Technology

1. Apple’s identity crisis
2. China’s new breakthrough
3. US-China race intensifies
4. AI isn’t social media
5. Cleaning robots’ big win

AI experts are learning a “bitter lesson” in biology, and agents hit the pageant stage.

Over the last decade, experts in artificial intelligence learned a “bitter lesson”: Their own knowledge was getting in the way of progress. “The actual contents of minds are tremendously, irredeemably complex,” computer scientist Richard Sutton wrote in 2019. The most successful AI breakthroughs involved humans getting out of the way and allowing increasingly powerful computers to take over.

The same humbling lesson is now being learned by scientists in the field of biology. I’ve spent most of this week in Boston, meeting with leading thinkers in biotech for a podcast series airing later this fall. It’s clear that what we think of as science has changed, and is about to change even more.

There’s a new generation of drugs about to hit the market that didn’t originate with elegant hypotheses, but rather from brute-force analyses of massive datasets. Future discoveries and therapies will come not from a human-like understanding of science, but by simple pattern recognition of new biological information at scale. It’s as if an unfathomable amount of spaghetti is being thrown against the biggest wall ever by computers and robots.

New scientific methods using nanotechnology and AI allow us to measure more aspects of human biology, such as the thousands of proteins found in human blood. Better computational methods are finding meaningful patterns in that data, making it even more valuable. And in the coming years, humanoid robots with dexterous hands will automate the other parts of lab work, such as handling mice, or slicing thin layers of tissue. Every lab will be able to operate 24/7, making it possible to do experiments that today take too long and cost too much.

Cloud labs will be able to use an AI chatbot to conceive of a research study, then simply hit a button to have it carried out in real life. AI models will operate in agentic loops, running physical experiments in fully automated labs, analyzing the results and then coming up with new experiments based on the findings.

Sutton’s bitter lesson is applicable to biology because so much of the human body — not just the mind — is still beyond our understanding. And we’ll find the way forward by industrializing trial-and-error experimentation until the breakthroughs materialize.

What comes next is going to be strange and, at times, controversial (imagine animal studies in this coming era). It will also save a lot of lives.

Apple pushes ahead in trade-secrets case

Apple is leveling up its legal battle with OpenAI, where it alleges the frontier lab and its staffers systematically executed a campaign to steal trade secrets. The iPhone maker sent letters to about 40 of its former employees who now work at OpenAI, demanding they meet with Apple’s lawyers, the Financial Times reported. The requests, which include orders not to destroy documents, come a week after Apple dropped a blockbuster lawsuit that, at first glance, appears to be a pretty good case — if it can be proven in court.

The theatrics around Apple’s suit and its letters may make it look like the aggressor, but the case is a glaring reminder that AI is a huge threat to Apple’s fundamental identity: selling simplicity in a bespoke ecosystem where everything “just works.” AI, which is the ultimate simplifier, takes disparate technologies and makes them disappear behind a simple chat interface in consumer tech, making Apple’s software ecosystem less relevant.

OpenAI, which famously hired Apple hardware designer Jony Ive a year ago, is already encroaching. Bloomberg earlier this week reported the company is planning to release a screen-free speaker, powered by its AI models, to control all the smart appliances in a person’s home.

The law may be on Apple’s side in the end, but by the time it wins a lawsuit against OpenAI, the decisive battles in the AI war might already be over.

What the release of Kimi K3 means for AI business models

The AI world is going nuts over the Kimi K3 AI model, the latest open-weight offering from Chinese startup Moonshot. While the new model is a big deal, the concern is somewhat misguided. For instance, Nvidia’s stock (and American markets broadly) took a hit over fears that China is closing the gap with the US. But if you’re an Nvidia shareholder, the excitement over K3 is pretty good news. In order to run the most capable version of Kimi K3, a 2.8-trillion-parameter model, you need a cluster of Nvidia GPUs that would total several million dollars. Frontier labs like Anthropic and OpenAI have a bit more to worry about, because the Kimi models perform at or near the frontier.

There’s now an established pattern: American frontier labs come out with state-of-the-art AI models. Chinese firms allegedly “distill” those models — they use them to extract a form of training data, which is then used to train new open-source models for anyone in the world to download.

This is not sustainable for the frontier labs. One view is that American models simply need to move faster, staying far enough ahead of the Chinese firms.

But AI models are now so powerful that the US government is requesting to keep them off the market for a month while it vets them for national security concerns, slowing US firms down.

Instead of building powerful AI models and then releasing them to the public, frontier labs could keep them locked up, and use them to build their own software businesses. Eventually, they’d become like holding companies.

Keeping the models secret could solve two problems at once: Chinese firms would be prevented from distillation, and the security concerns would go away. But it would also turn frontier-model companies into powerful conglomerates with a massive advantage over essentially every business in the world, ushering in the future that open-source advocates and critics of big tech companies fear.

