{"podcast":{"title":"Super Data Science: ML & AI Podcast with Jon Krohn","slug":"super-data-science","podcast_index_feed_id":220402,"rss_url":"https://feeds.megaphone.fm/SUPERDATASCIENCEPTYLTD9836501887","website_url":"https://www.superdatascience.com/podcast","image_url":"https://megaphone.imgix.net/podcasts/efa92454-1c31-11ef-9e30-03596b470c27/image/c3e0edc239c962f8bcd144000fafa5aa.jpeg?ixlib=rails-4.3.1&max-w=3000&max-h=3000&fit=crop&auto=format,compress","author":"Jon Krohn","episode_count":991,"summary":"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.","last_synced_at":null,"page_url":"https://stenobird.com/podcast/super-data-science"},"episode":{"title":"976: NVIDIA’s Nemotron 3 Super: The Perfect LLM for Multi-Agent Systems","slug":"976-nvidia-s-nemotron-3-super-the-perfect-llm-for-multi-agent-systems","published_at":"2026-03-20T11:00:00+00:00","page_url":"https://stenobird.com/podcast/super-data-science/976-nvidia-s-nemotron-3-super-the-perfect-llm-for-multi-agent-systems","show_page_url":"https://stenobird.com/podcast/super-data-science","url":"https://www.podtrac.com/pts/redirect.mp3/chrt.fm/track/E581B9/arttrk.com/p/VI4CS/pscrb.fm/rss/p/traffic.megaphone.fm/SUPERDATASCIENCEPTYLTD5434277099.mp3?updated=1773997714","audio_url":"https://www.podtrac.com/pts/redirect.mp3/chrt.fm/track/E581B9/arttrk.com/p/VI4CS/pscrb.fm/rss/p/traffic.megaphone.fm/SUPERDATASCIENCEPTYLTD5434277099.mp3?updated=1773997714","summary":"NVIDIA just dropped Nemotron 3 Super, a 120-billion-parameter open-weight model that only activates 12 billion parameters at a time and it’s built for the agentic AI era. In this Five-Minute Friday, Jon Krohn breaks down the model’s hybrid Mamba-Transformer architecture, its million-token context window, and why its combination of frontier-class reasoning with blazing-fast throughput matters for anyone building multi-agent systems. Find out how Nemotron 3 Super claimed the #1 spot on the DeepResearch Bench leaderboards, which companies are already adopting it, and where you can start using it today. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/976⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.","meta_description":"NVIDIA just dropped Nemotron 3 Super, a 120-billion-parameter open-weight model that only activates 12 billion parameters at a time and it’s built for the…","key_points":[],"chapters":[],"topics":[],"duration_seconds":612,"processing_state":"failed","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/super-data-science/episodes/976-nvidia-s-nemotron-3-super-the-perfect-llm-for-multi-agent-systems/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/super-data-science/976-nvidia-s-nemotron-3-super-the-perfect-llm-for-multi-agent-systems.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}