Scotland Yard is understood to be moving quickly towards embracing AI automation in its intelligence units. Scotland Yard is understood to be moving quickly towards embracing AI automation in its intelligence units. The Metropolitan police has held talks with Palantir that could lead to the London force buying the US spy-tech company's AI technology to automate intelligence analysis for criminal investigations, the Guardian has learned. Palantir, whose software is used by Donald Trump's ICE immigration enforcement programme and the Israeli military, demonstrated its systems to senior officers in the intelligence division at the UK's largest police force last month. Intelligence staff have been tasked with finding intelligence systems that AI could automate to increase productivity.

Science The Weirdest Thing I Learned This Week Why do female reindeer have antlers? Plus wild neutrinos and other weird things we learned this week. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Breakthroughs, discoveries, and DIY tips sent six days a week. What's the weirdest thing you learned this week?

'She had big googly eyes and was wearing a red hat knitted by one of the careworkers' Emma the Social Robot by Paula Hornickel. 'She had big googly eyes and was wearing a red hat knitted by one of the careworkers' Emma the Social Robot by Paula Hornickel. 'The first resident that Emma - a social robot - was introduced to was called Peter. After that, Emma assumed they were all called Peter, which everyone found hilarious. O ne morning in July 2025, I arrived in the small, quiet town of Albershausen in south-west Germany.

Neural Information Processing Systems http://nips.cc/

Previous studies have proposed image-based clutter measures that correlate with human search times and/or eye movements. However, most models do not take into account the fact that the effects of clutter interact with the foveated nature of the human visual system: visual clutter further from the fovea has an increasing detrimental influence on perception. Here, we introduce a new foveated clutter model to predict the detrimental effects in target search utilizing a forced fixation search task. We use Feature Congestion (Rosenholtz et al.) as our non foveated clutter model, and we stack a peripheral architecture on top of Feature Congestion for our foveated model. We introduce the Peripheral Integration Feature Congestion (PIFC) coefficient, as a fundamental ingredient of our model that modulates clutter as a non-linear gain contingent on eccentricity. We show that Foveated Feature Congestion (FFC) clutter scores (r(44) = 0.82 0.04,p < 0.0001) correlate better with target detection (hit rate) than regular Feature Congestion (r(44) = 0.19 0.13,p= 0.0774) in forced fixation search; and we extend foveation to other clutter models showing stronger correlations in all cases. Thus, our model allows us to enrich clutter perception research by computing fixation specific clutter maps. Code for building peripheral representations is available1.

Pima County Sheriff Chris Nanos' attorney acknowledges he resigned from El Paso Police Department in 1982 to avoid suspension, defending his sworn deposition testimony.

Hey Meta workers, are you getting paid for those keystrokes? It's a very simple question that your bosses aren't inclined to answer. No longer content to subsume recognizable intellectual properties, the majority of the i ndexed internet and books ( basically all of them), AI will apparently now begin devouring its own workforce. A report in alleged that the keystrokes, mouse movements and clicks of Meta's workforce are to be captured for the purposes of training AI -- something the company's communications department was happy to confirmed as accurate! In a cheery missive, a company spokesperson told Engadget that If we're building agents to help people complete everyday tasks using computers, our models need real examples of how people use them [...] we're launching an internal tool that will capture these kinds of inputs on certain applications to help us train our models.

Better understanding of the potential benefits of information transfer and representation learning is an important step towards the goal of building intelligent systems that are able to persist in the world and learn over time. In this work, we consider a setting where the learner encounters a stream of tasks but is able to retain only limited information from each encountered task, such as a learned predictor. In contrast to most previous works analyzing this scenario, we do not make any distributional assumptions on the task generating process. Instead, we formulate a complexity measure that captures the diversity of the observed tasks. We provide a lifelong learning algorithm with error guarantees for every observed task (rather than on average). We show sample complexity reductions in comparison to solving every task in isolation in terms of our task complexity measure. Further, our algorithmic framework can naturally be viewed as learning a representation from encountered tasks with a neural network.

Neural Information Processing Systems http://nips.cc/

Whole-brain neural connectivity data are now available from viral tracing experiments, which reveal the connections between a source injection site and elsewhere in the brain.