Media Summary: One of the core roadblocks to understanding the computation inside a transformer is the fact that individual neurons do not seem ... A Google TechTalk, presented by Phillipp Schoppmann, Google, at the 2021 Google Federated Learning and Analytics Workshop ... Queering/Cripping Technologies of Productivity Sylvia Janicki, Alexandra Teixeira Riggs, Noura Howell, Anne Sullivan, Abigale ...

Hoagy Cunningham Finding Distributed Features - Detailed Analysis & Overview

One of the core roadblocks to understanding the computation inside a transformer is the fact that individual neurons do not seem ... A Google TechTalk, presented by Phillipp Schoppmann, Google, at the 2021 Google Federated Learning and Analytics Workshop ... Queering/Cripping Technologies of Productivity Sylvia Janicki, Alexandra Teixeira Riggs, Noura Howell, Anne Sullivan, Abigale ... Les Valiant (Harvard University) The Role of TCS in ... This has been my favorite video so far to make! I think interpretability is so important both in terms of ensuring safe AI and also ... Uli Wagner (IST Austria) Error-Correcting Codes and ...

Designing systems that are high-performance, power-efficient and easily programmable by non-experts is important at all levels of ... Predictive Processing Community Project Weekly Meeting - 5/26/2026 Suz Hinton, Novelty Coder, shares her "One Weird Trick" on how to implement someone else's work from a spec into her own.

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Hoagy Cunningham — Finding distributed features in LLMs with sparse autoencoders [TAIS 2024]
Distributed Point Functions: Efficient Secure Aggregation and Beyond with Non-Colluding Servers
Queering/Cripping Technologies of Productivity
Enhanced and Efficient Reasoning in Large Language Models
A Window  Into LLMs | Sparse Autoencoders Explained
Expansion from a Cohomological Viewpoint
Archive: The Design of a Micropolygon Rendering Pipeline
Predictive Processing Community Project Weekly Meeting - 5/26/2026
#HowICode Implementing Other Works
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Hoagy Cunningham — Finding distributed features in LLMs with sparse autoencoders [TAIS 2024]

Hoagy Cunningham — Finding distributed features in LLMs with sparse autoencoders [TAIS 2024]

One of the core roadblocks to understanding the computation inside a transformer is the fact that individual neurons do not seem ...

Distributed Point Functions: Efficient Secure Aggregation and Beyond with Non-Colluding Servers

Distributed Point Functions: Efficient Secure Aggregation and Beyond with Non-Colluding Servers

A Google TechTalk, presented by Phillipp Schoppmann, Google, at the 2021 Google Federated Learning and Analytics Workshop ...

Queering/Cripping Technologies of Productivity

Queering/Cripping Technologies of Productivity

Queering/Cripping Technologies of Productivity Sylvia Janicki, Alexandra Teixeira Riggs, Noura Howell, Anne Sullivan, Abigale ...

Enhanced and Efficient Reasoning in Large Language Models

Enhanced and Efficient Reasoning in Large Language Models

Les Valiant (Harvard University) https://simons.berkeley.edu/talks/les-valiant-harvard-university-2026-05-26 The Role of TCS in ...

A Window  Into LLMs | Sparse Autoencoders Explained

A Window Into LLMs | Sparse Autoencoders Explained

This has been my favorite video so far to make! I think interpretability is so important both in terms of ensuring safe AI and also ...

Expansion from a Cohomological Viewpoint

Expansion from a Cohomological Viewpoint

Uli Wagner (IST Austria) https://simons.berkeley.edu/talks/cohomological-viewpoint-expansion Error-Correcting Codes and ...

Archive: The Design of a Micropolygon Rendering Pipeline

Archive: The Design of a Micropolygon Rendering Pipeline

Designing systems that are high-performance, power-efficient and easily programmable by non-experts is important at all levels of ...

Predictive Processing Community Project Weekly Meeting - 5/26/2026

Predictive Processing Community Project Weekly Meeting - 5/26/2026

Predictive Processing Community Project Weekly Meeting - 5/26/2026

#HowICode Implementing Other Works

#HowICode Implementing Other Works

Suz Hinton, Novelty Coder, shares her "One Weird Trick" on how to implement someone else's work from a spec into her own.