Things to Do in L.A. Tap to enable a layout that focuses on the article. Rep. Swalwell, candidate for California governor, has an AI side gig This is read by an automated voice. Please report any issues or inconsistencies here . Rep. Eric Swalwell co-founded Findraiser, an AI tool that analyzes campaign fundraising data. Findraiser is being paid by dozens of campaigns, including his own.

Things to Do in L.A. Kate Brody's 7-year-old son plays at home in North Hollywood on March 14. This is read by an automated voice. Please report any issues or inconsistencies here . Early childhood experts say excessive screen time displaces hands-on learning and peer interaction critical to development. At least 11 states have considered legislation limiting technology in the classroom this year.

Each year the AAAI recognizes a group of individuals who have made significant, sustained contributions to the field of artificial intelligence by appointing them as Fellows. Over the course of the next few months, we'll be talking to some of the 2026 AAAI Fellows . In this interview, we met with Yan Liu, University of Southern California, who was elected as a Fellow . We found out about how time series research has progressed, the vast range of applications, and what the future holds for this field. Could you start with a quick introduction to your area of research?

Recent research indicates that large language models (LLMs) are susceptible to jailbreaking attacks that can generate harmful content. This paper introduces a novel token-level attack method, Adaptive Dense-to-Sparse Constrained Optimization (ADC), which has been shown to successfully jailbreak multiple open-source LLMs.

Success in collaborative and competitive environments, where agents must work with or against each other, requires individuals to encode the position and trajectory of themselves and others. Decades of neurophysiological experiments have shed light on how brain regions [e.g., medial entorhinal cortex (MEC), hippocampus] encode the self's position and trajectory. However, it has only recently been discovered that MEC and hippocampus are modulated by the positions and trajectories of others. To understand how encoding spatial information of multiple agents shapes neural representations, we train a recurrent neural network (RNN) model that captures properties of MEC to path integrate trajectories of two agents simultaneously navigating the same environment. We find significant differences between these RNNs and those trained to path integrate only a single agent. At the individual unit level, RNNs trained to path integrate more than one agent develop weaker grid responses, stronger border responses, and tuning for the relative position of the two agents. At the population level, they develop more distributed and robust representations, with changes in network dynamics and manifold topology. Our results provide testable predictions and open new directions with which to study the neural computations supporting spatial navigation.

An engineer at the AgiBot factory in Shanghai, China, where the 5,000th mass-produced humanoid robot had rolled off the production line. An engineer at the AgiBot factory in Shanghai, China, where the 5,000th mass-produced humanoid robot had rolled off the production line. How close are we to the sci-fi vision of autonomous humanoid robots? C hen Liang, the founder of Guchi Robotics, an automation company headquartered in Shanghai, is a tall, heavy-set man in his mid-40s with square-rimmed glasses. His everyday manner is calm and understated, but when he is in his element - up close with the technology he builds, or in business meetings discussing the imminent replacement of human workers by robots - he wears an exuberant smile that brings to mind an intern on his first day at his dream job. Guchi makes the machines that install wheels, dashboards and windows for many of the top Chinese car brands, including BYD and Nio. He took the name from the Chinese word, "steadfast intelligence", though the fact that it sounded like an Italian luxury brand was not entirely unwelcome. For the better part of two decades, Chen has tried to solve what, to him, is an engineering problem: how to eliminate - or, in his view, liberate - as many workers in car factories as technologically possible. Late last year, I visited him at Guchi headquarters on the western outskirts of Shanghai. Next to the head office are several warehouses where Guchi's engineers tinker with robots to fit the specifications of their customers. Chen, an engineer by training, founded Guchi in 2019 with the aim of tackling the hardest automation task in the car factory: "final assembly", the last leg of production, when all the composite pieces - the dashboard, windows, wheels and seat cushions - come together. At present, his robots can mount wheels, dashboards and windows on to a car without any human intervention, but 80% of the final assembly, he estimates, has yet to be automated. That is what Chen has set his sights on. As in much of the world, AI has become part of everyday life in China . But what most excites Chinese politicians and industrialists are the strides being made in the field of robotics, which, when combined with advances in AI, could revolutionise the world of work.

RelBench provides databases and tasks spanning diverse domains, scales, and database dimensions, and is intended to be a foundational infrastructure for future research in this direction. We use RelBench to conduct the first comprehensive empirical study of graph neural network (GNN) based predictive models on relational data, as recently proposed by Fey et al. 2024. End-to-end learned GNNs are capable fully exploiting the predictive signal encoded in links between entities, marking a significant shift away from the dominant paradigm of manual feature engineering combined with tabular machine learning. To thoroughly evaluate GNNs against the prior gold-standard we conduct a user study, where an experienced data scientist manually engineers features for each task. In this study, GNNs learn better models whilst reducing human work needed by more than an order of magnitude. This result demonstrates the power of GNNs for solving predictive tasks in relational databases, opening up new research opportunities.

NTT Global Data Centers is working on 34 projects to double its capacity to 4 gigawatts within as little as two years, CEO Doug Adams said, as it races to meet surging global demand driven by the AI boom. NTT Global Data Centers, the world's third-largest data center provider outside of China, is working to double its capacity to 4 gigawatts to meet the rising global demand for the critical digital infrastructure amid an artificial intelligence boom. The unit of Japan's NTT is working on 34 projects that will double its capacity in as soon as two years, according to the data center business's Chief Executive Officer Doug Adams. Capacity will continue to increase from there, and will be "well over 5 gigawatts" in five years, Adams said in an interview. NTT GDC has seen increasing demand from companies moving more of their software and operations to the cloud as well as businesses hunting for extra capacity to run AI programs. The business's revenue is expected to keep growing at more than 20% a year, Adams said, declining to give a specific time period.

Gesture synthesis is a vital realm of human-computer interaction, with wide-ranging applications across various fields like film, robotics, and virtual reality. Recent advancements have utilized the diffusion model to improve gesture synthesis. However, the high computational complexity of these techniques limits the application in reality. In this study, we explore the potential of state space models (SSMs).Direct application of SSMs in gesture synthesis encounters difficulties, which stem primarily from the diverse movement dynamics of various body parts. The generated gestures may also exhibit unnatural jittering issues.To address these, we implement a two-stage modeling strategy with discrete motion priors to enhance the quality of gestures.Built upon the selective scan mechanism, we introduce MambaTalk, which integrates hybrid fusion modules, local and global scans to refine latent space representations.Subjective and objective experiments demonstrate that our method surpasses the performance of state-of-the-art models.

Trendy designer dogs often have the same issues as pure breeds. The'doodle' industry earns over $1 billion a year. Breakthroughs, discoveries, and DIY tips sent six days a week. Designer crossbreed dogs are increasingly popular pets . Much of the rising interest is tied to claims that these mixed pooches possess more desirable aspects than many purebreeds or mutts.