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When the Netflix anthology series "Beef" premièred, in 2023, it was a revelation in more ways than one. The show, which traced the depths into which two Angelenos descend after a road-rage incident, reintroduced Ali Wong as a dramatic lead, gave Steven Yeun a chance to go darkly comic, and shined a rare light on the issue of Asian American mental health. It also remade the career of its creator, Lee Sung Jin, a seeming overnight success who actually had nearly two decades of TV-comedy writing under his belt. Lee first pitched the show after he stalked another driver for a half hour following a parking-lot dispute; he similarly drew from life for Season 2, which stars Oscar Isaac as Josh, a country-club manager, and Carey Mulligan as his interior-designer wife, Lindsay. The couple are caught on video having a nasty fight by two members of his staff, Austin (Charles Melton) and Ashley (Cailee Spaeny). The Gen Z employees, about to embark on their own marriage, see the footage as blackmail material--and thus an opportunity to start their next chapter on secure financial footing. As in the first season, the story quickly broadens beyond the central conflict, roping in the club's new billionaire owner, Chairwoman Park (Youn Yuh-jung), her unreliable plastic-surgeon husband, and the seething resentments of both the haves and the have-nots. I met Lee earlier this month, at his new office in Hollywood. The space was sparsely decorated, but he'd already mounted posters for "Beef"; "It's Always Sunny in Philadelphia," the show that gave him his start in the industry; and "Thunderbolts," a 2025 Marvel movie directed by his creative partner, Jake Schreier. Lee, who has gone by Sonny since childhood and was credited as Sonny Lee for the first half of his career, opened up about the long road to "Beef"--a journey toward more intentional storytelling, as well as feeling "O.K. in my own skin." Perhaps surprisingly, the "Beef" character he seemed to relate to most was Josh, a congenial go-getter who mires himself in workaholism to avoid addressing his grief, as Lee did when one of his dogs died suddenly during production. We talked about his method of tailoring dialogue to his actors, the differences between Korean and American billionaires, and why class and capitalism are such inescapable themes on TV today.

NATO to beef up defense of Europe's eastern flank after Poland drone incursions NATO Supreme Allied Commander Europe Gen. Alexus G. Grynkewich speaks during a news conference on the violation of Polish airspace by Russian drones, at the NATO headquarters in Brussels on Friday. BRUSSELS/WARSAW/UNITED NATIONS - NATO announced plans to beef up the defense of Europe's eastern flank on Friday, two days after Poland shot down drones that had violated its airspace in the first known action of its kind by a member of the Western alliance during Russia's war in Ukraine. At the United Nations, the United States called the airspace violations alarming and vowed to defend every inch of NATO territory, remarks that appeared aimed at assuaging Washington's NATO allies after President Donald Trump said Russia's drone incursion could have been a mistake. Warsaw has portrayed the drone incursions as an attempt by Russia to test the capabilities of Poland and NATO to respond. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

By the time you read this article, there's a good chance it will have already been scanned by an artificially intelligent machine. If asked about the artist David Salle, large language models such as ChatGPT or Gemini may repurpose some of the words below to come up with their answer. The bigger the data set, the more convincing the response – and Salle has been written about exhaustively since he first rose to art world stardom in the 1980s. The question is whether AI can ever say anything new about the artist and his work, or if it's for ever condemned to generate more of the same. A similar question lingers beneath the surface of the paintings that Salle has been making since 2023, a new series of which he has just unveiled at Thaddaeus Ropac in London.

British Prime Minister Keir Starmer stresses the United Kingdom's intention to provide "robust and credible" security guarantees to prevent Russia from attacking Ukraine again as Russian President Vladimir Putin has yet to sign up to a US-brokered truce proposal as fighting rages on the ground. "We will build up Ukraine's own defences and armed forces and be ready to deploy as a'coalition of the willing' in the event of a peace deal to help secure Ukraine on the land, at sea and in the sky," Starmer said on Saturday after a virtual meeting with 25 European Union and other world leaders as well as Ukrainian President Volodymyr Zelenskyy. "We agreed military planners would convene again in the UK this week to progress practical plans for how our militaries can support Ukraine's future security," Starmer added. The meeting was held after Putin on Friday agreed in principle to an immediate 30-day ceasefire put forward by Washington and already accepted by Ukraine. But on Friday, Putin also said there were issues to work out.

