Search a title or topic

Over 20 million podcasts, powered by 

Player FM logo
Artwork

Content provided by Machine Learning Street Talk (MLST). All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Machine Learning Street Talk (MLST) or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.
Player FM - Podcast App
Go offline with the Player FM app!

ARC Prize v2 Launch! (Francois Chollet and Mike Knoop)

54:15
 
Share
 

Manage episode 473109604 series 2803422
Content provided by Machine Learning Street Talk (MLST). All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Machine Learning Street Talk (MLST) or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

We are joined by Francois Chollet and Mike Knoop, to launch the new version of the ARC prize! In version 2, the challenges have been calibrated with humans such that at least 2 humans could solve each task in a reasonable task, but also adversarially selected so that frontier reasoning models can't solve them. The best LLMs today get negligible performance on this challenge.

https://arcprize.org/

SPONSOR MESSAGES:

***

Tufa AI Labs is a brand new research lab in Zurich started by Benjamin Crouzier focussed on o-series style reasoning and AGI. They are hiring a Chief Engineer and ML engineers. Events in Zurich.

Goto https://tufalabs.ai/

***

TRANSCRIPT:

https://www.dropbox.com/scl/fi/0v9o8xcpppdwnkntj59oi/ARCv2.pdf?rlkey=luqb6f141976vra6zdtptv5uj&dl=0

TOC:

1. ARC v2 Core Design & Objectives

[00:00:00] 1.1 ARC v2 Launch and Benchmark Architecture

[00:03:16] 1.2 Test-Time Optimization and AGI Assessment

[00:06:24] 1.3 Human-AI Capability Analysis

[00:13:02] 1.4 OpenAI o3 Initial Performance Results

2. ARC Technical Evolution

[00:17:20] 2.1 ARC-v1 to ARC-v2 Design Improvements

[00:21:12] 2.2 Human Validation Methodology

[00:26:05] 2.3 Task Design and Gaming Prevention

[00:29:11] 2.4 Intelligence Measurement Framework

3. O3 Performance & Future Challenges

[00:38:50] 3.1 O3 Comprehensive Performance Analysis

[00:43:40] 3.2 System Limitations and Failure Modes

[00:49:30] 3.3 Program Synthesis Applications

[00:53:00] 3.4 Future Development Roadmap

REFS:

[00:00:15] On the Measure of Intelligence, François Chollet

https://arxiv.org/abs/1911.01547

[00:06:45] ARC Prize Foundation, François Chollet, Mike Knoop

https://arcprize.org/

[00:12:50] OpenAI o3 model performance on ARC v1, ARC Prize Team

https://arcprize.org/blog/oai-o3-pub-breakthrough

[00:18:30] Chain-of-Thought Prompting Elicits Reasoning in Large Language Models, Jason Wei et al.

https://arxiv.org/abs/2201.11903

[00:21:45] ARC-v2 benchmark tasks, Mike Knoop

https://arcprize.org/blog/introducing-arc-agi-public-leaderboard

[00:26:05] ARC Prize 2024: Technical Report, Francois Chollet et al.

https://arxiv.org/html/2412.04604v2

[00:32:45] ARC Prize 2024 Technical Report, Francois Chollet, Mike Knoop, Gregory Kamradt

https://arxiv.org/abs/2412.04604

[00:48:55] The Bitter Lesson, Rich Sutton

http://www.incompleteideas.net/IncIdeas/BitterLesson.html

[00:53:30] Decoding strategies in neural text generation, Sina Zarrieß

https://www.mdpi.com/2078-2489/12/9/355/pdf

  continue reading

218 episodes

Artwork
iconShare
 
Manage episode 473109604 series 2803422
Content provided by Machine Learning Street Talk (MLST). All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Machine Learning Street Talk (MLST) or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

We are joined by Francois Chollet and Mike Knoop, to launch the new version of the ARC prize! In version 2, the challenges have been calibrated with humans such that at least 2 humans could solve each task in a reasonable task, but also adversarially selected so that frontier reasoning models can't solve them. The best LLMs today get negligible performance on this challenge.

https://arcprize.org/

SPONSOR MESSAGES:

***

Tufa AI Labs is a brand new research lab in Zurich started by Benjamin Crouzier focussed on o-series style reasoning and AGI. They are hiring a Chief Engineer and ML engineers. Events in Zurich.

Goto https://tufalabs.ai/

***

TRANSCRIPT:

https://www.dropbox.com/scl/fi/0v9o8xcpppdwnkntj59oi/ARCv2.pdf?rlkey=luqb6f141976vra6zdtptv5uj&dl=0

TOC:

1. ARC v2 Core Design & Objectives

[00:00:00] 1.1 ARC v2 Launch and Benchmark Architecture

[00:03:16] 1.2 Test-Time Optimization and AGI Assessment

[00:06:24] 1.3 Human-AI Capability Analysis

[00:13:02] 1.4 OpenAI o3 Initial Performance Results

2. ARC Technical Evolution

[00:17:20] 2.1 ARC-v1 to ARC-v2 Design Improvements

[00:21:12] 2.2 Human Validation Methodology

[00:26:05] 2.3 Task Design and Gaming Prevention

[00:29:11] 2.4 Intelligence Measurement Framework

3. O3 Performance & Future Challenges

[00:38:50] 3.1 O3 Comprehensive Performance Analysis

[00:43:40] 3.2 System Limitations and Failure Modes

[00:49:30] 3.3 Program Synthesis Applications

[00:53:00] 3.4 Future Development Roadmap

REFS:

[00:00:15] On the Measure of Intelligence, François Chollet

https://arxiv.org/abs/1911.01547

[00:06:45] ARC Prize Foundation, François Chollet, Mike Knoop

https://arcprize.org/

[00:12:50] OpenAI o3 model performance on ARC v1, ARC Prize Team

https://arcprize.org/blog/oai-o3-pub-breakthrough

[00:18:30] Chain-of-Thought Prompting Elicits Reasoning in Large Language Models, Jason Wei et al.

https://arxiv.org/abs/2201.11903

[00:21:45] ARC-v2 benchmark tasks, Mike Knoop

https://arcprize.org/blog/introducing-arc-agi-public-leaderboard

[00:26:05] ARC Prize 2024: Technical Report, Francois Chollet et al.

https://arxiv.org/html/2412.04604v2

[00:32:45] ARC Prize 2024 Technical Report, Francois Chollet, Mike Knoop, Gregory Kamradt

https://arxiv.org/abs/2412.04604

[00:48:55] The Bitter Lesson, Rich Sutton

http://www.incompleteideas.net/IncIdeas/BitterLesson.html

[00:53:30] Decoding strategies in neural text generation, Sina Zarrieß

https://www.mdpi.com/2078-2489/12/9/355/pdf

  continue reading

218 episodes

All episodes

×
 
Loading …

Welcome to Player FM!

Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.

 

Listen to this show while you explore
Play