There are an increasing number of domains in which artificial intelligence (AI) systems both surpass human ability and accurately model human behavior. This introduces the possibility of algorithmically-informed teaching in these domains through more relatable AI partners and deeper insights into human decision-making. Critical to achieving this goal, however, is coherently modeling human behavior at various skill levels. Chess is an ideal model system for conducting research into this kind of human-AI alignment, with its rich history as a pivotal testbed for AI research, mature superhuman AI systems like AlphaZero, and precise measurements of skill via chess rating systems. Previous work in modeling human decision-making in chess uses completely independent models to capture human style at different skill levels, meaning they lack coherence in their ability to adapt to the full spectrum of human improvement and are ultimately limited in their effectiveness as AI partners and teaching tools. In this work, we propose a unified modeling approach for human-AI alignment in chess that coherently captures human style across different skill levels and directly captures how people improve. Recognizing the complex, non-linear nature of human learning, we introduce a skill-aware attention mechanism to dynamically integrate players' strengths with encoded chess positions, enabling our model to be sensitive to evolving player skill. Our experimental results demonstrate that this unified framework significantly enhances the alignment between AI and human players across a diverse range of expertise levels, paving the way for deeper insights into human decision-making and AI-guided teaching tools.

The Tokyo Metropolitan Government is developing a Generative AI Platform, which will allow government employees to create AI applications to assist with their work. The Tokyo Metropolitan Government and municipal governments throughout the Japanese capital are increasingly using generative artificial intelligence in their administrative operations. To support this trend, the metropolitan government is working with GovTech Tokyo, an affiliated organization that promotes digitalization in local governments, to develop a Generative AI Platform. The system will allow government employees to create generative AI applications tailored to their specific duties. By encouraging active use of the platform, Tokyo authorities aim to boost efficiency in public services and address growing concerns over labor shortages. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Single-cell transcriptomics has revolutionized our understanding of cellular heterogeneity and drug perturbation effects.

Since the conflict in the Middle East began on Feb. 28, Emirates has cancelled more than 2,000 flights -- 54% of scheduled services, according to data from Cirium. As Emirates flight EK10 from London cruised over Saudi Arabia on Monday, news broke of a drone strike at its destination, Dubai. The aircraft turned back to Gatwick, flight data shows, completing a 9,100 km round trip -- one of dozens of flights to nowhere triggered by the Middle East war. Roughly 30 Emirates flights heading to Dubai International Airport were also ordered back or rerouted after Iranian drone attacks temporarily shut what is normally the world's busiest airport for international passengers. Passengers expecting a dawn landing in the glitzy United Arab Emirates port city were stunned. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

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.

In this paper, we explore the properties of loss curvature with respect to input data in deep neural networks. Curvature of loss with respect to input (termed input loss curvature) is the trace of the Hessian of the loss with respect to the input. We investigate how input loss curvature varies between train and test sets, and its implications for train-test distinguishability. We develop a theoretical framework that derives an upper bound on the train-test distinguishability based on privacy and the size of the training set.

Things to Do in L.A. Tap to enable a layout that focuses on the article. Teachers, union members, attend a rally at Molina Grand Park in Los Angeles on Wednesday. United Teachers Los Angeles and Local 99 service workers announced members would strike on April 14, if no deal is reached before then. This is read by an automated voice. Please report any issues or inconsistencies here .

Scaling deep learning models has been at the heart of recent revolutions in language modelling and image generation. Practitioners have observed a strong relationship between model size, dataset size, and performance. However, structure-based architectures such as Graph Neural Networks (GNNs) are yet to show the benefits of scale mainly due to lower efficiency of sparse operations, large data requirements, and lack of clarity about the effectiveness of various architectures. We address this drawback of GNNs by studying their scaling behavior. Specifically, we analyze message-passing networks, graph Transformers, and hybrid architectures on the largest public collection of 2D molecular graphs for supervised pretraining.

Humour and science fiction may not seem obvious bedfellows but a history of cinema will tell you different. Think Spaceballs, Mars Attacks! and Everything Everwhere All At Once to name but a few. And now Ryan Gosling is hopping on board. The 45-year-old is both the lead actor and producer of Project Hail Mary, a space adventure film based on the 2021 Andy Weir novel of the same name. While Gosling has showcased his comedy chops in films such as Barbie and Nice Guys, he tells the BBC he's always struggled as an actor because I would want to bring humour to something but has found opportunities to be funny limited with some projects.

Consumer electronics used to follow the miniaturization trend described by Moore's Law. Despite increased processing power in Microcontroller Units (MCUs), MCUs used in the smallest appliances are still not capable of running even moderately big, state-of-the-art artificial neural networks (ANNs) especially in time-sensitive scenarios. In this work, we present a novel method called Scattered Online Inference (SOI) that aims to reduce the computational complexity of ANNs.