Agents built on large language models (LLMs) have excelled in turn-by-turn human-AI collaboration but struggle with simultaneous tasks requiring real-time interaction. Latency issues and the challenge of inferring variable human strategies hinder their ability to make autonomous decisions without explicit instructions. Through experiments with current independent System 1 and System 2 methods, we validate the necessity of using Dual Process Theory (DPT) in real-time tasks. We propose DPT-Agent, a novel language agent framework that integrates System 1 and System 2 for efficient real-time simultaneous human-AI collaboration. DPT-Agent's System 1 uses a Finite-state Machine (FSM) and code-as-policy for fast, intuitive, and controllable decision-making. DPT-Agent's System 2 integrates Theory of Mind (ToM) and asynchronous reflection to infer human intentions and perform reasoning-based autonomous decisions. We demonstrate the effectiveness of DPT-Agent through further experiments with rule-based agents and human collaborators, showing significant improvements over mainstream LLM-based frameworks. To the best of our knowledge, DPT-Agent is the first language agent framework that achieves successful real-time simultaneous human-AI collaboration autonomously. Code of DPT-Agent can be found in https://github.com/sjtu-marl/DPT-Agent.

The pursuit of quality improvements and accountability in the food supply chains, especially how they relate to food-related outcomes, such as hunger, has become increasingly vital, necessitating a comprehensive approach that encompasses product quality and its impact on various stakeholders and their communities. Such an approach offers numerous benefits in increasing product quality and eliminating superfluous measurements while appraising and alleviating the broader societal and environmental repercussions. A traceable impact management model (TIMM) provides an impact structure and a reporting mechanism that identifies each stakeholder's role in the total impact of food production and consumption stages. The model aims to increase traceability's utility in understanding the impact of changes on communities affected by food production and consumption, aligning with current and future government requirements, and addressing the needs of communities and consumers. This holistic approach is further supported by an ontological model that forms the logical foundation and a unified terminology. By proposing a holistic and integrated solution across multiple stakeholders, the model emphasizes quality and the extensive impact of championing accountability, sustainability, and responsible practices with global traceability. With these combined efforts, the food supply chain moves toward a global tracking and tracing process that not only ensures product quality but also addresses its impact on a broader scale, fostering accountability, sustainability, and responsible food production and consumption.

Drake and Kendrick Lamar's ongoing beef has left their devoted fans utterly divided over who's winning. The rappers have released several diss songs against each other and their fan bases are certain their team is winning. To try and strip biases out of the debate, we asked artificial intelligence chatbots who is winning the ongoing feud - and it produced some surprising insights. Three out of four AI chatbots remained politically correct when addressing which rapper is winning the beef, calling it'subjective' and saying it is up to the fans to decide. But Meta's AI bot said Kendrick had a slight edge in the beef so far. Gemini called Drake a'commercial powerhouse with numerous hit singles and albums that have topped the charts,' but said who is winning the feud remains subjective'Ultimately, the winner of the Drake versus Kendrick Lamar beef is subjective and depends on personal preference,' said DeepAI.

Stealing someone else's joke is one of the highest crimes in comedy. With new AI tools like ChatGPT, some comedians are now worried about getting ripped off. Comedian Matt Rife is facing backlash on social media after allegedly telling a 6-year-old boy that his mother buys his presents with profits from OnlyFans. In a Saturday video that has garnered over 13 million views, TikToker Bunny Hedaya claimed Rife had started "beef" with her child online. Hedaya's son drew Rife's attention after criticizing the comedian's recent Netflix standup special, "Natural Selection."

Large language models (LLMs) have pushed the limits of natural language understanding and exhibited excellent problem-solving ability. Despite the great success, most existing open-source LLMs (e.g., LLaMA-2) are still far away from satisfactory for solving mathematical problems due to the complex reasoning procedures. To bridge this gap, we propose MetaMath, a finetuned language model that specializes in mathematical reasoning. Specifically, we start by bootstrapping mathematical questions by rewriting the question from multiple perspectives, which results in a new dataset called MetaMathQA. Experimental results on two popular benchmarks (i.e., GSM8K and MATH) for mathematical reasoning demonstrate that MetaMath outperforms a suite of open-source LLMs by a significant margin. Our MetaMath-7B model achieves 66.5% on GSM8K and 19.8% on MATH, exceeding the state-ofthe-art models of the same size by 11.5% and 8.7%. Particularly, MetaMath-70B achieves an accuracy of 82.3% on GSM8K, slightly better than GPT-3.5-Turbo. We release all the MetaMathQA dataset, the MetaMath models with different model sizes and the training code for public use. What is the total amount that James paid when he purchased 5 packs of beef, each weighing 4 pounds, at a price of $5.50 per pound? James buys x packs of beef that are 4 packs of beef that are 4 pounds each. The price of beef is $5.50 per pound. What is The price of beef is $5.50 per pound. James buys x packs of beef that are 4 pounds each.