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Super Data Science: ML & AI Podcast with Jon Krohn
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Super Data Science: ML & AI Podcast with Jon Krohn

Author: Jon Krohn

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The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.


Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.


We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

815 Episodes
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As summer winds down, this episode shifts focus from the usual tech discussions to something more personal: reflecting on the importance of balancing work with life’s simple pleasures. While the world of data science and AI continues to evolve rapidly, it's essential to remember that true success isn't just about professional milestones. It’s also about cherishing the moments that make life meaningful. Tune in for a brief but impactful reflection on how to redefine success to include not just achievements, but also the everyday joys that often go unnoticed. Additional materials: www.superdatascience.com/814  Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
Jerry Yurchisin from Gurobi joins Jon Krohn to break down mathematical optimization, showing why it often outshines machine learning for real-world challenges. Find out how innovations like NVIDIA’s latest CPUs are speeding up solutions to problems like the Traveling Salesman in seconds. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • The Burrito Optimization Game and mathematical optimization use cases [03:36] • Key differences between machine learning and mathematical optimization [05:45] • How mathematical optimization is ideal for real-world constraints [13:50] • Gurobi’s APIs and the ease of integrating them [21:33] • How LLMs like GPT-4 can help with optimization problems [39:39] • Why integer variables are so complex to model [01:02:37] • NP-hard problems [01:11:01] • The history of optimization and its early applications [01:26:23] Additional materials: www.superdatascience.com/813
In this episode of Five-Minute Friday, Jon Krohn investigates published findings from the startup Sakana AI and its paper’s co-authors from the University of Oxford, the University of British Columbia and the Vector Institute in Toronto. These authors explore the potential of The AI Scientist, a framework that could change the way we conduct scientific research forever. Additional materials: www.superdatascience.com/812  Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
Nick Elprin talks to Jon Krohn about how and when to scale a data science team and its workflows to secure a company’s commercial viability. You’ll also hear how to launch your own data science startup and why it’s so important to understand that AI tools are not one-size-fits-all. This episode is brought to you by AWS Inferentia and AWS Trainium. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • How Nick served enterprises with his AI startup, Domino Data Lab [05:36] • About the Navy’s own mine detection models [17:43] • The hype surrounding GenAI [30:35] • How AI platforms integrate with business strategies [39:49] • When it’s time to integrate an AI tool into your business [51:12] • Why Nick started Domino Data Lab [1:03:53] Additional materials: www.superdatascience.com/811
Self-driving cars are here, and Jon Krohn is breaking down the five levels of automation that could change driving forever. From full human control at Level 0 to cars that drive themselves in any condition at Level 5, get the real story on what these levels mean. With firsthand insights from a recent autonomous vehicle experience, this episode cuts through the buzz and tells you what’s coming next. Additional materials: www.superdatascience.com/810  Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
Agentic AI is revolutionizing the tech landscape, and Shingai Manjengwa from ChainML is here to tell us why. Discover how AI agents are becoming an integral part of our lives, automating tasks like travel bookings and daily inspiration. Shingai explains the power of multi-agent systems, where AI agents collaborate to solve complex challenges, and highlights how blockchain technology is enhancing AI transparency and trust. Plus, get an inside look at ChainML’s innovative Theoriq protocol and the groundbreaking Council Analytics tool. This episode is brought to you by Gurobi, the Decision Intelligence Leader, and by ODSC, the Open Data Science Conference. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • What A.I. agents are [10:51] • How blockchain technology helps humans trust A.I. agents [18:27] • The Theoriq protocol developed by ChainML [34:05] • How Council Analytics lets you “speak” to their dataset with natural language [39:00] • A future of multi-agent systems [50:42] • Challenges and risks associated with agentic AI [1:04:17] Additional materials: www.superdatascience.com/809
Advice for emerging data scientists, the latest in model merging, and how GenAI can supercharge your creativity: Host Jon Krohn gives us his highlights from a month of interviews, packed with tips from some of the leading names in data science and beyond. Guests include Daliana Liu, Charles Duhigg, Charles Goddard, Rosanne Liu and Andrey Kurenkov. Additional materials: www.superdatascience.com/808  Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
