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Artwork for The Information Bottleneck

The Information Bottleneck

Ravid Shwartz-Ziv & Allen Roush
Artificial Intelligence
Openai
AI Coding
AI Research
Copyright
Large Language Models
Reinforcement Learning
Gpt-4
Gpt-5
Samplers
Cursor
Neuroscience
Google
Deepseek
Urban Design
NVIDIA
Computational Models
Generative AI
Thoughtworks
Smart Cities

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

PublishesWeeklyEpisodes9Founded2 months ago
Number of ListenersCategories
TechnologyScience

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Artwork for The Information Bottleneck

Latest Episodes

In this episode we host Tal Kachman, an assistant professor at Radboud University, to explore the fascinating intersection of artificial intelligence and natural sciences. Prof. Kachman's research focuses on multiagent interaction, complex systems, a... more

In this episode, we talked with Ahmad Beirami, an ex-researcher at Google, to discuss various topics. We explored the complexities of reinforcement learning, its applications in LLMs, and the evaluation challenges in AI research. We also discussed th... more

In this episode of the "Information Bottleneck" podcast, we hosted Aran Nayeb, an assistant professor at Carnegie Mellon University, to discuss the intersection of computational neuroscience and machine learning. We talked about the challenges and op... more

We talked with Ariel Noyman, an urban scientist, working in the intersection of cities and technology. Ariel is a research scientist at the MIT Media Lab, exploring novel methods of urban modeling and simulation using AI. We discussed the potential o... more

We discussed the inference optimization technique known as Speculative Decoding with a world class researcher, expert, and ex-coworker of the podcast hosts: Nadav Timor.

Papers and links:

* Accelerating LLM Inference with Lossless Speculative Deco... more

In this episode, Ravid and Allen discuss the evolving landscape of AI coding. They explore the rise of AI-assisted development tools, the challenges faced in software engineering, and the potential future of AI in creative fields. The conversation hi... more

Allen and Ravid discuss the dynamics associated with the extreme need for GPUs that AI researchers utilize. They also discuss the latest advancements in AI, including Google's Nano Banana and DeepSeek V3.1, exploring the implications of synthetic dat... more

Allen and Ravid sit down and talk about Parameter Efficient Fine Tuning (PeFT) along with the latest updated in AI/ML news.

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Recent Guests

Ahmad Beirami
Former researcher at Google
Google
Episode: EP8: RL with Ahmad Beirami
Aran Nayebi
Assistant Professor at Carnegie Mellon University specializing in AI and neuroscience.
Carnegie Mellon University
Episode: EP7: AI and Neuroscience with Aran Nayebi
Ariel Noyman
Research scientist at MIT Media Lab and an expert in urban design.
MIT Media Lab
Episode: EP6: Urban Design Meets AI: With Ariel Noyman
Nadav Timor
AI researcher and former colleague at One Day AI
Co-founder of the open-source initiative in New York
Episode: EP5: Speculative Decoding with Nadav Timor

Hosts

Allen Roush
Co-host with focus on AI research and technology discussions.
Ravid Shwartz Ziv
Co-host with emphasis on AI advancements and research trends.

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Talking Points

Recent interactions between the hosts and their guests.

EP5: Speculative Decoding with Nadav Timor
Q: What are some implications and limitations when implementing speculative decoding?
The efficiency of speculative decoding significantly depends on the accuracy and speed of the drafter models used for token generation, and it's crucial that the drafter models can maintain distribution integrity comparable to larger models.
EP5: Speculative Decoding with Nadav Timor
Q: Could you describe what speculative decoding is?
Speculative decoding is an optimization method to enhance inference efficiency by using parallel processing to generate tokens with a smaller, faster model while ensuring output quality through verification.

Audience Metrics

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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?

Conversations center around the latest developments and research in artificial intelligence, particularly within the realms of generative AI and large language models (LLMs). Notable themes include the advancements in AI coding, inference efficiency, and the implications of various AI tools and techniques on industries and society. Episodes often feature insights from experts and cover emerging technologies related to urban design, data utilization, and AI ethics, making it a valuable resource for professionals and enthusiasts interested in the intersection of technology and research. Unique discussions emphasize real-world applications and the importance of human-centered design, positioning the content as both informative and accessible f... more

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Which podcasts are similar to The Information Bottleneck?

These podcasts share a similar audience with The Information Bottleneck:

1. Dwarkesh Podcast
2. The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
3. גיקונומי
4. a16z Podcast
5. Deep Questions with Cal Newport

How many episodes of The Information Bottleneck are there?

The Information Bottleneck launched 2 months ago and published 9 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. Ahmad Beirami
2. Aran Nayebi
3. Ariel Noyman
4. Nadav Timor

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