AI fight complicates US-China competition

China is leaning into the fight with the US over artificial intelligence as the technology’s ramifications cleave the American public. Chinese leader Xi Jinping spoke for the first time at Shanghai’s AI conference today, telling the crowd that AI development should be a “symphony of international cooperation,” as the arms race intensifies. AI safety advocates in the US have been advocating for more cooperation between the US and China. The AI Futures Project laid out one such scenario in its research report published last week. The US is widely viewed as leading China on advanced models, but domestic backlash to data centers and labor market shifts could threaten that edge. New York imposed the nation’s first moratorium on data centers this week, and a group chaired by a former tea party activist is planning a nationwide day of protest against data centers tomorrow. Asked about the protests, the White House referred Semafor to a post in which Trump called New York’s move a “terrible decision” and data centers the “biggest Driving Forces in the Future for Jobs.”

— Morgan Chalfant

Can AI companies protect teens?

Frontier AI labs don’t want to be known for helping teens commit harm against themselves or others. “The principle here is to avoid the mistakes that were made before us,” Lauren Jonas, OpenAI’s head of youth well-being, told Semafor. “AI is not social media,” she said, arguing that teens primarily use its tools for schoolwork.

OpenAI on Thursday published its stance on why teens should have access to AI with safeguards like nudges to take breaks and time limits set by parents, saying kids will be less prepared for life as adults if they don’t practice with the technology when they are young. That’s a different approach than Anthropic’s, which requires users to enter a birthday that indicates they are more than 18 years old to use its AI products. Meta also just announced it will notify parents if their child discusses self-harm with its chatbot, following OpenAI’s lead.

Teens, however, need to buy into the idea by submitting their real ages and connecting a parent’s account — actions that they have little incentive to take. Major AI companies have employed machine learning that predicts users’ ages based on their queries, flagging accounts for additional verification, which is the most sophisticated method for protecting kids thus far. But if the last decade has shown us anything, it’s that teen safety is about more than product updates: It requires support from communities, schools, parents, and the kids themselves.

— Rachyl Jones

Robot-data startup taps huge funding

A record round of seed funding by a Munich-based robotics data startup reflects a hunger for real-world data to train humanoids — as well as companies’ ongoing flirtation with factory automation.

Microagi — which this week closed the $55 million funding round, the largest ever in Germany — made headlines in May when it rolled out a service in New York offering free apartment cleanings, so long as customers let the company record everything. It has licensed some of that data exclusively to frontier AI labs, but it is also helping to shape the “brains” of robots Microagi deploys in its customers’ factories, founder and CEO Bercan Kilic told Semafor.

The company consults with manufacturing and logistics firms, collecting data and footage from live production lines and later implementing automation where possible. It buys its hardware — often from Chinese robot-makers Unitree or UBTech — and leases it to factories where the company installs it — finetuned for each client.

This setup — Chinese bots injected with a German company’s software supplemented by training data collected in New York — underscores how, despite geopolitical tensions and calls for decoupling in the tech industry, the actual development and deployment of physical AI remains heavily integrated across borders.

— J.D. Capelouto

Steve Hilton has lived many lives. He’s been a key strategist to former British Prime Minister David Cameron, a populist Fox News host, and now — after renouncing his UK citizenship — he’s become the Republican nominee in California’s gubernatorial race. On this week’s episode of Mixed Signals, Max and Ben ask him about a career that has intertwined politics and media at every turn, why he succeeded in a primary where Spencer Pratt failed, and how he balances conservative media’s portrayal of California with his campaign to lead the state. Plus, they ask whether David Ellison’s Paramount would really flee Hollywood, what people get wrong about the Murdochs, and what he really thinks about the character he inspired on The Thick of It.

AI agents have made inroads in businesses and government. Now they’re hitting the pageant stage. Samantha Smitte, 37, who worked at IBM for a decade, spent about $150 on AI agents to train for the Miss New York USA pageant next week, she told Semafor. They run practice interviews with her, suggest workout routines, keep her up on current events, and suggest dresses like those of past winners. Her AI “poise and style” coach for her onstage posing practice didn’t give good advice, unfortunately, so Smitte went with a human for that.

Space for AI in the pageant world has been contested: As an April Fools’ joke this year, the Miss America organization posted that it would use AI with contestants on stage, asking them to solve real-world problems. A pageant of competing AI-generated women, dubbed “Miss AI,” received mixed reviews, with some saying it celebrated diversity and others saying humans are losing touch with reality. Smitte said she can be fully authentic while using AI and called it her “collaborator and thought partner,” but added, “I don’t think we’re ready to see the AI in front of the curtain yet.”

— Rachyl Jones