ashater

5 ms·

1.
What if you could stop your AI agent before it makes a mistake?(arxiv.org)
2 points by ashater 2mo ago|1 comments
2.
by ashater 2mo ago
Do you want to monitor what an Al agent is about to do before it acts? In our new paper, Beyond the Black Box: Interpretability of Agentic Al Tool Use, we explore how mechanistic interpretability can help surface signals around tool-use dec
3.
by ashater 6mo ago
Likely reasoning is part of the original model. It is well known that it is not possible to get a 1bn parameter model to reason, even with RL.
4.
by ashater 1y ago
We want to do both. In finance, highly regulated industry, understanding how models work is critical. In addition, mech interp will allow us to understand which current or new architectures could work better for financial applications.
5.
by ashater 1y ago
Thank you for reading. One of the main reasons we've written the paper is to help with model validation of LLM usage in our highly regulated industry. We are also engaging with regulators. The industry at the moment is mostly using clo
6.
by ashater 1y ago
Our paper provides evidence of features in Finance but I would suggest reading seminal papers from Anthropic https://www.anthropic.com/news/golden-gate-claude and https://transformer-circuits.pub/2024&#
7.
by ashater 1y ago
Thank you. Agreed, we are exploring different ways to apply these interpretability methods to a wide range of transformer based methods, not just decoder based generative applications.
8.
Beyond the Black Box: Interpretability of LLMs in Finance(arxiv.org)
67 points by ashater 1y ago|12 comments
9.
by ashater 1y ago
Paper introduces AI explainability methods, mechanistic interpretation, and novel Finance-specific use cases. Using Sparse Autoencoders, we zoom into LLM internals and highlight Finance-related features. We provide examples of using interpr
10.
Beyond the Black Box: Interpretability of LLMs in Finance(papers.ssrn.com)
4 points by ashater 1y ago|1 comments
11.
by ashater 1y ago
Our paper introduces AI explainability methods, mechanistic interpretation, and novel Finance-specific use cases. Using Sparse Autoencoders, we zoom into LLM internals and highlight Finance-related features. We provide examples of using int
12.
by ashater 2y ago
My younger daughter, who is pretty good at making games in Scratch is not that interested in jumping into text/code based programming. I do think Scratch makes things a lot easier and text based programming is not thar appealing to kid
13.
by ashater 2y ago
Another piece of evidence that LLMs are plateauing
14.
by ashater 2y ago
Terrence Tao has a very healthy view of what AI can and cannot achieve shorter term. It is refreshing to hear more grounded views from a top mathematician who is clearly well versed in the topic.
15.
Espionage Probe Finds Communications Device on Chinese Cranes at U.S. Ports(wsj.com)
13 points by ashater 3y ago|3 comments
16.
What Makes It Hard to Control Inflation(chicagobooth.edu)
1 points by ashater 5y ago|1 comments
17.
by ashater 5y ago
Good article, steps one level below container managers like Docker or k8s. Obviously not the indepth of how Linux kernel manages container processes but a good write-up.
18.
by ashater 6y ago
pynq is a good starting board. What's really good is the software environment connected to the fpga logic via Python ecosystem. There are lots of examples via Jupyter notebooks.
19.
by ashater 6y ago
how do I modify the link?
20.
Towards an Untrepreneurial Economy?(papers.ssrn.com)
2 points by ashater 6y ago|5 comments
21.
by ashater 6y ago
The paper describes the rise of “tech entrepreneurship as a lifestyle” and how more entrepreneurship seems primarily motivated by people wanting to “be entrepreneurs” rather than by those with potentially valuable ideas that are likely to l