The release of Moonshot's Kimi K3 model upended assumptions that Chinese AI capabilities were meaningfully behind U.S. leaders such as OpenAI and Anthropic. A White House official accused China's Moonshot of improperly using U.S. AI models and Nvidia chips to create the Kimi K3 system that stunned the tech industry last week with its advanced capabilities. The company "acquired GB300-equipped servers and has accessed GB300s in Thailand, likely to train its AI models," White House Office of Science and Technology Policy Director Michael Kratsios said in a social media post Wednesday, making the case that Moonshot violated U.S. export control rules and companies' terms of service to build its product. The semiconductor servers Kratsios referenced are part of the Blackwell generation of Nvidia products, which the U.S. forbids from sale to Chinese companies. Though the Trump administration has allowed some sales of Nvidia's H200 chips, it continues to prevent sales of the more advanced Blackwells. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Chinese AI sensation Moonshot's gamble on big models pays off People visit the Moonshot AI stand, featuring the Kimi K3 model, during the World Artificial Intelligence Conference in Shanghai on Saturday. Crowds rushed to an obscure corner of China's premier tech summit, moving past monumental booths from Alibaba Group Holding and Tencent Holdings to catch a glimpse of the hottest name in domestic artificial intelligence. Developers and users at the World AI Conference jostled for a closer look at Moonshot and its Kimi K3 -- the giant 2.8 trillion-parameter model whose release on Friday showed China was closing the gap on OpenAI and Anthropic PBC far quicker than anticipated. The startup became an instant global sensation, drawing comparisons to DeepSeek's 2025 breakout and plaudits from the likes of Tesla CEO Elon Musk. Such was the crush over the weekend that Moonshot blew through its entire stock of branded swag in just a few hours. Moonshot's emergence is a vindication not just for the country's AI industry, but also for founder Yang Zhilin.

Plus: Elizabeth Warren wants answers on xAI's access to military data. Human-made glass is thousands of years old. But it's now poised to find its way into the AI chips used in the world's newest and largest data centers. This year, a South Korean company called Absolics will start producing special glass panels that make next-generation computing hardware more powerful and efficient. Other companies, including Intel, are also pushing forward in this area. If all goes well, the technology could reduce the energy demands of chips in AI data centers--and even consumer laptops and mobile devices.

A robust nonproliferation regime has contained the spread of nuclear weapons to just nine states. Yet, emerging and disruptive technologies are reshaping the landscape of nuclear risks, presenting a critical juncture for decision makers. This article lays out the contours of an overlooked but intensifying technological arms race for nuclear (in)visibility, driven by the interplay between proliferation-enabling technologies (PETs) and detection-enhancing technologies (DETs). We argue that the strategic pattern of proliferation will be increasingly shaped by the innovation pace in these domains. Artificial intelligence (AI) introduces unprecedented complexity to this equation, as its rapid scaling and knowledge substitution capabilities accelerate PET development and challenge traditional monitoring and verification methods. To analyze this dynamic, we develop a formal model centered on a Relative Advantage Index (RAI), quantifying the shifting balance between PETs and DETs. Our model explores how asymmetric technological advancement, particularly logistic AI-driven PET growth versus stepwise DET improvements, expands the band of uncertainty surrounding proliferation detectability. Through replicable scenario-based simulations, we evaluate the impact of varying PET growth rates and DET investment strategies on cumulative nuclear breakout risk. We identify a strategic fork ahead, where detection may no longer suffice without broader PET governance. Governments and international organizations should accordingly invest in policies and tools agile enough to keep pace with tomorrow's technology.

Google is still aiming for its "moonshot" 2030 energy goals The company's electricity demand has doubled since 2020, making its end-of-decade target more of a challenge. Last week, we hosted EmTech MIT, MIT Technology Review's annual flagship conference in Cambridge, Massachusetts. Over the course of three days of main-stage sessions, I learned about innovations in AI, biotech, and robotics. But as you might imagine, some of this climate reporter's favorite moments came in the climate sessions. I was listening especially closely to my colleague James Temple's discussion with Lucia Tian, head of advanced energy technologies at Google. They spoke about the tech giant's growing energy demand and what sort of technologies the company is looking to to help meet it.

An elite group of companies known as the "Six Tigers"--Stepfun, Zhipu, Minimax, Moonshot, 01.AI, and Baichuan--are generally considered to be at the forefront of China's AI sector. But alongside them, research-focused firms like DeepSeek and ModelBest continue to grow in influence. Some, such as Minimax and Moonshot, are giving up on costly foundational model training to hone in on building consumer-facing applications on top of others' models. Others, like Stepfun and Infinigence AI, are doubling down on research, driven in part by US semiconductor restrictions. We have identified these four Chinese AI companies as the ones to watch.

The generation and editing of floor plans are critical in architectural planning, requiring a high degree of flexibility and efficiency. Existing methods demand extensive input information and lack the capability for interactive adaptation to user modifications. This paper introduces ChatHouseDiffusion, which leverages large language models (LLMs) to interpret natural language input, employs graphormer to encode topological relationships, and uses diffusion models to flexibly generate and edit floor plans. This approach allows iterative design adjustments based on user ideas, significantly enhancing design efficiency. Compared to existing models, ChatHouseDiffusion achieves higher Intersection over Union (IoU) scores, permitting precise, localized adjustments without the need for complete redesigns, thus offering greater practicality. Experiments demonstrate that our model not only strictly adheres to user specifications but also facilitates a more intuitive design process through its interactive capabilities.

It was early January 2016, and I had just joined Google X, Alphabet's secret innovation lab. My job: help figure out what to do with the employees and technology left over from nine robot companies that Google had acquired. Andy "the father of Android" Rubin, who had previously been in charge, had suddenly left under mysterious circumstances. Larry Page and Sergey Brin kept trying to offer guidance and direction during occasional flybys in their "spare time." Astro Teller, the head of Google X, had agreed a few months earlier to bring all the robot people into the lab, affectionately referred to as the moonshot factory.

If you want evidence of Microsoft's progress towards its environmental "moonshot" goal, then look closer to earth: at a building site on a west London industrial estate. The company's Park Royal datacentre is part of its commitment to drive the expansion of artificial intelligence (AI), but that ambition is jarring with its target of being carbon negative by 2030. Microsoft says the centre will be run fully on renewable energy. However, the construction of datacentres and the servers they are filled with means that the company's scope 3 emissions – such as CO2 related to the materials in its buildings and the electricity people consume when using products such as Xbox – are more than 30% above their 2020 level. As a result, the company is exceeding its overall emissions target by roughly the same rate.

CLAIRE and euRobotics, two European non-profit organisations in the area of AI and robotics, have announced an ambitious plan to establish Europe as a powerhouse in trustworthy artificial intelligence (AI) by 2030. This "moonshot" aims to "provide European citizens, industries, and public organisations with reliable and ethical AI alternatives, creating systems aligned with European values and boosting global competitiveness. The initiative calls for a pan-European effort, pooling talent and resources to overcome the current technological dependency on non-European big tech firms". According to Chair of the Board of CLAIRE directors, Holger Hoos, "Europe has a storied history of rising to technological challenges and emerging with global solutions. From CERN to the European Space Agency, we've turned collaboration into innovation. Now, as AI begins to permeate every aspect of our work and lives, it's imperative we forge our own path, ensuring the broad availability of trustworthy AI systems with European values at their core."