500 episodes
Super Data Science: ML & AI Podcast with Jon Krohn Jon Krohn
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- Technology
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5.0 • 1 Rating
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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.
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796: Earth's Coming Population Collapse and How AI Can Help, with Simon Kuestenmacher
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. -
795: Fast-Evolving Data and AI Regulatory Frameworks, with Dr. Gina Guillaume-Joseph
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 (go.aws/3zWS0au) and AWS Trainium (go.aws/3ycV6K0), by Crawlbase (crawlbase.com), the ultimate data crawling platform, and by Babbel (https://www.babbel.com/superdata), 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 -
794: Exciting (and Frightening!) Trends in Open-Source AI
Trends in open-source AI: Join Jon Krohn and a panel of data science icons as they discuss the most exciting and concerning developments in open-source AI. Hear insights from Drew Conway, Jared Lander, Emily Zabor, and JD Long on the transformative potential of AI and its future impact.
Additional materials: www.superdatascience.com/794
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. -
793: Bayesian Methods and Applications, with Alexandre Andorra
Bayesian methods take the spotlight in this episode with Alex Andorra, co-founder of PyMC Labs, and Jon Krohn. Learn how Bayesian techniques handle tough problems, make the most of prior knowledge, and work wonders with limited data. Alex and Jon break down essentials like PyMC, PyStan, and NumPyro libraries, show how to boost model efficiency with PyTensor, and talk about using ArviZ for top-notch diagnostics and visualizations. Plus, get into advanced modeling with Gaussian Processes.
This episode is brought to you by Crawlbase (https://crawlbase.com), the ultimate data crawling platform. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
• Practical introduction to Bayesian statistics [04:54]
• Definition and significance of epistemology [17:52]
• Explanation of PyMC and Monte Carlo methods [27:57]
• How to get started with Bayesian modeling and PyMC [34:26]
• PyMC Labs and its consulting services [50:50]
• ArviZ for post-modeling diagnostics and visualization [01:02:23]
• Gaussian processes and their applications [01:09:02]
Additional materials: www.superdatascience.com/793 -
792: In Case You Missed It in May 2024
Jon Krohn shares his favorite clips from May. Hear how Navdeep Martin is spearheading a company to tackle the climate crisis, why Sol Rashidi and Demetrios Brinkmann find nailing job titles so necessary in the fast-paced industries of tech and AI, and get the latest on embeddings with Luis Serrano.
Additional materials: www.superdatascience.com/792
Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information. -
791: Reinforcement Learning from Human Feedback (RLHF), with Dr. Nathan Lambert
Reinforcement learning through human feedback (RLHF) has come a long way. In this episode, research scientist Nathan Lambert talks to Jon Krohn about the technique’s origins of the technique. He also walks through other ways to fine-tune LLMs, and how he believes generative AI might democratize education.
This episode is brought to you by AWS Inferentia (https://go.aws/3zWS0au) and AWS Trainium (https://go.aws/3ycV6K0), and Crawlbase (https://crawlbase.com), the ultimate data crawling platform. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
• Why it is important that AI is open [03:13]
• The efficacy and scalability of direct preference optimization [07:32]
• Robotics and LLMs [14:32]
• The challenges to aligning reward models with human preferences [23:00]
• How to make sure AI’s decision making on preferences reflect desirable behavior [28:52]
• Why Nathan believes AI is closer to alchemy than science [37:38]
Additional materials: www.superdatascience.com/791