"We're going to get into a period of potentially unprecedented I.P.O. "But we are confident they're executable given the scale of these companies and the investor interest." These listings could create an enormous bonanza for Wall Street and Silicon Valley after years of lackluster offerings. They could set off a feeding frenzy among public market investors who have been waiting to get a piece of the A.I. boom, and Wall Street banks stand to make hundreds of millions facilitating the listings. That is stoking more excitement for the A.I. boom as it enters its fourth year, even as the question of a bubble intensifies.

Two years ago, companies like Meta and OpenAI were united against military use of their tools. Now all of that has changed. At the start of 2024, Anthropic, Google, Meta, and OpenAI were united against military use of their AI tools. But over the next 12 months, something changed. In January, OpenAI quietly rescinded its ban on using AI for "military and warfare" purposes, and soon after it was reported to be working on "a number of projects" with the Pentagon. In November, in the same week that Donald Trump was reelected US president, Meta announced that the United States and select allies would be able to employ Llama for defense uses.

A poster featuring an image of billionaire Elon Musk, calling for users of his X social media platform to delete their accounts due to the artificial intelligence chatbot Grok's image-creation feature, is seen at a bus stop in London on Tuesday. PARIS - Elon Musk's company xAI has faced global backlash in recent days over sexualized "deepfake" images of women and children created by its Grok chatbot. Here are the essential facts about the scandal, how governments have responded and the company's attempts to cool the controversy. Grok -- Musk's version of the chatbots also offered by OpenAI and other generative AI companies -- has its own account on the X social media network allowing users to interact with it. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Deep double descent is one of the key phenomena underlying the generalization capability of deep learning models. In this study, epoch-wise double descent, which is delayed generalization following overfitting, was empirically investigated by focusing on the evolution of internal structures. Fully connected neural networks of three different sizes were trained on the CIFAR-10 dataset with 30% label noise. By decomposing the loss curves into signal contributions from clean and noisy training data, the epoch-wise evolutions of internal signals were analyzed separately. Three main findings were obtained from this analysis. First, the model achieved strong re-generalization on test data even after perfectly fitting noisy training data during the double descent phase, corresponding to a "benign overfitting" state. Second, noisy data were learned after clean data, and as learning progressed, their corresponding internal activations became increasingly separated in outer layers; this enabled the model to overfit only noisy data. Third, a single, very large activation emerged in the shallow layer across all models; this phenomenon is referred as "outliers," "massive activations," and "super activations" in recent large language models and evolves with re-generalization. These empirical findings directly link the recent key phenomena of "deep double descent," "benign over-fitting," and "large activation", and support the proposal of a novel scenario for understanding deep double descent. Artificial intelligence technologies have undergone remarkable development in recent years, introducing substantial transformation to social structures and influencing various academic fields. Although these models form the core of such technologies, the fundamental principles underlying their high generalization capability when trained on real-world data remain poorly understood. Recent numerical experiments have empirically revealed various intriguing phenomena related to this gap.

Why the World's Best AI Systems Are Still So Bad at Pokémon Pillay is an editorial fellow at TIME. Pillay is an editorial fellow at TIME. Right now, live on Twitch, you can watch three of the world's smartest AI systems-- GPT 5.2, Claude Opus 4.5, and Gemini 3 Pro --doing their best to beat classic Pokémon games. At least by human standards, they are not very good. The systems are slow, overconfident, and often confused.

Improvements to a number of Apple services - including a more personalised version of its virtual assistant, Siri - are to be powered with AI provided by Google. The tech giants have announced a multi-year collaboration which will see the iPhone-maker base some of its key tech on Google's Gemini AI models. In a joint statement, the two firms said the partnership would unlock innovative new experiences for Apple users. However, experts say it demonstrates how Apple's cautious approach to building and rolling out its own AI tools has left it reliant on other companies. By outsourcing the foundational layer of its AI to Google, Apple is effectively admitting that its internal efforts couldn't compete with Google's Gemini in terms of capability and scale in the short term, IDC analyst Francisco Jeronimo said.

Plus: This company is developing gene therapies for muscle growth, erectile dysfunction, and "radical longevity" For decades, lithium-ion batteries have powered our phones, laptops, and electric vehicles. But lithium's limited supply and volatile price have led the industry to seek more resilient alternatives. They work much like lithium-ion ones: they store and release energy by shuttling ions between two electrodes. But unlike lithium, a somewhat rare element that is currently mined in only a handful of countries, sodium is cheap and found everywhere. Read why it's poised to become more important to our energy future. Sodium-ion batteries are one of 10 Breakthrough Technologies this year.

Apple and Google have confirmed that Gemini's models power the new version of Siri and other generative AI features. Here's part of it: "Apple determined that Google's Al technology provides the most capable foundation for Apple Foundation Models Apple Intelligence will continue to run on Apple devices and Private Cloud Compute, while maintaining Apple's industry-leading privacy standards." In June, it was reported that Apple was considering partnerships with OpenAI and Anthropic for Siri (the voice assistant can currently tap ChatGPT for certain queries as part of Apple Intelligence). Two months later, Google emerged as a contender. Another report suggested Apple might build the new Siri using a custom version of Gemini -- and that it would pay Google around $1 billion a year for the privilege.

If you want to put people back on the moon, don't gut the agency in charge of getting them there. The senator wanted a promise. For the last six years--or maybe the last decade or quarter century, depending on how you count it--the United States and China had been locked in a space race, a contest to see which nation could put its people on the moon . Senator Ted Cruz wanted President Donald Trump's nominee to run NASA, Jared Isaacman, to pledge that the US would not lose. Cruz brought a little surprise to Isaacman's confirmation hearing last April. It was a poster of the moon. On one side stood three astronauts and a giant Chinese flag. On the other were two more figures in space suits, with the tiniest Stars and Stripes planted in the lunar soil . Cruz apologized for the imbalance. "My team used ChatGPT," explained the senator, who chairs the committee that oversees NASA. Then Cruz, with a bit more seriousness, asked Isaacman, "Do we have your commitment that you will not allow the scenario on the right of this poster to happen? That China will not beat us to the moon?" Isaacman, a billionaire entrepreneur who had paid for his own missions to space, replied, "Senator, I only see the left-hand portion of that poster."

New York governor Kathy Hochul says she will propose a new law allowing limited autonomous vehicle pilots in smaller cities. Full-blown services could be next. As self-driving car services from Alphabet's Waymo, Amazon's Zoox, and Tesla have slowly, quietly expanded across the US, one big, important state has mostly stayed mum: New York . The union's fourth most populous state has some of the tightest laws governing autonomous vehicles, requiring companies approved to test in the state to only do so with a driver behind the wheel. There's no current path for companies to operate the sort of commercial robotaxi services like the sort seen in San Francisco or Las Vegas.