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Follow this section to personalize your feed and get instant alerts. Follow Go to your personalized feed WHY FOLLOW? Smart Alerts: Get notified about major news as it happens. LeBron James speaks onstage during the TIME100 Sports Gala on July 16, 2026 in New York City. LeBron James speaks onstage during the TIME100 Sports Gala on July 16, 2026 in New York City.

Agentic LLM frameworks promise autonomous behavior via task decomposition, tool use, and iterative planning, but most deployed systems remain brittle. They lack runtime introspection, cannot diagnose their own failure modes, and do not improve over time without human intervention. In practice, many agent stacks degrade into decorated chains of LLM calls with no structural mechanisms for reliability. We present VIGIL (Verifiable Inspection and Guarded Iterative Learning), a reflective runtime that supervises a sibling agent and performs autonomous maintenance rather than task execution. VIGIL ingests behavioral logs, appraises each event into a structured emotional representation, maintains a persistent EmoBank with decay and contextual policies, and derives an RBT diagnosis that sorts recent behavior into strengths, opportunities, and failures. From this analysis, VIGIL generates both guarded prompt updates that preserve core identity semantics and read only code proposals produced by a strategy engine that operates on log evidence and code hotspots. VIGIL functions as a state gated pipeline. Illegal transitions produce explicit errors rather than allowing the LLM to improvise. In a reminder latency case study, VIGIL identified elevated lag, proposed prompt and code repairs, and when its own diagnostic tool failed due to a schema conflict, it surfaced the internal error, produced a fallback diagnosis, and emitted a repair plan. This demonstrates meta level self repair in a deployed agent runtime.

The event celebrates the third annual TIME100 AI list, which highlights the 100 most influential people in AI. This year's list includes 84 new honorees--a testament to the dynamism of the field--with those selected ranging in age from 15 to nearly 80. The aim of the TIME list is to show how it is people, not machines, that will determine the direction of AI, and honorees were drawn from every angle of the discipline. The event culminated in four toasts delivered by 2025 TIME100 AI honorees, who highlighted the importance of guiding AI responsibly, including with regulation; protecting human creativity; and fostering collaboration between human and machine intelligence. Stuart Russell, professor of computer science at the University of California, Berkeley, and co-founder of the International Association for Safe and Ethical AI (IASEAI), delivered the first toast--a provocative call to make wise choices about how we use AI, given the high existential stakes involved.

Partitioning large machine learning models across distributed accelerator systems is a complex process, requiring a series of interdependent decisions that are further complicated by internal sharding ambiguities. Consequently, existing auto-partitioners often suffer from out-of-memory errors or are prohibitively slow when exploring the exponentially large space of possible partitionings. To mitigate this, they artificially restrict the search space, but this approach frequently yields infeasible solutions that violate device memory constraints or lead to sub-optimal performance. We propose a system that combines a novel static compiler analysis with a Monte Carlo Tree Search. Our analysis constructs an efficient decision space by identifying (i) tensor dimensions requiring identical sharding, and (ii) partitioning "conflicts" that require resolution. Our system significantly outperforms state-of-the-art industrial methods across diverse hardware platforms and model architectures, discovering previously unknown, superior solutions, and the process is fully automated even for complex and large models.

Dear Prudence is Slate's advice column. For this edition, Hillary Frey, Slate's editor-in-chief, will be filling in as Prudie. My partner of five years and I just got married after two years of extensive wedding planning and preparation. We had a very large guest list with a variety of needs that needed to be taken into account, such as international travel and physical limitations, and I feel grateful that my husband was very intentional about making sure the labor of wedding planning was split as equitably as possible between the two of us. We agreed that we wanted to write our own vows because we thought it was more meaningful than using traditional ones.

From slices of toast to patches of clouds, Jesus's face has a habit of appearing in some unusual places. But this mind-boggling optical illusion might be the most bizarre appearance yet.

Leaders from across the world of business, technology, policy, and entertainment gathered at the TIME100 Davos Dinner as the World Economic Forum's 55th annual meeting kicked off on Jan. 20. In keeping with this year's annual meeting theme "Collaboration for the Intelligent Age," Dario Amodei, CEO and co-founder of AI company Anthropic, joined TIME editor-in-chief Sam Jacobs on stage to talk about the future of AI. Discussing what Amodei calls powerful AI, which he prefers over Artificial General Intelligence because of the latter's connotations with science fiction, the CEO emphasized the importance of understanding the reality of the technology's potential. "We have to be very serious about when this actually happens, what is possible and what exists. What are the bounds that are provided by physics, by the limits in human institutions, what's left after we consider those," he said.

TIME hosted its inaugural TIME100 Impact Dinner: Leaders Shaping the Future of AI, in San Francisco on Monday evening. The event kicked off a weeklong celebration of the TIME100 AI, a list that recognizes the 100 most influential individuals in artificial intelligence across industries and geographies and showcases the technology's rapid evolution and far-reaching impact. TIME CEO Jessica Sibley set the tone for the evening, highlighting the diversity and dynamism of the 2024 TIME100 AI list. With 91 newcomers from last year's inaugural list and honorees ranging from 15 to 77 years old, the group reflects the field's explosive growth and its ability to attract talent from all walks of life. The heart of the evening centered around three powerful toasts delivered by distinguished AI leaders, each offering a unique perspective on the transformative potential of AI and the responsibilities that come with it.

Abstract--In this study, we introduce a novel framework called Toast for learning general-purpose representations of road networks, along with its advanced counterpart DyToast, designed to enhance the integration of temporal dynamics to boost the performance of various time-sensitive downstream tasks. Specifically, we propose to encode two pivotal semantic characteristics intrinsic to road networks: traffic patterns and traveling semantics. To achieve this, we refine the skip-gram module by incorporating auxiliary objectives aimed at predicting the traffic context associated with a target road segment. Moreover, we leverage trajectory data and design pre-training strategies based on Transformer to distill traveling semantics on road networks. DyToast further augments this framework by employing unified trigonometric functions characterized by their beneficial properties, enabling the capture of temporal evolution and dynamic nature of road networks more effectively. With these proposed techniques, we can obtain representations that encode multi-faceted aspects of knowledge within road networks, applicable across both road segment-based applications and trajectory-based applications. Extensive experiments on two real-world datasets across three tasks demonstrate that our proposed framework consistently outperforms the state-of-the-art baselines by a significant margin. These tasks include trajectory-based tasks like route inference [1], [2] and road segment-based tasks like traffic forecasting [3], [4].