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By Rhiannon Williamsarchive pageJanuary 26, 2026 This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. Meet the new biologists treating LLMs like aliens   How large is a large language model? We now coexist with machines so vast and so complicated that nobody quite understands what they are, how they work, or what they can really do—not even the people who build them.That’s a problem. Even though nobody fully understands how it works—and thus exactly what its limitations might be—hundreds of millions of people now use this technology every day.  To help overcome our ignorance, researchers are studying LLMs as if they were doing biology or neuroscience on vast living creatures—city-size xenomorphs that have appeared in our midst. And they’re discovering that large language models are even weirder than they thought. Read the full story.—Will Douglas Heaven
This is our latest story to be turned into a MIT Technology Review Narrated podcast, which we publish 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. And mechanistic interpretability, the technique these researchers are using to try and understand AI models, is one of our 10 Breakthrough Technologies for 2026. Check out the rest of the list here!
Job titles of the future: Head-transplant surgeon The Italian neurosurgeon Sergio Canavero has been preparing for a surgery that might never happen. His idea? Swap a sick person’s head—or perhaps just the brain—onto a younger, healthier body.Canavero caused a stir in 2017 when he announced that a team he advised in China had exchanged heads between two corpses. But he never convinced skeptics that his technique could succeed—or to believe his claim that a procedure on a live person was imminent. Canavero may have withdrawn from the spotlight, but the idea of head transplants isn’t going away. Instead, he says, the concept has recently been getting a fresh look from life-extension enthusiasts and stealth Silicon Valley startups. Read the full story. —Antonio Regalado This story is from the latest print issue of MIT Technology Review magazine, which is all about exciting innovations. If you haven’t already, subscribe now to receive future issues once they land. The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Big Tech is facing multiple high-profile social media addiction lawsuits Meta, TikTok and YouTube will face parents’ accusations in court this week. (WP $)+ It’s the first time they’re defending against these claims before a jury in a court of law. (CNN)2 Power prices are surging in the world’s largest data center hubVirginia is struggling to meet record demand during a winter storm, partly because of the centers’ electricity demands. (Reuters)+ Why these kinds of violent storms are getting harder to forecast. (Vox)+ AI is changing the grid. Could it help more than it harms? (MIT Technology Review)3 TikTok has started collecting even more data on its usersIncluding precise information about their location. (Wired $)4 ICE-watching groups are successfully fighting DHS efforts to unmask themAn anonymous account holder sued to block ICE from identifying them—and won. (Ars Technica)5 A new wave of AI companies want to use AI to make AI betterThe AI ouroboros is never-ending. (NYT $)+ Is AI really capable of making bona fide scientific advancements? (Undark)+ AI trained on AI garbage spits out AI garbage. (MIT Technology Review) 6 Iran is testing a two-tier internetMeaning its current blackout could become permanent. (Rest of World)7 Don’t believe the humanoid robot hypeEven a leading robot maker admits that at best, they’re only half as efficient as humans. (FT $)+ Tesla wants to put its Optimus bipedal machine to work in its Austin factory. (Insider)+ Why the humanoid workforce is running late. (MIT Technology Review) 8 AI is changing how manufacturers create new productsIncluding thinner chewing gum containers and new body wash odors. (WSJ $)+ AI could make better beer. Here’s how. (MIT Technology Review)9 New Jersey has had enough of e-bikes 🚲But will other US states follow its lead? (The Verge)10 Sci-fi writers are cracking down on AIHuman-produced works only, please. (TechCrunch)+ San Diego Comic-Con was previously a safe space for AI-generated art. (404 Media)+ Generative AI is reshaping South Korea’s webcomics industry. (MIT Technology Review) Quote of the day “Choosing American digital technology by default is too easy and must stop.” —Nicolas Dufourcq, head of French state-owned investment bank Bpifrance, makes his case for why Big European companies should use European-made software as tensions with the US rise, the Wall Street Journal reports.
One more thing
The return of pneumatic tubesPneumatic tubes were once touted as something that would revolutionize the world. In science fiction, they were envisioned as a fundamental part of the future—even in dystopias like George Orwell’s 1984, where they help to deliver orders for the main character, Winston Smith, in his job rewriting history to fit the ruling party’s changing narrative.In real life, the tubes were expected to transform several industries in the late 19th century through the mid-20th. For a while, the United States took up the systems with gusto.But by the mid to late 20th century, use of the technology had largely fallen by the wayside, and pneumatic tube technology became virtually obsolete. Except in hospitals. Read the full story. —Vanessa Armstrong We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet 'em at me.) + You really can’t beat the humble jacket potato for a cheap, comforting meal. + These tips might help you whenever anxiety strikes. ($)+ There are some amazing photos in this year’s Capturing Ecology awards.+ You can benefit from meditation any time, anywhere. Give it a go! by Rhiannon WilliamsShareShare story on linkedinShare story on facebookShare story on emailPopular10 Breakthrough Technologies 2026Amy NordrumThe great AI hype correction of 2025Will Douglas HeavenChina figured out how to sell EVs. Now it has to deal with their aging batteries.Caiwei ChenThe 8 worst technology flops of 2025Antonio RegaladoDeep DiveThe DownloadThe Download: AI’s impact on the economy, and DeepSeek strikes againPlus: OpenAI is sounding the "code red" alarm
By Rhiannon Williamsarchive pageThe Download: China’s dying EV batteries, and why AI doomers are doubling downPlus: TikTok has finally signed a deal to keep operating in the US
By Rhiannon Williamsarchive pageThe Download: sodium-ion batteries and China’s bright tech futurePlus: This company is developing gene therapies for muscle growth, erectile dysfunction, and “radical longevity”
By Charlotte Jeearchive pageThe Download: the worst technology of 2025, and Sam Altman’s AI hypePlus: China has built a major chip-making machine
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The article explores the evolving relationship between humans and increasingly complex artificial intelligence, specifically focusing on Large Language Models (LLMs) and their growing complexity. Researchers are beginning to treat these AI models as if they were living organisms, much like xenomorphs from science fiction, attempting to understand their inner workings through a process called mechanistic interpretability. This approach seeks to unravel the “black box” of LLMs, revealing the underlying mechanisms that drive their outputs.

