Gods and Robots In this episode of the podcast we shake things up! Neil is on the guest side of the table with his partner Rabbi Laura Janner-Klausner to discuss their upcoming project Gods and Robots. Katherine is joined on the host side by friend of the show professor Michael Littman. See... See More Episodes arXiv Whitepapers How Robust is Unsupervised Representation Learning to Distribution Shift? The robustness of machine learning algorithms to distributions shift is primarily discussed in the context of supervised learning (SL). As such, there is a lack of insight on the robustness of the representations learned from unsupervised methods, such as self-supervised learning (SSL) and auto... Simplistic Collection and Labeling Practices Limit the Utility of Benchmark Datasets for Twitter Bot Detection Accurate bot detection is necessary for the safety and integrity of online platforms. It is also crucial for research on the influence of bots in elections, the spread of misinformation, and financial market manipulation. Platforms deploy infrastructure to flag or remove automated accounts, but... A Watermark for Large Language Models Potential harms of large language models can be mitigated by watermarking model output, i.e., embedding signals into generated text that are invisible to humans but algorithmically detectable from a short span of tokens. We propose a watermarking framework for proprietary language models. The... More featured content News Articles Flood forecasts in real-time with block-by-block data could save lives – a new machine learning method makes it possible An automated way to assemble thousands of objects Stay in the loop. Subscribe to our newsletter for a weekly update on the latest podcast, news, events, and jobs postings. E-mail Leave this field blank From a ‘deranged’ provocateur to IBM’s failed AI superproject: the controversial story of how data has transformed healthcare Computers that power self-driving cars could be a huge driver of global carbon emissions Subtle biases in AI can influence emergency decisions AI might be seemingly everywhere, but there are still plenty of things it can’t do – for now A simpler path to better computer vision Solving brain dynamics gives rise to flexible machine-learning models Not everything we call AI is actually ‘artificial intelligence’. Here’s what you need to know Breaking the scaling limits of analog computing More news