The singularity could soon be upon us. The PESTLE framework, developed by this episode’s guest Daniel Hulme, expresses not one but six types of singularity that could occur: political, environmental, social, technological, legal and economic. Jon Krohn and Daniel Hulme discuss how each of these singularities could bring good to the world, aligning with human interests and pushing forward progress. They also talk about neuromorphic computing, machine consciousness, and applying AI at work. This episode is brought to you by AWS Inferentia and AWS Trainium, and by Gurobi, the Decision Intelligence Leader. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • About the six singularities [03:43] • How the singularity could improve life on earth [09:01] • The credibility of AI experts [32:51] • How the decentralization of technology could benefit earth [43:14] • How AI might enhance creativity [1:04:33] Additional materials: www.superdatascience.com/807
Llama 3.1 is here, and it’s a game-changer. Meta’s latest AI model, especially the massive 405B variant, finally brings an open-source option to compete with giants like OpenAI's GPT-4o and Anthropic's Claude 3.5 Sonnet. While Meta didn’t fully open-source everything, the availability of "open weights" is a strategic move to shake up the AI landscape. The model boasts an impressive 128,000-token context window and multilingual support in eight languages. Meta is also focusing on responsible AI development with tools like Llama Guard 3 for content moderation. This release is more than just a tech upgrade—it's about democratizing AI and sparking innovation across industries. How will you leverage Llama 3.1 to make a real impact? Tune into this week’s FMF episode and let’s explore the future with this latest AI development together. Additional materials: www.superdatascience.com/806 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
Become a Supercommunicator! New York Times bestselling author Charles Duhigg, known for The Power of Habit and Smarter Faster Better, gets real about mastering communication in this episode. Discover insights from his latest book, Supercommunicator, where he reveals how to align conversation styles for deeper connections, handle conflicts effectively, and why AI can't replicate the emotional depth of human interactions. This episode is brought to you by Gurobi, the Decision Intelligence Leader. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • The inspirations behind Supercommunicator [03:41] • The three types of conversations: Practical, emotional, and social conversations [05:22] • The matching principle: Align communication styles for better connection [10:36] • What is neural entrainment: Achieve a mind meld through synchronized brain activity [13:22] • The series of steps/principles to connect with someone [24:39] • How to avoid or de-escalate conflict conversations [31:07] • The impact of GenAI on conversations: How AI mimics dialogue but lacks emotional depth [45:24] Additional materials: www.superdatascience.com/805
Solar power now provides 6% of the world's electricity, thanks to rapid growth. Host Jon Krohn discusses the factors driving this rise, the challenges ahead, and how AI and data science are optimizing solar technologies. Tune in for insights on the future of solar power, and don't forget to like, share, and subscribe! Additional materials: www.superdatascience.com/804 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
Daliana Liu is a big name in data science teaching, and she has always been generous in sharing everything she knows about getting a job in data science. In this episode, she continues to extend her generosity, helping listeners define their approach to achieving a fulfilling career in data science and tech. This episode is brought to you by AWS Inferentia and AWS Trainium, by Babbel, the science-backed language-learning platform, and by Gurobi, the Decision Intelligence Leader. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • Common career challenges for data scientists [34:57] • Advice for people who don’t know where to go in their career [48:05] • How to build resilience and protect against Imposter Syndrome [1:06:23] • Skills that data scientists should develop today [1:39:17] • The future of the data science and AI job market [1:46:55] Additional materials: www.superdatascience.com/803
How to grab investor interest with your AI startup idea, revisiting algorithms, and helping practitioners ensure AI safety with regulatory frameworks and beyond: This month, you missed a whole bunch of great interviews. But don’t worry, Jon Krohn is here to recap all the best bits for you! Additional materials: www.superdatascience.com/802 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
