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.

Check your subscription status, update your details and more. Powerful artificial intelligence models built by Chinese companies have gone from inducing widespread panic to being met with a shrug of the shoulders - what changed? When Chinese company DeepSeek released its open-source R1 model in January 2025, it made headlines around the world. The large language model (LLM) was reported to rival some of the most powerful AIs from US companies, but it was completely free for anyone to download. A trillion dollars was wiped off the value of US tech companies and US lawmakers immediately proposed banning it on government devices.

China's DeepSeek developing its own AI chip, sources say DeepSeek is designing its own chip for inference, the stage of artificial intelligence computing in which a trained model generates responses for users, sources said. Chinese startup DeepSeek is developing its own artificial intelligence chip, according to three people familiar with the matter, a push that could reduce its reliance on Nvidia and Huawei chips, which it has depended on to train and run its globally popular models. The chip is designed for inference -- the stage of AI computing in which a trained model generates responses for users -- rather than for training new models, the sources said. If successful, DeepSeek's expansion into semiconductor development would mark a major strategic shift for a company widely hailed in China as the country's AI champion, potentially adding to challenges faced by Chinese tech giant Huawei. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

It is reportedly hiring engineers and speaking to manufacturers. DeepSeek, the Chinese AI company which sometimes keeps tech executives awake at night, is reportedly looking to build its own silicon. The move comes as part of a push to reduce its reliance on third-party chip providers like Huawei and NVIDIA. If the report is accurate, it could signal another entrant in the fiercely competitive Chinese AI market. The report suggests DeepSeek is already in talks with manufacturing partners and has quietly begun hiring engineers to support the effort.

Plus: Meta is pausing an AI training program that tracks workers' keystrokes. It's a bit of a schlep to get to the top of ASML's newest machine. It's about the size of a double-decker bus, weighs more than 150 tons, and costs $400 million. But if you want to make the world's most powerful chips, a lithography system like this is essential. The AI era needs ever faster chips, and ASML's machines make that possible. They pattern chip features with extreme-ultraviolet light, or EUV--radiation outside the visible spectrum, produced by shooting lasers at tiny molten drops of tin tens of thousands of times a second.

Large Language Models (LLMs) have demonstrated notable capabilities across financial tasks, including financial report summarization, earnings call transcript analysis, and asset classification. However, their real-world effectiveness in managing complex fund investment remains inadequately assessed. A fundamental limitation of existing benchmarks for evaluating LLM-driven trading strategies is their reliance on historical back-testing, inadvertently enabling LLMs to "time travel" - leveraging future information embedded in their training corpora, thus resulting in possible information leakage and overly optimistic performance estimates. To address this issue, we introduce DeepFund, a live fund benchmark tool designed to rigorously evaluate LLM in real-time market conditions. Utilizing a multi-agent architecture, DeepFund connects directly with real-time stock market data - specifically data published after each model's pretraining cutoff - to ensure fair and leakage-free evaluations. Empirical tests on nine flagship LLMs from leading global institutions across multiple investment dimensions--including ticker-level analysis, investment decision-making, portfolio management, and risk control--reveal significant practical challenges.

Plus: The Pentagon says it used Grok in strikes on Iran. For decades, physicists have hunted for weakly interacting massive particles (WIMPs), a leading candidate for dark matter. But their search has run into a new problem: neutrinos. These tiny particles from the sun and other stars can create a "neutrino fog" that drowns out any signal of dark matter. Hitting the neutrino fog does not, however, mean an end to the search. Researchers just have to shift the focus of their hunt.

Plus: SpaceX is now valued higher than Amazon. Solar geoengineering, the controversial idea that we could deliberately intervene in the climate system to counteract global warming, is moving beyond computer simulations and into the practical engineering challenges required to make it real. Researchers are now working on aircraft, materials, and other systems for solar geoengineering. But as they delve into these details, they're finding that even early deployment would require significant new infrastructure, time, and investment. Find out what happens when solar geoengineering encounters the realities of trying to cool the planet . Scientists have a word for how we sense ourselves from the inside: interoception.

Plus: Anthropic has shut down access to its top models after a US directive. That's good for our health, but bad for the planet: it already accounts for 7% of global electricity use and 3% of greenhouse-gas emissions. Feeling the heat, scientists and startups are hoping to amp up solid-state cooling. These systems move heat through conductive materials, which could cool spaces and surfaces with fewer messy side effects. The catch is whether it can match the efficiency of traditional AC. Find out how the unconventional coolers aim to dial down AC emissions .

The Download: how the World Cup ball will fly and OpenAI's "super app" Plus: OpenAI plans to turn ChatGPT into a'super app' before its IPO. Why this year's World Cup ball may not fly as far Much is new about this month's FIFA World Cup tournament. It hosts more teams than ever before. It's the first to occur in three different host countries. And, like every World Cup for over half a century, it will employ a football with a brand-new design. Through wind-tunnel experiments, researchers found that long-distance kicks with Adidas's new Trionda ball might not travel as far as they did in the past.