A key aspect of this investigation is the disconcerting discovery that LLMs are, in fact, incredibly strange. Their behavior isn't easily predictable, and their internal logic remains largely opaque, even to those who build them. This realization highlights the significant challenges in assessing and controlling AI systems, particularly as their capabilities continue to expand. The article suggests that the current approach of simply scaling up AI models – increasing size and data – is reaching a point of diminishing returns and that a deeper understanding of how these systems truly operate is now critical. The use of mechanistic interpretability represents a shift towards a more biological, systematic approach to AI study.

The article then pivots to examine the concept of “head transplants” spearheaded by neurosurgeon Sergio Canavero. Canavero’s audacious proposal, initially met with skepticism, has recently garnered renewed interest from life-extension enthusiasts and stealth Silicon Valley startups. Despite the lack of tangible progress and the inherent technical challenges, the idea of transferring a human brain to a new body is being re-evaluated, indicating a potential future direction for bioengineering and neuroscience.

Beyond these specific examples, the article highlights broader trends in the technology landscape. There’s a growing awareness of the limitations of simply scaling AI, with a renewed focus on developing more interpretable and understandable models. Simultaneously, the “AI ouroboros” – the tendency for AI to be trained on AI-generated content, resulting in a feedback loop of increasingly flawed outputs – is a significant concern. This cycle amplifies existing biases and inaccuracies, demonstrating the need for careful oversight and robust evaluation methods.

Furthermore, the piece touches upon anxieties surrounding artificial intelligence, with some observers – dubbed “doomers” – dubbing the current state of AI development a “code red,” suggesting imminent and catastrophic consequences. This reflects broader concerns about the potential societal impacts of advanced AI, fueling a trend of preparing for a potentially negative future.

Finally, several tangential stories contribute to the overall theme. These include the rise of pneumatic tubes, which were once envisioned as a revolutionary transportation system but ultimately faded into obsolescence; the increasing use of e-bikes, leading to local regulations; the exploration of AI’s impact on webcomics; and the persistent challenges in manufacturing with AI. These diverse anecdotes illustrate the broader, interconnected nature of technological innovation and the disruptive potential of emerging technologies. The return of pneumatic tubes is a nostalgic reminder of past technological optimism and cautionary tale of unfulfilled promises.