Merged LLMs are the future, and we’re exploring how with Mark McQuade and Charles Goddard from Arcee AI on this episode with Jon Krohn. Learn how to combine multiple LLMs without adding bulk, train more efficiently, and dive into different expert approaches. Discover how smaller models can outperform larger ones and leverage open-source projects for big enterprise wins. This episode is packed with must-know insights for data scientists and ML engineers. Don’t miss out! Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • Explanation of Charles' job title: Chief of Frontier Research [03:31] • Model Merging Technology combining multiple LLMs without increasing size [04:43] • Using MergeKit for model merging [14:49] • Evolutionary Model Merging using evolutionary algorithms [22:55] • Commercial applications and success stories [28:10] • Comparison of Mixture of Experts (MoE) vs. Mixture of Agents [37:57] • Spectrum Project for efficient training by targeting specific modules [54:28] • Future of Small Language Models (SLMs) and their advantages [01:01:22] Additional materials: www.superdatascience.com/801
The SuperDataScience Podcast is celebrating its 800th episode! Host Jon Krohn speaks to his grandmother, Annie, about growing up at a time when so many technologies we take for granted today were yet to be developed. Listen in to hear Annie’s experience of the changes in technology across 94 years and how she and her family fared in 1940s Ukraine with no electricity or running water. Additional materials: www.superdatascience.com/800
No-code games with GenAI, the creative possibilities of LLMs, and our proximity to AGI: In this episode, Jon Krohn talks to Andrey Kurenkov about what turned him from an AGI skeptic to a positivist. You’ll also hear about his wildly popular podcast “Last Week in AI” and how the NVIDIA-backed startup Astrocade is helping videogame enthusiasts to create their own games through generative AI. A must-listen! This episode is brought to you by AWS Inferentia and AWS Trainium. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • All about The Gradient and Last Week in AI [10:42] • All about Astrocade and Andrey’s role at the startup [24:35] • Balancing UX and creative control at Astrocade [42:00] • The creative possibilities of LLMs [1:04:15] • The rapid emergence of AGI [1:10:31] Additional materials: www.superdatascience.com/799
Claude 3.5 Sonnet, Anthropic’s newest model, is making waves in the AI community. This mid-size model outshines the larger Claude 3 Opus in tasks like code generation, content creation, and document summarization, and it’s twice as fast. In this episode of The Super Data Science Podcast, Jon Krohn discusses its top-notch performance across benchmarks like MMLU, GPQA, and HumanEval, along with its improved machine vision capabilities. Plus, learn about the new Artifacts UI feature, which makes managing generated content easier by displaying outputs side-by-side with inputs. Tune in to find out why Claude 3.5 Sonnet is setting new standards in AI. Additional materials: www.superdatascience.com/798 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
Dr. Rosanne Liu, Research Scientist at Google DeepMind and co-founder of the ML Collective, shares her journey and the mission to democratize AI research. She explains her pioneering work on intrinsic dimensions in deep learning and the advantages of curiosity-driven research. Jon and Dr. Liu also explore the complexities of understanding powerful AI models, the specifics of character-aware text encoding, and the significant impact of diversity, equity, and inclusion in the ML community. With publications in NeurIPS, ICLR, ICML, and Science, Dr. Liu offers her expertise and vision for the future of machine learning. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • How the ML Collective came about [03:31] • The concept of a failure CV [16:12] • ML Collective research topics [19:03] • How Dr. Liu's work on the “intrinsic dimension” of deep learning models inspired the now-standard LoRA approach to fine-tuning LLMs [21:28] • The pros and cons of curiosity-driven vs. goal-driven ML research [29:08] • Discussion on Dr. Liu's research and papers [33:17] • Character-aware vs. character-blind text encoding [54:59] • The positive impacts of diversity, equity, and inclusion in the ML community [57:51] Additional materials: www.superdatascience.com/797
Want to feel optimistic about your day? In this Friday episode, Simon Kuestenmacher talks to Jon Krohn about demography: What it is, why it’s so important, and why its forecasts should give us reason to hope for a better future. In an increasingly globalized world, and with an aging population in countries with the biggest GDPs, demography is more valuable than ever. Additional materials: www.superdatascience.com/796 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
Gina Guillaume-Joseph talks to Jon Krohn about the data and regulatory frameworks set to transform the AI industry and why that’s important to anyone working with data. This episode offers a solid path to understanding AI regulation’s past, present and future. Gina walks listeners through the AI Bill of Rights, the NIST AI Risk Framework and the MITRE ATLAS threat model. This episode is brought to you by AWS Inferentia and AWS Trainium, by Crawlbase, the ultimate data crawling platform, and by Babbel, the science-backed language-learning platform. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • What “responsible AI” means [08:14] • Why the federal government should be behind AI regulation [12:22] • The US vs EU on AI regulation [18:46] • About the AI Bill of Rights [26:14] • About MITRE and the MITRE Atlas [37:19] • What a systems engineer does [54:11] Additional materials: www.superdatascience.com/795
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Comments (29)

