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Artwork for The Information Bottleneck

The Information Bottleneck

Ravid Shwartz-Ziv & Allen Roush
Artificial Intelligence
Machine Learning
Openai
Large Language Models
AI Research
Generative AI
Data Curation
Language Models
Reinforcement Learning
Textai
Gpt-5
AI Coding
Joint Embedding Predictive Architectures
Natural Language Processing
Reasoning Models
NVIDIA
Local-First AI
Semantic Search
Artificial General Intelligence
Cursor

Two AI Researchers - Ravid Shwartz Ziv, and Allen Roush, discuss the latest trends, news, and research within Generative AI, LLMs, GPUs, and Cloud Systems.

PublishesWeeklyEpisodes38Founded9 months ago
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ScienceTechnology

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Artwork for The Information Bottleneck

Latest Episodes

We host Chieh-Hsin (Jesse) Lai, Staff Research Scientist at Sony AI and visiting professor at National Yang Ming Chiao Tung University, Taiwan, for a conversation about diffusion models, the technology behind tools like Stable Diffusion, and most of ... more

YouTube

We talked with Christian Szegedy, co-inventor of Inception and Batch Normalization, founding scientist at xAI, now at Math Inc, about what it takes to build a frontier lab, and why he left xAI to work on formal mathematics. Christian thinks Lean and ... more

YouTube

We sat down with Rao Kambhampati, a Professor of CS at Arizona State University and former President of AAAI, to talk about reasoning models: what they are, when they work, and when they break.

Rao has been working on planning and decision-making si... more

YouTube

In this episode, we hosted Zhuang Liu, Assistant Professor at Princeton and former researcher at Meta, for a conversation about what actually matters in modern AI and what turns out to be a historical accident.

Zhuang is behind some of the most impo... more

YouTube

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Recent Guests

Christian Szegedy
AI researcher, co-inventor of Inception and batch normalization; co-founder of XAI and Math Inc
Math Inc; XAI
Episode: Inside xAI, and the Bet on AI Math - with Christian Szegedy (Math Inc)
Subbarau Kamphampati
Professor at Arizona State University
Arizona State University
Episode: Reasoning Models and Planning - with Rao Kambhampati (Arizona State)
Zhuang Liu
Assistant Professor at Princeton
Princeton University
Episode: What Actually Matters in AI? - with Zhuang Liu (Princeton)
Sasha Rush
Researcher at Cursor and professor at Cornell
Cursor; Cornell University
Episode: The Future of Coding Agents with Sasha Rush (Cursor/Cornell)
Peyman Milanfar
Distinguished scientist at Google since 2012, leading the imaging team
Google
Episode: The Hidden Engine of Vision with Peyman Milanfar (Google)
Yaroslav Bulatov
AI researcher, early researcher at OpenAI and Google Brain
OpenAI, Google Brain
Episode: Reinventing AI From Scratch with Yaroslav Bulatov
Kyunghyun Cho
Glendy, various professor of health statistics and computer science at New York University
New York University
Episode: Why Healthcare Is AI's Hardest and Most Important Problem with Kyunghyun Cho (NYU)
Stefano Ermon
Professor at Stanford; CEO of Inception AI
Stanford University; Inception AI
Episode: Diffusion LLM & Why the Future of AI Won't Be Autoregressive - Stefano Ermon (Stanford /Inception)
Naomi Saphra
Kempner Research Fellow at Harvard and incoming Assistant Professor at Boston University
Harvard University, Boston University
Episode: Training Is Nothing Like Learning with Naomi Saphra (Harvard)

Hosts

Ravid Shwartz Ziv
Co-host of The Information Bottleneck; host of The Information Bottleneck Podcast
Allen Roush
Co-host of The Information Bottleneck; host of The Information Bottleneck Podcast

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#224
France/Technology
Apple Podcasts
#84
Poland/Technology
Apple Podcasts
#99
Israel/Technology
Apple Podcasts
#153
Denmark/Technology
Apple Podcasts
#183
Netherlands/Technology
Apple Podcasts
#238
Switzerland/Technology

Talking Points

Recent interactions between the hosts and their guests.

What Actually Matters in AI? - with Zhuang Liu (Princeton)
Q: Do you think architecture is the primary driver of AI progress, or do data and training regimes matter more?
The guest argues that while architecture matters, the data, scale, and how we train (the interface and objectives) largely determine performance; you can achieve frontier-level results with different architectures if you get the training data and process right, and you often see diminishing returns chasing purely architectural changes without broader data and training considerations.
Reinventing AI From Scratch with Yaroslav Bulatov
Q: What is your approach to building better models while addressing energy efficiency and memory constraints?
Start from energy-aware toy tasks, design with a clear energy budget in mind, and progressively scale while measuring energy per unit of useful capability. Consider architecture shifts (like local hierarchical message passing) and embrace open, iterative experimentation rather than chasing a single benchmark.
Reinventing AI From Scratch with Yaroslav Bulatov
Q: Do you think AI coding agents will replace software engineers or researchers, or will they augment human labor?
They will augment, increasing what engineers and researchers can accomplish, but not replace them entirely. The trend is toward integrating agents into workflows to amplify productivity, with humans providing direction, evaluation, and creative problem-solving.
Reinventing AI From Scratch with Yaroslav Bulatov
Q: What is your view on AGI and why is the term so contested today?
AGI is not a single, well-defined target; there are multiple interpretations (a sudden, almost religious milestone; a marketable insurance-like construct; or a subjective feeling of capability). This ambiguity leads to divergent expectations, timelines, and risk-taking by companies and researchers alike.
EP27: Medical Foundation Models - with Tanishq Abraham (Sophont.AI)
Q: What does Sophont specifically do in medical AI?
Sophont builds foundation models tailored for medicine with a emphasis on multimodality, integrating neuroimaging, pathology, and clinical text, and plans to merge domain encoders into a single, unified model to aid clinical decision-making.

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Frequently Asked Questions About The Information Bottleneck

What is The Information Bottleneck about and what kind of topics does it cover?

A spotlight on cutting-edge AI research, practical deployment insights, and the evolving landscape of generative models, LLMs, and AI infrastructure. Discussions frequently center on evaluation methodologies, real-world performance, data quality, and privacy, with episodes ranging from open-source frameworks and data curation for LLMs to AI applications in finance and robotics. The tone blends deep technical exploration with thoughtful consideration of ethics, governance, and the societal impact of rapid AI advancement, making it a strong fit for listeners who want rigorous, practitioner-oriented conversations about how AI technologies actually perform and scale in real-world contexts. Noteworthy traits include a steady emphasis on evaluati... more

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The Information Bottleneck launched 9 months ago and published 38 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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What guests have appeared on The Information Bottleneck?

Recent guests on The Information Bottleneck include:

1. Christian Szegedy
2. Subbarau Kamphampati
3. Zhuang Liu
4. Sasha Rush
5. Peyman Milanfar
6. Yaroslav Bulatov
7. Kyunghyun Cho
8. Stefano Ermon

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