Everything Is Content for the'Clicktatorship' In the second Trump administration, online conspiracy theories are shaping real-world policies like never before. In President Donald Trump's second term, everything is content . Videos of immigration raids are shared widely on X by the Department of Homeland Security (DHS), conspiracy theories dictate policy, and prominent right-wing podcasters and influencers have occupied high-level government roles. The second Trump administration is, to put it bluntly, very online. Trump and his supporters have long trafficked in--and benefited from-- misinformation and conspiracy theories, leveraging them to build visibility on social media platforms and set the tone of national conversations.

This year, hype around AI really exploded, and so did concerns about AI's environmental footprint. We also saw some surprising biotech developments. It's been a busy and productive year here at . We published magazine issues on power, creativity, innovation, bodies, relationships, and security . We hosted 14 exclusive virtual conversations with our editors and outside experts in our subscriber-only series, Roundtables, and held two events on MIT's campus. And we published hundreds of articles online, following new developments in computing, climate tech, robotics, and more.

The Cybertruck, sycophantic AI, and humanoid robots all made this year's list of the biggest technology failures. Welcome to our annual list of the worst, least successful, and simply dumbest technologies of the year. This year, politics was a recurring theme. Donald Trump swept back into office and used his executive pen to reshape the fortunes of entire sectors, from renewables to cryptocurrency. The wrecking-ball act began even before his inauguration, when the president-elect marketed his own memecoin, $TRUMP, in a shameless act of merchandising that, of course, we honor on this year's worst tech list. We like to think there's a lesson in every technological misadventure.

Quantum navigation could solve the military's GPS jamming problem The rise of GPS vulnerability is putting more resilient, atom-based navigational tools on the map. The Royal Navy partnered with Infleqtion to test a quantum clock on the uncrewed submarine XV Excalibur. In late September, a Spanish military plane carrying the country's defense minister to a base in Lithuania was reportedly the subject of a kind of attack --not by a rocket or anti-aircraft rounds, but by radio transmissions that jammed its GPS system. The flight landed safely, but it was one of thousands that have been affected by a far-reaching Russian campaign of GPS interference since the 2022 invasion of Ukraine. The growing inconvenience to air traffic and risk of a real disaster have highlighted the vulnerability of GPS and focused attention on more secure ways for planes to navigate the gauntlet of jamming and spoofing, the term for tricking a GPS receiver into thinking it's somewhere else. US military contractors are rolling out new GPS satellites that use stronger, cleverer signals, and engineers are working on providing better navigation information based on other sources, like cellular transmissions and visual data.

But they certainly wish people were still taking their warnings really seriously. It's a weird time to be an AI doomer. This small but influential community of researchers, scientists, and policy experts believes, in the simplest terms, that AI could get so good it could be bad--very, very bad--for humanity. Though many of these people would be more likely to describe themselves as advocates for AI safety than as literal doomsayers, they warn that AI poses an existential risk to humanity. They argue that absent more regulation, the industry could hurtle toward systems it can't control. They commonly expect such systems to follow the creation of artificial general intelligence (AGI), a slippery concept generally understood as technology that can do whatever humans can do, and better. Though this is far from a universally shared perspective in the AI field, the doomer crowd has had some notable success over the past several years: helping shape AI policy coming from the Biden administration, organizing prominent calls for international "red lines " to prevent AI risks, and getting a bigger (and more influential) megaphone as some of its adherents win science's most prestigious awards. But a number of developments over the past six months have put them on the back foot.

We'll keep following these developments, but this just wasn't their year. If you're a longtime reader, you probably know that our newsroom selects 10 breakthroughs every year that we think will define the future . This group exercise is mostly fun and always engrossing, but at times it can also be quite difficult. We collectively pitch dozens of ideas, and the editors meticulously review and debate the merits of each. We agonize over which ones might make the broadest impact, whether one is too similar to something we've featured in the past, and how confident we are that a recent advance will actually translate into long-term success. There is plenty of lively discussion along the way.

"Everyone thinks they're on this big now," Debbie said, refilling her glass. "I've had it with the journey. I've had it with you people." "I don't think I'm on a journey," Burt said. Life's too short to find out who we really are." It was the first time the six of them had got together for dinner in more than a year (since Maria's diagnosis), and after such a long time (and in celebration of Maria's remission) they'd expected to have more interesting things to tell one another, deeper things, but they were entering dessert territory now, a cake was on the table, and only superficial topics had been broached: Ervin's promotion, Jane and Burt's move to the suburbs, Katherine's recent purchase of a metabolism-tracking device--a pen-shaped item and the cause of Debbie's rant. "How much can you know about yourself, exactly?" she said. "The therapy, the vision quests, the birth charts--do we really need the data on metabolic flexibility, too?" Jane, in Katherine's defense, said that, the more you knew about yourself, the more useful you could be to society. Knowing whether Kat is in fat-or carb-burning mode doesn't help anyone." As a result of Katherine declining cake five minutes earlier, no one had touched it. No one, Debbie included, really wanted to. They'd all overeaten already, drunk too much, made private plans to atone for it the next day. The cake presented a challenge, it sat there taunting them, and Debbie knew this, that you couldn't serve cake to a group of fortysomethings without causing ripples, but what else could she have done? She got it, no one wanted to put on weight, but this was a gorgeous princess cake, just gorgeous, she'd had to drive all the way to Andersonville to get it from that Swedish bakery everyone talked about. Staring at it now, though, she wondered if the cake didn't look a little bit like a tit, the smooth half sphere, the small pink marzipan flower nippling the top of it--and, oh, God, did think it looked like a tit?

AI is eminently capable of political persuasion and could automate it at a mass scale. In January 2024, the phone rang in homes all around New Hampshire. On the other end was Joe Biden's voice, urging Democrats to "save your vote" by skipping the primary. It sounded authentic, but it wasn't. The call was a fake, generated by artificial intelligence. Today, the technology behind that hoax looks quaint.

We present Apertus, a fully open suite of large language models (LLMs) designed to address two systemic shortcomings in today's open model ecosystem: data compliance and multilingual representation. Unlike many prior models that release weights without reproducible data pipelines or regard for content-owner rights, Apertus models are pretrained exclusively on openly available data, retroactively respecting `robots.txt` exclusions and filtering for non-permissive, toxic, and personally identifiable content. To mitigate risks of memorization, we adopt the Goldfish objective during pretraining, strongly suppressing verbatim recall of data while retaining downstream task performance. The Apertus models also expand multilingual coverage, training on 15T tokens from over 1800 languages, with ~40% of pretraining data allocated to non-English content. Released at 8B and 70B scales, Apertus approaches state-of-the-art results among fully open models on multilingual benchmarks, rivalling or surpassing open-weight counterparts. Beyond model weights, we release all scientific artifacts from our development cycle with a permissive license, including data preparation scripts, checkpoints, evaluation suites, and training code, enabling transparent audit and extension.

It's free and easy to nominate yourself or someone you know--here's how. We have some exciting news: Nominations are now open for's 2026 Innovators Under 35 competition. This annual list recognizes 35 of the world's best young scientists and inventors, and our newsroom has produced it for more than two decades. It's free to nominate yourself or someone you know, and it only takes a few moments. We're looking for people who are making important scientific discoveries and applying that knowledge to build new technologies. Or those who are engineering new systems and algorithms that will aid our work or extend our abilities.