Pine is the Creative Director at TIME. To illustrate the choice of the Architects of AI as TIME's 2025 Person of the Year, we asked two separate artists to help us visualize the incredibly complex technological revolution that is currently underway. London-based illustrator and graphics animator Peter Crowther and digital painter Jason Seiler each created an image that speaks to the duality AI has produced - man vs. machine. Inspired by the inner workings of computer chips, Crowther's intricate AI structure looms large over the busy construction site.

Recurrent neural networks (RNNs) are a vital modeling technique that rely on internal states learned indirectly by optimization of a supervised, unsupervised, or reinforcement training loss. RNNs are used to model dynamic processes that are characterized by underlying latent states whose form is often unknown, precluding its analytic representation inside an RNN. In the Predictive-State Representation (PSR) literature, latent state processes are modeled by an internal state representation that directly models the distribution of future observations, and most recent work in this area has relied on explicitly representing and targeting sufficient statistics of this probability distribution. We seek to combine the advantages of RNNs and PSRs by augmenting existing state-of-the-art recurrent neural networks with Predictive-State Decoders (PSDs), which add supervision to the network's internal state representation to target predicting future observations. PSDs are simple to implement and easily incorporated into existing training pipelines via additional loss regularization. We demonstrate the effectiveness of PSDs with experimental results in three different domains: probabilistic filtering, Imitation Learning, and Reinforcement Learning. In each, our method improves statistical performance of state-of-the-art recurrent baselines and does so with fewer iterations and less data.

Multi-agent AI research promises a path to develop human-like and human-compatible intelligent technologies that complement the solipsistic view of other approaches, which mostly do not consider interactions between agents. Aiming to make progress in this direction, the Melting Pot contest 2023 focused on the problem of cooperation among interacting agents and challenged researchers to push the boundaries of multi-agent reinforcement learning (MARL) for mixed-motive games. The contest leveraged the Melting Pot environment suite to rigorously evaluate how well agents can adapt their cooperative skills to interact with novel partners in unforeseen situations. Unlike other reinforcement learning challenges, this challenge focused on social rather than environmental generalization. In particular, a population of agents performs well in Melting Pot when its component individuals are adept at finding ways to cooperate both with others in their population and with strangers.

Enabling deep models to generalize in non-stationary environments is vital for real-world machine learning, as data distributions are often found to continually change. Recently, evolving domain generalization (EDG) has emerged to tackle the domain generalization in a time-varying system, where the domain gradually evolves over time in an underlying continuous structure. Nevertheless, it typically assumes multiple source domains simultaneously ready. It still remains an open problem to address EDG in the domain-incremental setting, where source domains are non-static and arrive sequentially to mimic the evolution of training domains. To this end, we propose Weight Diffusion (W-Diff), a novel framework that utilizes the conditional diffusion model in the parameter space to learn the evolving pattern of classifiers during the domain-incremental training process.

Sign up for our daily newsletter to get the best of The New Yorker in your inbox. The microchip maker Nvidia is a Silicon Valley colossus. After years as a runner-up to Intel and Qualcomm, Nvidia has all but cornered the market on the parallel processors essential for artificial-intelligence programs like ChatGPT. "Nvidia was there at the beginning of A.I.," the tech journalist Stephen Witt tells David Remnick. "They really kind of made these systems work for the first time. We think of A.I. as a software revolution, something called neural nets, but A.I. is also a hardware revolution."

Image taken from the front cover of the Future of AI Research report. The Association for the Advancement of Artificial Intelligence (AAAI), has published a report on the Future of AI Research. The report, which was announced by outgoing AAAI President Francesca Rossi during the AAAI 2025 conference, covers 17 different AI topics and aims to clearly identify the trajectory of AI research in a structured way. The report is the result of a Presidential Panel, chaired by Francesca Rossi, and comprising of 24 experienced AI researchers, who worked on the project between summer 2024 and spring 2025. As well as the views of the panel members, the report also draws on community feedback, which was received from 475 AI researchers via a survey.

Oscar Wilde's quip, "Life imitates art far more than art imitates life", needs updating: replace "art" with "AI". The Amazon page for Alexander C Karp and Nicholas W Zapiska's new book, The Technological Republic: Hard Power, Soft Belief and the Future of the West, also lists: a "workbook" containing "key takeaways" from the volume; a second volume on how the Karp/Zapiska tome "can help you navigate life"; and a third offering another "workbook" comprising a "Master Plan for Navigating Digital Age and the Future of Society". It is conceivable that these parasitical works were written by humans, but I wouldn't bet on it. The Guardian's journalism is independent. We will earn a commission if you buy something through an affiliate link.

The future of artificial intelligence (AI) has been the focus of tech entrepreneurs and financial backers gathered in Doha for the second annual Web Summit hosted by Qatar. The four-day digital technology and emerging innovation summit kicked off its second day on Monday, with attendees eyeing an AI environment being transformed rapidly. Leading entrepreneurs from around the world, including Alexander Wang, founder and CEO of Scale AI, and Alexis Ohanian, co-founder of Reddit and general partner at Seven Seven Six, took centre stage at the event on the opening day. Reporting from Doha, Al Jazeera's Colin Baker said the summit is grappling with questions over the future of AI amid "companies and investors that are changing that landscape more rapidly than we expected". The United States and China are leading in preparedness for AI, said Wang of US company Scale AI.

On Tuesday 4th February 2025, the Children's AI Summit brought together around 150 children from across the UK to share their messages for global leaders, policymakers, and AI developers on what the future of AI should look like. Hosted by the Children and AI team in The Alan Turing Institute's Public Policy Programme and Queen Mary University of London, the event aimed to put children's voices and experiences centre stage by exploring how the technology impacts young people today, and how children can shape its future. As part of the summit, a Children's Manifesto for the Future of AI was developed. This incorporates ideas that were submitted in the run-up to the event, and was refined with the help of summit participants. The Turing's Children and AI team are attending the Paris AI Action Summit this week and will be taking the Children's Manifesto for the Future of AI with them, as well as screening a short film made at the Children's AI Summit.

The increasing availability of computer-mediated knowledge and the advancement of information and communication technologies have altered the methods through which health care information is sought [3] [25] [30]. The Internet has had a significant impact on healthcare service and is a virtual medical library for an estimated 75-80% of users in developed countries [4] [5] [11]. On an average day, more than six million patients and their caregivers in the United States use the Internet to obtain health and medical information. This number exceeds the average daily number of 2.27 million Americans who make visits to physician offices [11] [18] [26]. Furthermore, not only patients but their caregivers want to get actively involved in the health-care management of their loved ones. In a research nearly 60% of people who identified themselves as caregivers use the Internet to find answers to their health-related questions [16]. This computer mediated environment has become, as Vargo and Lusch [32] argue, a fundamental hub where "people exchange to acquire the benefits of specialized competencies (knowledge and skills), or services."