atefeh

thank you for this episode.

Mar 5th
Reply (1)

mrs rime

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Jan 16th
Reply

Priya Dharshini

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Jan 16th
Reply

Andrew Miller

I found this podcast really helpful for anyone who wants to better their knowledge of machine learning. I am especially interested in the data processing. If you want to deepen your knowledge of this topic, check this article https://techlogitic.net/categorization-and-data-labeling-for-supervised-machine-learning/. It has some pretty useful information and professional tips from experts in data annotation and tagging.

Apr 21st
Reply

Toben Nelson

a really nice and quick overview with just the right amount of detail.

Mar 3rd
Reply

Maryam Alizadeh

great thanks to you and your endeavors for this pod. I learnt a lot. welcome to Jon , wish you the best 👏👍

Jan 4th
Reply

Maryam Alizadeh

😢

Jan 4th
Reply

Masoud Fard

you are the best

Nov 19th
Reply

Nikhil Parmar

nice summarisation, Data Analyts looks at the past and data scientist looks at past and future

Oct 27th
Reply

Tough Nut

Great talk, very inspiring. thanks.

Aug 6th
Reply

Venkat M

Sleeps 3 hrs a day, not a good example for healthy person. sleep well and keep the brain more refreshed and healthy. #health

Mar 13th
Reply

Mehrdad Salimi

a lot of extra, unrelated stuff. Dude I appreciate your effort but you need to be specific and respect audiences' time.

Jan 19th
Reply

Maria Lacerda

Eu não conhecia Gabriela de Queiroz mas agora ouvindo esse podcast (já ouvi umas 5x) estou completamente encantada. Muito legal descobrir esse nível de profissional pelo mundo e ainda saber que trata-se de uma brasileira.

Dec 2nd
Reply

Natalia Zawadzka

Great job!👍 It's so interesting to listen your podcasts! thanks for sharing your knowledge and helping people to get into data business 🙌👍

Sep 10th
Reply

SriLatha K

Hi thanks for doing this podcast. Being a data engineer and who commutes a lot, I gain a lot from your podcasts. One suggestion that I would like to give is, it would be better if you do not interrupt the speaker until they complete their flow.

May 10th
Reply

Alberto Andrade

What amazing episode! Adrian rocks!! Congratulations!

Apr 25th
Reply

Simon SOUVANNARAT

Thanks for this advice !

Feb 6th
Reply

Troy Kirin

Great episode! I wish he touched on how to connect Sparklyr to data viz like Tableau!

Dec 10th
Reply

Richard Leyshon

thought this was one of my stoic podcast episodes! Great message.

Dec 1st
Reply

Ari Meier

Great episode! I'd love to access the show notes, but is having an issue pulling up the link.

Nov 10th
Reply