You've probably heard that statistic that every search on ChatGPT uses the equivalent of a bottle of water. And while that's technically true, it misses some of the nuance. The MIT Technology Review dropped a massive report that reveals how the artificial intelligence industry uses energy -- and exactly how much energy it costs to use a service like ChatGPT. The report determined that the energy cost of large-language models like ChatGPT cost anywhere from 114 joules per response to 6,706 joules per response -- that's the difference between running a microwave for one-tenth of a second to running a microwave for eight seconds. The lower-energy models, according to the report, use less energy because they uses fewer parameters, which also means the answers tend to be less accurate.

On Wednesday, OpenAI announced that it had acquired the startup of iPhone designer Jony Ive, a big win for the company. Ive's startup is called io, and the purchase price is nearly 6.5 billion, according to Bloomberg, which would make it OpenAI's biggest acquisition to date. The official announcement didn't contain much detail and mostly consisted of Altman and Ive gushing about each other. "Two years ago, Jony Ive and the creative collective LoveFrom, quietly began collaborating with Sam Altman and the team at OpenAI. A collaboration built upon friendship, curiosity and shared values quickly grew in ambition. Tentative ideas and explorations evolved into tangible designs. The ideas seemed important and useful. They were optimistic and hopeful. They reminded us of a time when we celebrated human achievement, grateful for new tools that helped us learn, explore and create...We gathered together the best hardware and software engineers, the best technologists, physicists, scientists, researchers and experts in product development and manufacturing. Many of us have worked closely for decades. The io team, focused on developing products that inspire, empower and enable, will now merge with OpenAI to work more intimately with the research, engineering and product teams in San Francisco."

Despite their remarkable successes, state-of-the-art large language models (LLMs), including vision-and-language models (VLMs) and unimodal language models (ULMs), fail to understand precise semantics. For example, semantically equivalent sentences expressed using different lexical compositions elicit diverging representations. The degree of this divergence and its impact on encoded semantics is not very well understood.

Although the Cannes Film Festival is the world's most prestigious movie showcase, its spotlight rarely falls on nonfiction film. Years go by without a single documentary competing for its biggest honor, the Palme d'Or, and there is no separate documentary prize. Juliette Binoche, the president of this year's jury, devoted part of her opening-night remarks to Fatma Hassona, the Palestinian photojournalist who was killed in an Israeli airstrike the day after it was announced that her documentary Put Your Soul on Your Hand and Walk would be premiering at Cannes. But the film itself was slotted into a low-profile sidebar devoted to independent productions. The festival did, however, roll out the red carpet for The Six Billion Dollar Man, Eugene Jarecki's portrait of WikiLeaks founder Julian Assange, which premiered out of competition on Wednesday evening.

K and M are short for thousand and million respectively. True_neg denotes whether it includes true negative feedback. We only show the statistics of the QK-video (QKV) and QK-article (QKA) in this table. We show the difference between Tenrec and other popular recommendation datasets in Table1. First, most datasets contain only a single scenario. Without overlapped users and items, it is difficult to develop and evaluate transfer learning recommendation methods. In addition, Tenrec contains very rich positive user feedback, which can be used to evaluate the multi-task learning and preference-level transfer learning tasks. Third, compared with most recommendation datasets, Tenrec has true negative examples, which can be used to evaluate more realistic CTR prediction task.

If the AI lovefest of Google I/O 2025 were a TV show, you might be tempted to call it It's Always Sunny in Mountain View. But here's a better sitcom analogy for the event that added AI Mode to all U.S. search results, whether we want it or not. It's The Good Place, in which our late heroes are repeatedly assured that they've gone to a better world. A place where everything is fine, all is as it seems, and search quality just keeps getting better. Don't worry about ever-present and increasing AI hallucinations here in the Good Place, where the word "hallucination" isn't even used.

The short-lived firing of Sam Altman, the CEO of possibly the world's most important AI company, was sensational. When he was sacked by OpenAI's board members, some of them believed the stakes could not have been higher – the future of humanity – if the organisation continued under Altman. Imagine Succession, with added apocalypse vibes. In early November 2023, after three weeks of secret calls and varying degrees of paranoia, the OpenAI board agreed: Altman had to go. After his removal, Altman's most loyal staff resigned, and others signed an open letter calling for his reinstatement.

Google's AI Era is officially officially here, and at the center of it is a new generative video model called Flow. At the Google I/O 2025 keynote event on May 20, Google unveiled a new suite of AI video tools, powered by state-of-the-art models. The offspring of media models Veo 3 and Imagen 4, Flow is Google's answer to OpenAI's Sora -- AI tools for a new era in video generation for filmmakers and creatives. However, unlike Sora, Flow comes with native audio generation baked right in. Pitched as an "AI filmmaking tool built for creatives, by creatives," Flow is the tech giant's latest attempt to demo the power of AI as a use case in reshaping the creative process.

Google has injected AI features into practically all of its products, now including Chrome. At Google I/O, the tech giant's annual event, Google announced that Gemini is coming to Chrome as it transitions into the generative AI era, antitrust issues be damned. Gemini's integration with the browser means users can ask questions about information on sites, or even navigate to those sites, while browsing the web. Gemini on Chrome will be available to Chrome users on Windows and macOS, but only for paying subscribers to Google AI Pro and AI Ultra plans, which cost 20 and 250 a month, respectively. Meanwhile, Google is in the remedial phase of its antitrust case, which the U.S. Department of Justice is prosecuting. Google has been ruled a monopoly for leveraging its Chrome browser in anti-competitive ways.

Google just cracked open the future of search, and it talks back. During today's Google I/O 2025 keynote event, Google announced that it is now rolling out the AI Mode search tool to everyone in the United States. Powered by Gemini, AI Mode will now include new "Deep Search" features and some agentic capabilities. AI Mode represents the biggest shift in Google Search since its inception. It's no longer just a place to find links.