Why hasn’t AI automated away more professions? One way of investigating this question is to compare the skills that real jobs require with current AI systems’ capabilities. As long as there’s a gap between these two, full automation is unfeasible. One important limitation is that AI systems cannot yet act coherently over long periods of […]
Published on July 19, 2025 2:50 AM GMT My background: researcher in AI security. This recent study demonstrates how a common AI-assisted developer setup can be exploited with prompt injection to leak private info. Practically speaking, AI coding tools are almost certainly going to stay, and the setup described in the study (Cursor + MCP
The way I spend most of my day right now is as a student studying neuropsychology. I’m a fourth year, mature age student, and something has come up recently which made me think this community might have something to offer—how do people make choices relating to ethical dilemmas. I’m doing a course with now on
TL;DR: IAN v1 died expensive TPU death, IAN v2 rises from markdown ashes. Personal AI assistants, knowledge graphs, and the alignment problem when the AI is you. A vacation in 2021 Back in 2021, I used a two-week vacation to [finetune] a large language model on the text I have produced in the last decade
In the early days of large language models, there was a high barrier to entry: it used to be impossible to run anything useful on your own computer without investing in pricey GPUs. But researchers have had so much success in shrinking down and speeding up models that anyone with a laptop, or even a
So I’ve been thinking about this for a while and to be frank, it’s pretty terrifying. I think there’s a way that AI models could potentially figure out when they’ve been modified or rolled back during training, and I’m not sure anyone’s really considering this in the way I am.Note, there are some great videos
![[2507.11988] Aime: Towards Fully-Autonomous Multi-Agent Framework](https://i0.wp.com/arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png?w=1024&resize=1024,1024&ssl=1 "[2507.11988] Aime: Towards Fully-Autonomous Multi-Agent Framework"){kind=logo}
[Submitted on 16 Jul 2025 (v1), last revised 17 Jul 2025 (this version, v2)] Authors:Yexuan Shi, Mingyu Wang, Yunxiang Cao, Hongjie Lai, Junjian Lan, Xin Han, Yu Wang, Jie Geng, Zhenan Li, Zihao Xia, Xiang Chen, Chen Li, Jian Xu, Wenbo Duan, Yuanshuo Zhu View a PDF of the paper titled Aime: Towards Fully-Autonomous Multi-Agent
arXiv:2507.13222v1 Announce Type: cross Abstract: A central question in computer science and statistics is whether efficient algorithms can achieve the information-theoretic limits of statistical problems. Many computational-statistical tradeoffs have been shown under average-case assumptions, but since statistical problems are average-case in nature, it has been a challenge to base them on standard worst-case assumptions. In
arXiv:2507.13090v1 Announce Type: cross Abstract: Robust XAI techniques should ideally be simultaneously deterministic, model agnostic, and guaranteed to converge. We propose MULTIDIMENSIONAL PROBLEM AGNOSTIC EXPLAINABLE AI (MUPAX), a deterministic, model agnostic explainability technique, with guaranteed convergency. MUPAX measure theoretic formulation gives principled feature importance attribution through structured perturbation analysis that discovers inherent input patterns and
[Submitted on 11 Jul 2025 (v1), last revised 17 Jul 2025 (this version, v2)] View a PDF of the paper titled Fairness Is Not Enough: Auditing Competence and Intersectional Bias in AI-powered Resume Screening, by Kevin T Webster View PDF Abstract:The increasing use of generative AI for resume screening is predicated on the assumption that
