www.nytimes.com/2025/02/05/o...

This is such an amazing opinion piece! Time to pivot regulation to logical areas

My NeurIPS paper on LLM regulation through data and evaluation finally up on arxiv - I feel stronger about this approach with the shift to reasoning and away from compute as a proxy for performance arxiv.org/abs/2502.03472

With all the Deepseek news, thought I’d reshare my NeurIPS paper on data and evaluation based regulation as an alternative or complement to compute. The shift to reasoning makes this even more relevant: wesleypasfield.com/pasfield_neu...

Has anyone seen an estimate on what will happen to human labor in knowledge work if agentic LLM solutions are successful? I’ve seen the market opportunity from the VC side (10x SaaS) but presumably that would come at the direct cost of human employment?

I put together an automated newsletter featured in Data Elixir and Data Science Weekly posts that identifies interesting AI research and summarizes the content, sending out twice a week.

You can sign up here: wesleypasfield.com/aipapers/

And check out the code here: github.com/WesleyPasfie...

Happy New Year! To kick off the year, I've finally been able to format and upload the draft of my AI Research Highlights of 2024 article.
It covers a variety of topics, from mixture-of-experts models to new LLM scaling laws for precision:

Easy prediction for 2025 is that the gains in AI model capability will continue to grow much faster than (a) the vast majority of people’s understanding of what AI can do & (b) organizations’ ability to absorb the pace of change. Social change is much slower than technological change.

I've been trying to write more on Substack - I just published a post on how some of the more recent LLM trends (agents, test-time inference) could impact society moving forward, and what we should do about it:

open.substack.com/pub/wesleypa...

“This is not just incremental progress; it is new territory, and it demands serious scientific attention.” As inference enhancements drive LLM performance optimizations, regulatory efforts that don’t directly measure model output will be less and less relevant arcprize.org/blog/oai-o3-...

I’ll be at the RegML workshop tomorrow at Neurips in East Meeting Room 13 come say hi!

I just updated the NeurIPS starter pack with many more attendees

Let me know if you'd like to be added

go.bsky.app/BuJXg5q

#NeurIPS2024 #NeurIPS

Strongly agree with the primary takeaway from this argument “You are getting left behind if you do not adopt chat-based programming as your primary modality.” Not sure if chat will always be the primary medium but LLM assisted/driven development is here to stay sourcegraph.com/blog/the-dea...

Very happy to see this release from AWS. This makes Bedrock very compelling and the type of practical offering that can help LLM based experiences exit the experimental phase into prod for a specific domain/application aws.amazon.com/about-aws/wh...

Extremely interesting findings from this paper : lauraruis.github.io/2024/11/10/i...

“The approach to reasoning LLMs use looks unlike retrieval, and more like a generalisable strategy synthesising procedural knowledge from many documents doing a similar form of reasoning.”

It’s really great to see domain specific means of LLM evaluation start to pop up (in this case chemistry) arxiv.org/pdf/2411.16736

AGI seems like the wrong output metric to focus on. With the existing incremental progress observed If we get to AGI it likely means professions have been entirely disrupted along the way. Measuring model efficacy vs human equivalent by profession seems like a more practical near term metric

I’m new to this platform, sharing my Substack where I share my thoughts on AI and society: open.substack.com/pub/wesleypa...