Things to Do in L.A. Tap to enable a layout that focuses on the article. The Dodgers of esports: How L.A.'s Liquid Guild won the attention of over 100,000 people The top "WoW" guilds around the world, including Team Liquid, race to be the first to defeat highest-difficulty bosses. This is read by an automated voice. Please report any issues or inconsistencies here . Los Angeles-based Team Liquid won the "World of Warcraft" world championship for the fourth consecutive time, defeating Germany's Echo guild in a monthlong competition watched by more than 100,000 viewers.

Things to Do in L.A. Tap to enable a layout that focuses on the article. L.A.'s defense industry is booming. This is read by an automated voice. Please report any issues or inconsistencies here . L.A. defense-tech startups like Gambit face funding shortfalls as the Small Business Innovation Research program expired in September amid a Capitol Hill dispute.

Valar Atomics Says It's the First Nuclear Startup to Achieve Criticality A Trump administration pilot program aims for three nuclear startups to reach a key milestone by July 4, 2026. Valar Atomics says it's the first to do so--but it had some help. The El Segundo, California-based startup, which last week announced it had secured a $130 million funding round with backing from Palmer Luckey and Palantir CTO Shyam Sankar, claims that it is the first nuclear startup to create a critical fission reaction. It's also, more specifically, the first company in a special Department of Energy pilot program aiming to get at least three startups to criticality by July 4 of next year to announce it had achieved this reaction. The pilot program, which was formed following an executive order president Donald Trump signed in May, has upended US regulation of nuclear startups, allowing companies to reach new milestones like criticality at a rapid pace.

We prove that CSP learns a near-optimal risk-free offline adaptation policy upon convergence.

Things to Do in L.A. Tap to enable a layout that focuses on the article. Gov. Gavin Newsom holds a news conference at the Google office in San Francisco in August to announce new AI partnerships. This is read by an automated voice. Please report any issues or inconsistencies here . Gov. Gavin Newsom signed legislation Monday requiring AI companies to publicly disclose security protocols and report critical safety incidents.

Things to Do in L.A. Tap to enable a layout that focuses on the article. Starting Oct. 1, over 2,700 Kroger locations will be available on DoorDash. Customers will be able to shop the store's entire selection. Above, bagged purchases from a Kroger grocery store sit in a shopping cart in Flowood, Miss. This is read by an automated voice.

Early Detection of Risks (EDR) on the Web involves identifying at-risk users as early as possible. Although Large Language Models (LLMs) have proven to solve various linguistic tasks efficiently, assessing their reasoning ability in specific domains is crucial. In this work, we propose a method for solving depression-related EDR using LLMs on Spanish texts, with responses that can be interpreted by humans. We define a reasoning criterion to analyze users through a specialist, apply in-context learning to the Gemini model, and evaluate its performance both quantitatively and qualitatively. The results show that accurate predictions can be obtained, supported by explanatory reasoning, providing a deeper understanding of the solution. Our approach offers new perspectives for addressing EDR problems by leveraging the power of LLMs.

The field of high-speed autonomous racing has seen significant advances in recent years, with the rise of competitions such as RoboRace and the Indy Autonomous Challenge providing a platform for researchers to develop software stacks for autonomous race vehicles capable of reaching speeds in excess of 170 mph. Ensuring the safety of these vehicles requires the software to continuously monitor for different faults and erroneous operating conditions during high-speed operation, with the goal of mitigating any unreasonable risks posed by malfunctions in sub-systems and components. This paper presents a comprehensive overview of the HALO safety architecture, which has been implemented on a full-scale autonomous racing vehicle as part of the Indy Autonomous Challenge. The paper begins with a failure mode and criticality analysis of the perception, planning, control, and communication modules of the software stack. Specifically, we examine three different types of faults - node health, data health, and behavioral-safety faults. To mitigate these faults, the paper then outlines HALO safety archetypes and runtime monitoring methods. Finally, the paper demonstrates the effectiveness of the HALO safety architecture for each of the faults, through real-world data gathered from autonomous racing vehicle trials during multi-agent scenarios.

In multiwinner approval voting, forming a committee that proportionally represents voters' approval ballots is an essential task. The notion of justified representation (JR) demands that any large "cohesive" group of voters should be proportionally "represented". The "cohesiveness" is defined in different ways; two common ways are the following: (C1) demands that the group unanimously approves a set of candidates proportional to its size, while (C2) requires each member to approve at least a fixed fraction of such a set. Similarly, "representation" have been considered in different ways: (R1) the coalition's collective utility from the winning set exceeds that of any proportionally sized alternative, and (R2) for any proportionally sized alternative, at least one member of the coalition derives less utility from it than from the winning set. Three of the four possible combinations have been extensively studied: (C1)-(R1) defines Proportional Justified Representation (PJR), (C1)-(R2) defines Extended Justified Representation (EJR), (C2)-(R2) defines Full Justified Representation (FJR). All three have merits, but also drawbacks. PJR is the weakest notion, and perhaps not sufficiently demanding; EJR may not be compatible with perfect representation; and it is open whether a committee satisfying FJR can be found efficiently. We study the combination (C2)-(R1), which we call Full Proportional Justified Representation (FPJR). We investigate FPJR's properties and find that it shares PJR's advantages over EJR: several proportionality axioms (e.g. priceability, perfect representation) imply FPJR and PJR but not EJR. We also find that efficient rules like the greedy Monroe rule and the method of equal shares satisfy FPJR, matching a key advantage of EJR over FJR. However, the Proportional Approval Voting (PAV) rule may violate FPJR, so neither of EJR and FPJR implies the other.