500 episodes
Super Data Science: ML & AI Podcast with Jon Krohn Jon Krohn
-
- Technology
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.
-
788: Multi-Agent Systems: How Teams of LLMs Excel at Complex Tasks
Multi-agent systems could mark a significant turning point in generative AI. From mastering increasingly complex tasks to getting LLMs to collaborate, in this Five-Minute Friday, Jon Krohn discusses the systems that are working to bridge the remaining gaps left by the latest large language models (LLMs).
Additional materials: www.superdatascience.com/788
Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information. -
787: MLOps: The Job and The Key Tools, with Demetrios Brinkmann
MLOps, how to build an online community, and tools for scaling LLMs: In this episode, Demetrios Brinkmann speaks to Jon Krohn about the similarities and differences between LLMOps, MLOps and DevOps, and why this should matter to companies looking to hire such engineers. You will also hear how to get involved in the MLOps community wherever you are in the world, and how you can start developing great products with the available tools.
This episode is brought to you by AWS Inferentia (https://go.aws/3zWS0au) and AWS Trainium (https://go.aws/3ycV6K0). Interested in sponsoring a SuperDataScience Podcast episode? Visit https://passionfroot.me/superdatascience for sponsorship information.
In this episode you will learn:
• What MLOps is [03:51]
• About LLMOps [12:06]
• About LlamaIndex and Ollama [18:29]
• Insights from Demetrios’ MLOps survey [20:49]
• Guidance for using third-party APIs [40:18]
• Recommendations for building an online community in tech and AI [47:07]
Additional materials: www.superdatascience.com/787 -
786: The Six Keys to Data Scientists' Success, with Kirill Eremenko
Learn about the six keys to data science success as host Jon Krohn welcomes back Kirill Eremenko, the mastermind behind SuperDataScience. Kirill shares his top insights on data science careers, from building strong portfolios to leveraging mentors and hands-on labs. With over 2.7 million students, his advice is a must-hear for aspiring and experienced data scientists alike.
Additional materials: www.superdatascience.com/786
Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information. -
785: Math, Quantum ML and Language Embeddings, with Dr. Luis Serrano
Dr. Luis Serrano from the Serrano Academy reveals how to make Math and Quantum ML accessible, tackles the challenges of teaching A.I. to beginners, and explores the power of embeddings in enterprise applications. Explore the future of Quantum Machine Learning and the latest trends in AI, including multimodality and autonomous systems.
This episode is brought to you by AWS Inferentia (https://go.aws/3zWS0au) and AWS Trainium (https://go.aws/3ycV6K0). Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information.
In this episode you will learn:
• How math and AI can be made easy to understand [05:21]
• The three major categories of learners [16:21]
• Why embeddings are the most important component of LLMs [26:19]
• How semantic search differs from a traditional keyword search [29:57]
• The most exciting emerging application areas for AI [42:41]
• The promising application areas for Quantum Machine Learning [49:18]
Additional materials: www.superdatascience.com/785 -
784: Aligning Large Language Models, with Sinan Ozdemir
Aligning LLMs: How can we teach pre-trained LLMs to hold a conversation and learn new information from each other? This was where Sinan Ozdemir began his investigation into aligning LLMs. In this episode, he talks to Jon Krohn about the limitations of definitions for LLMs, training LLMs, and whether it is possible to train an LLM without alignment.
Additional materials: www.superdatascience.com/784
Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information. -
783: Generative A.I. for Solar Power Installation, with Navdeep Martin
Recent advances in GenAI, how to tackle the climate crisis with advanced technology, and addressing the knowledge gap in understanding AI: Jon Krohn speaks to Flypower co-founder and CEO Navdeep Martin about the advances made in GenAI, from products to applications, and how we might use AI to tackle climate change.
This episode is brought to you by AWS Inferentia (https://go.aws/3zWS0au) and AWS Trainium (https://go.aws/3ycV6K0). Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information.
In this episode you will learn:
• How the Washington Post’s recommendation systems work [03:29]
• Why product leaders make great CEOs [10:36]
• How Flypower uses GenAI to tackle climate change [22:13]
• How Flypower identifies its customers’ most pertinent questions [30:03]
• How AI might come to tackle climate change [36:52]
• How to mitigate hallucination in AI models [41:04]
Additional materials: www.superdatascience.com/783