumni and that reportedly was valued at over a $1 billion in June, this week published a paper titled "The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery" that is making big waves and could revolutionize how we conduct scientific research.
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