However, this moment creates a chance to do things differently. Because away from the self-centeredness of Silicon Valley, a quiet, grounded sense of resistance is reactivating. In China, people are seeking help from AI-generated avatars to process their grief after a family member passes away. Our story about this trend is the latest to be turned into a MIT Technology Review Narrated podcast, which we're publishing each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it's released.

This moment creates an existential opening, a chance to do things differently. Because away from the self-centeredness of Silicon Valley, a quiet, grounded sense of resistance is reactivating. In 2007, as the iPhone emerged, the maker movement was taking shape. DIY and open hardware enthusiasts gathered in person at Maker Faires--large events where people of all ages tinkered and shared their inventions in 3D printing, robotics, electronics, and more. Motivated by fun, self-fulfillment, and shared learning, the movement birthed companies like MakerBot, Raspberry Pi, Arduino, and (my own education startup) littleBits from garages and kitchen tables.

The legendary designer behind Apple's iPhone, Jony Ive, has joined OpenAI to create devices tailored for using generative artificial intelligence, according to a video posted Wednesday by the ChatGPT maker. Ive and his team will take over design at OpenAI as part of an acquisition of his startup named "IO" valued at 6.5 billion. Sharing no details, OpenAI chief executive Sam Altman said in the video that a prototype Ive shared with him "is the coolest piece of technology that the world will have ever seen."

Specialized hardware accelerators aid the rapid advancement of artificial intelligence (AI), and their efficiency impacts AI's environmental sustainability. This study presents the first publication of a comprehensive AI accelerator life-cycle assessment (LCA) of greenhouse gas emissions, including the first publication of manufacturing emissions of an AI accelerator. Our analysis of five Tensor Processing Units (TPUs) encompasses all stages of the hardware lifespan - from raw material extraction, manufacturing, and disposal, to energy consumption during development, deployment, and serving of AI models. Using first-party data, it offers the most comprehensive evaluation to date of AI hardware's environmental impact. We include detailed descriptions of our LCA to act as a tutorial, road map, and inspiration for other computer engineers to perform similar LCAs to help us all understand the environmental impacts of our chips and of AI. A byproduct of this study is the new metric compute carbon intensity (CCI) that is helpful in evaluating AI hardware sustainability and in estimating the carbon footprint of training and inference. This study shows that CCI improves 3x from TPU v4i to TPU v6e. Moreover, while this paper's focus is on hardware, software advancements leverage and amplify these gains.

The Biden administration this week introduced new export restrictions designed to control AI's progress globally and ultimately prevent the most advanced AI from falling into China's hands. The rule is just the latest in a string of measures put in place by Donald Trump and Joe Biden to keep Chinese AI in check. With prominent AI figures including OpenAI's Sam Altman and Anthropic's Dario Amodei warning of the need to "beat China" in AI, the Trump administration may well escalate things further. Paul Triolo is a partner at DGA Group, a global consulting firm, a member of the council of foreign relations, and a senior adviser to the University of Pennsylvania's Penn Project on the Future of US-China Relations. Alvin Graylin is an entrepreneur who previously ran China operations for the Taiwanese electronics firm HPC.

The rumors were true! AMD unveiled the Radeon RX 9070 and 9070 XT during the company's CES 2025 keynote on Monday, powered by the next-generation RDNA 4 architecture with a new AI-focused version of FSR (FidelityFX Super Resolution) in tow. Gamers hoping for deep details were left wanting, however, as AMD classified this as a "preview" without much hard information. It was more of a tease than anything, honestly, though it's clear that AMD is finally, truly embracing AI hardware within GPUs. Here's what we do know. For years, AMD has battled Nvidia's vaunted DLSS using (mostly) graphics cores rather than integrating dedicated AI hardware. AMD says RDNA 4 was built from the ground up on TSMC's 4nm process to "supercharge" AI performance, driven by a massive overhaul to the AI compute architecture.

The new year is a time for reflection, renewal, and rampant speculation about what wonders (or fresh hell) the future might hold. No place does this mix of anxiety and forward-looking techno-evangelism spring forth more profusely than at CES. The giant consumer tech showcase is barreling down on Las Vegas starting January 7, bringing with it a whirlwind of fuss about the newest gadgets and devices. And yes, you bet all these things are going to be packed full of AI features. You're probably going to be asked to wear many of them.

We're witnessing the birth of AI-ese, and it's not what anyone could have guessed. If you've spent enough time using AI assistants, you'll have noticed a certain quality to the responses generated. Without a concerted effort to break the systems out of their default register, the text they spit out is, while grammatically and semantically sound, ineffably generated. Some of the tells are obvious. The fawning obsequiousness of a wild language model hammered into line through reinforcement learning with human feedback marks chatbots out. Which is the right outcome: eagerness to please and general optimism are good traits to have in anyone (or anything) working as an assistant.

Apple's designer exodus continues as product design chief Tang Tan is leaving the company and joining Jony Ive's design firm LoveFrom, according to Bloomberg's Mark Gurman. There, he'll reportedly work on a new artificial intelligence hardware project backed by OpenAI's Sam Altman with aim of creating devices deploying the latest deep learning technology. Tan was in charge of design for Apple's main products including the iPhone, Watch and AirPods, so his departure leaves a sizable hole. As part of LoveFrom, Tan will act as hardware design lead for the new AI project, with Altman providing the software running underneath. All products are supposedly in the early concept phases, with a focus on devices for the home.

We know, as you do, that artificial intelligence is driving a lot of spending at IT organizations and is probably the fundamental driver of spending by the hyperscalers and cloud builders that have, thus far, benefitted most from the machine learning revolution. But just how much money are companies sinking into AI, and how will that grow over time? We have not seen a lot of good data on this, and the market researchers at IDC, as usual, have been the most vocal about how they dice and slice the AI market in their public statements, which dribble out some insight here and there to keep their name out there and to drive deeper engagements with AI startups, their investors, IT suppliers who are chasing this market, and large enterprises that are on the forefront of commercializing AI in their application stacks. What sent us down this AI spending rathole was some numbers that IDC released on March 7, which talks about worldwide spending on AI-Centric systems, including hardware, software, and services. AI-centric means that without the AI component, an application will not function.