activity
20172024
most citedThe State of Sparsity in Deep Neural Networks

439 citations · 1.5k across the 27 of their papers we have counts for

collaborators

28 papers

cs.AI2024★ 3 cited

On the Limitations of Compute Thresholds as a Governance Strategy

Sara Hooker

At face value, this essay is about understanding a fairly esoteric governance tool called compute thresholds. However, in order to grapple with whether these thresholds will achiev…

cs.LG2023

Generalisable Agents for Neural Network Optimisation

Kale-ab Tessera, Callum Rhys Tilbury, Sasha Abramowitz +5

Optimising deep neural networks is a challenging task due to complex training dynamics, high computational requirements, and long training times. To address this difficulty, we pro…

cs.SE2023★ 1 cited

The Grand Illusion: The Myth of Software Portability and Implications for ML Progress

Fraser Mince, Dzung Dinh, Jonas Kgomo +2

Pushing the boundaries of machine learning often requires exploring different hardware and software combinations. However, the freedom to experiment across different tooling stacks…

cs.CY2023★ 76 cited

Frontier AI Regulation: Managing Emerging Risks to Public Safety

Markus Anderljung, Joslyn Barnhart, Anton Korinek +21

Advanced AI models hold the promise of tremendous benefits for humanity, but society needs to proactively manage the accompanying risks. In this paper, we focus on what we term "fr…

cs.CY2023★ 3 cited

Evaluating the Social Impact of Generative AI Systems in Systems and Society

Irene Solaiman, Zeerak Talat, William Agnew +28

Generative AI systems across modalities, ranging from text (including code), image, audio, and video, have broad social impacts, but there is no official standard for means of eval…

cs.LG2023★ 5 cited

Intriguing Properties of Quantization at Scale

Arash Ahmadian, Saurabh Dash, Hongyu Chen +5

Emergent properties have been widely adopted as a term to describe behavior not present in smaller models but observed in larger models. Recent work suggests that the trade-off inc…