Super Data Science: ML & AI Podcast with Jon Krohn

Jon Krohn
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35 snips
Oct 21, 2025 • 1h 15min

933: Future-Proofing Your Career in the AI Era, feat. Sheamus McGovern

Seamus McGovern, CEO of Open Data Science and founder of the Open Data Science Conference, discusses his journey in building one of the leading AI events. He explores how the evolution of AI roles, from data scientists to specialized AI engineers, is shaping the job market. Seamus emphasizes the importance of continuous learning and adapting skills to keep pace with AI advancements. He predicts the emergence of new roles and highlights the shift towards skills-based hiring, encouraging listeners to embrace change and view AI as an opportunity.
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78 snips
Oct 17, 2025 • 29min

932: Should You Build or Buy Your AI Solution? With Larissa Schneider

Larissa Schneider, Co-founder and COO of Unframe, shares insights on deploying AI solutions effectively. She explores the build-vs-buy dilemma, recommending a hybrid approach: purchase quick-win solutions while developing core IP. Larissa details how Unframe’s modular platform offers no-cost proof-of-concepts and emphasizes the importance of ROI and KPIs in project selection. With a focus on speed, she explains their week-long demo cadence, showing how to ensure success in AI deployments. Larissa also highlights the effects of recent advancements like ChatGPT on business strategies.
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34 snips
Oct 14, 2025 • 1h 13min

931: Boost Your Profits with Mathematical Optimization, feat. Jerry Yurchisin

In this engaging discussion, Jerry Yurchisin, Senior Data Science Strategist at Gurobi, unveils the fascinating world of mathematical optimization. He explains how it differentiates from machine learning and shares intriguing use cases from Toyota and Total Wine. Listeners learn about practical games that illustrate optimization challenges and discover resources to get started with Gurobi. Jerry also touches on the future of quantum computing in optimization, emphasizing the importance of beginning to implement these strategies now for immediate business benefits.
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38 snips
Oct 10, 2025 • 37min

930: In Case You Missed It in September 2025

In a compelling discussion, Aurelian Jaron, an AI consultant and author, dives into the alarming risks of AI misalignment and self-preservation in advanced models. He elaborates on the potential paths to AI Armageddon. Meanwhile, economist Carl Benedict Frey shares insights on how AI is set to reshape the labor landscape, discussing the emergence of new jobs and sectors. Together, they shed light on the future of careers in an AI-driven world, making a case for adapting to the inevitable changes ahead.
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47 snips
Oct 7, 2025 • 1h 14min

929: Dragon Hatchling: The Missing Link Between Transformers and the Brain, with Adrian Kosowski

Join researcher Adrian Kosowski, known for leading the biologically inspired AI architecture at Pathway, as he explores groundbreaking advancements in AI. He dives into how the Dragon Hatchling model merges attention mechanisms with Hebbian learning to mimic brain functions. Discover the concept of unlimited context windows and the innovative sparse positive activations that set BDH apart from traditional transformers. Adrian also discusses the future of multilingual models and the potential for lifelong learning, making AI more human-like in reasoning.
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38 snips
Oct 3, 2025 • 6min

928: The “Lethal Trifecta”: Can AI Agents Ever Be Safe?

Explore the dangers of AI with a focus on the 'lethal trifecta'—private data access, exposure to untrusted inputs, and external communication. Learn how prompt injections can manipulate AI models by following hidden, harmful instructions. Discover real-world incidents illustrating security vulnerabilities and gain insights on dual-model sandboxing to mitigate risks. Jon also shares the Camel Framework for enhanced safety and outlines four best practices for securing AI agents. Engaging discussions highlight the importance of building robust defenses.
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107 snips
Sep 30, 2025 • 1h 19min

927: Automating Code Review with AI, feat. CodeRabbit’s David Loker

David Loker, Director of AI at CodeRabbit, discusses automating code reviews with AI, emphasizing its role in improving developer workflows. He explains how CodeRabbit offers real-time feedback, tackling the challenges of agentic AI and context engineering. Loker shares insights on 'vibe coding', the future of AI creativity, and the importance of privacy with zero-data-retention policies. He also contrasts traditional and modern coding productivity measures, advocating for a holistic approach to developer satisfaction beyond just lines of code.
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30 snips
Sep 26, 2025 • 5min

926: AI is Disrupting the Legal Industry: Are Paralegals Doomed?

AI is transforming the legal landscape by automating contract reviews and legal research. Rather than replacing lawyers, it augments their capabilities, allowing them to focus on more complex tasks. Paralegals are adapting to this shift by becoming legal technologists, managing AI tools and workflows. New roles in compliance and AI regulation are emerging, emphasizing human judgment. Startups like Harvey and CoCounsel are leading the charge in legal AI innovation, signaling a dynamic future for the industry. Embracing these technologies is crucial for staying competitive.
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66 snips
Sep 23, 2025 • 1h 10min

925: AI, Automation and the Future of Work, with Oxford’s Prof. Carl Benedikt Frey

Carl Benedikt Frey, an Oxford economist and researcher, discusses his latest book, How Progress Ends, exploring the relationship between technology and economic systems. He delves into the challenges of job displacement by AI and the role of weak social ties in driving innovation. Frey also highlights the struggle of large incumbents to innovate versus lobby, and suggests ways for workers to future-proof their careers amidst rapid automation. His insights urge a shift in protective policies that focus on people, not just jobs.
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32 snips
Sep 19, 2025 • 5min

924: 95% of Enterprise AI Projects Fail (Per MIT Research)

A recent report reveals that a staggering 95% of enterprise AI projects are failing to deliver returns on massive investments. The findings highlight high pilot adoption rates but dismal scaling success. Critics argue that the figure may be inflated, while successful projects share common traits like learning models and proper integration. The discussion offers insightful strategies on how to navigate the AI landscape effectively and avoid the pitfalls that many businesses face.

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