
In the 24th episode of the Data Science Bulletin podcast, hosts delve into a Netflix paper focusing on the GenRec model, an LLM-backed recommendation ranker designed to optimize content recommendations on the platform...


technology
technology · CS
Data Science Bulletin is a podcast about news in space of data science, artificial intelligence and machine learning. We bring you views of people "on the ground", implementing these methods into industry setting. Podcast in Czech, accompanying posts and newsletter in English.
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Contact path
Verified email
Booking probability
30%
Guest openness
Selective
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Signup to Generate a PitchData Science Bulletin is a podcast about news in space of data science, artificial intelligence and machine learning. We bring you views of people "on the ground", implementing these methods into industry setting. Podcast in Czech, accompanying posts and newsletter in English.
Recent episodes include "DSBP #24 [CZ] - GenRec and Reverse Engineering" (26 October 2026, 50 minutes), "DSB Podcast #23 [CZ] - Graph Engineering and Jev" (4 October 2026, 47 minutes), and "DSB Podcast #22 [CZ] - Minimal description Lenght and Harnesses" (10 September 2026, 46 minutes).
Data Science Bulletin publishes roughly monthly, with episodes averaging 43 minutes across 23 episodes.
Booking probability for Data Science Bulletin is 30%, and the host is rated Selective on guests. Data Science Bulletin requires a Pod Score of 80 or higher. Data Science Bulletin's contact route on record: verified email.
The strongest fits for Data Science Bulletin are IT Services & Software Development. Data Science Bulletin has a technology audience.
Data Science Bulletin is a technology podcast with 23 episodes published.
Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

In the 24th episode of the Data Science Bulletin podcast, hosts delve into a Netflix paper focusing on the GenRec model, an LLM-backed recommendation ranker designed to optimize content recommendations on the platform...

In this episode of the Data Science Bulletin podcast, hosts discuss the evolving concept of graph engineering, exploring how it can provide a more structured and deterministic framework for working with AI models...

In this episode of the Data Science Bulletin podcast, hosts delve into the historical significance of AI research by exploring a list of recommended papers, including Geoffrey Hinton's "Keeping Neural Networks Simple by...

Episode #21
In this episode, hosts delve into the concept of "world models" in AI, discussing their potential applications and the debates surrounding their development, particularly focusing on the insights of experts like Jan...

Episode #19
<p>In the nineteenth episode of the Data Science Bulletin podcast, hosts discuss two articles focusing on the influence of large language models and AI on the future of various fields.</p><p>"Something Big is Happening"...

<p>In this episode we discuss the research paper 'Large Language Model Reasoning Failures,' which was published in Transactions on Machine Learning Research. We focus on a categorization framework for identifying...

Episode #17
<p>In the 17th episode of the Data Science Bulletin podcast, hosts delve into a recent paper on "Decepticon," which examines the vulnerability of AI agents to dark patterns on websites, revealing that larger models are...

Episode #16
<p>In the 16th episode of the Data Science Bulletin podcast, hosts Martin and Jakub delve into the intricacies of AI strategies, focusing primarily on the national AI strategy of the Czech Republic and its...

Episode #15
<p>In this episode of the Data Science Bulletin podcast, hosts Martin and Jakub discuss the latest developments in the world of AI, focusing on the release of the GPT-5 model. They share their personal experiences and...

Episode #14
<p>In the 14th episode of the Data Science Bulletin podcast, hosts Martin Münch and Jakub Kramata discuss the latest advancements in AI regulations and infrastructure, focusing on the America's AI Action Plan announced...

Episode #13
<p>In this episode of the Data Science Bulletin Podcast, hosts Martin Münch and Jakub Kramata delve into recent AI reports, including the 2025 AI Index Report, AI Engineering Report, and a boxed State of AI Report. They...

Episode #12
<p>In the 12th episode of the Data Science Bulletin podcast, hosts Martin Münch and Jakub Kramata discuss two intriguing topics. They delve into the recent news of Meta reportedly offering $100 million signing bonuses...

Episode #11
<p>In this episode of Data Science Bulletin, hosts Martin and Jakub, delve into the current state of reasoning models in AI, with a focus on a recent research paper from Apple entitled "The Illusion of Thinking." The...

Episode #10
<p>In the 10th episode of the Data Science Bulletin podcast, Martin and Jakub celebrate reaching this milestone by discussing their journey and roles as team leaders in the data science field at ČSOB. They reflect on...

In this episode, we are joined by Ondra Draganov, a research mathematician at INRIA in France, who shares his 15-year academic path from Prague to Vienna and now to France. Ondra delves into his work in topological data...

Episode #8
This episode we talked about a trip to Darmstadt where PyCon and Pydata DE happend. More about here: https://datasciencebulletin.com/dsb-podcast/dsb-podcast-8-pycon-de/

Episode #7
This episode we dedicated to the material AI-2027. Prediction circulating social networks how the world will look like in 2 years. Accompanying blog post...

Episode #6
In this episode, we dove headfirst into the hotly debated question: Are programmers on the road to extinction, or will coding roles simply evolve? Here’s a concise look at the highlights, insights, and spirited...

Episode #5
Conversation about data science and AI. This episode we went through Klarna story and AI consultanciesSummary and links: https://datasciencebulletin.com/dsb-podcast/dsb-podcast-5/

Episode #4
In the 4th episode we went through topics of 2024 that we found interesting to mention and comment. Summary and links: https://datasciencebulletin.com/dsb-podcast/dsb-podcast-4/
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