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AI China Youth

The Arithmetic of Youth

The first meeting was at one of the banks on a high floor somewhere in Shanghai, the kind of view that turns a city into an abstraction. It was 2005, and I was there the way American investors were there that year โ€” curious, a little jet-lagged, trying to read a country that was rewriting itself faster than anyone could print the new edition. Across the table sat a management team, and what struck me wasn’t anything they said. It was how young they were. Not junior-young. Running-the-company young.

Afterward โ€” in the hallway or the car, early in the trip, when I still had the confidence of someone who thought he could just ask โ€” I put the question to one of our local colleagues. Casually, expecting a casual answer. Something about a young country, a young economy, energy meeting opportunity.

The answer I got instead was the Cultural Revolution.

There was a generation, she explained, that simply wasn’t there. Sent to the countryside, pulled out of universities, handed shovels instead of textbooks. By the time China opened back up, that cohort had a hole in it โ€” a rung missing from the ladder. So the young people I’d just watched run that meeting weren’t there because anyone had bet on youth. They were there because there was no one older left to put in the chair. Youth, in that boardroom, wasn’t a strategy. It was a vacancy dressed up as one.

I have thought about that answer, off and on, for twenty years, without knowing what to do with it. Then a few weeks ago I read a summary of a conversation with Nathan Lambert โ€” an AI researcher who’d just spent time visiting the frontier labs in Beijing and Hangzhou โ€” and I found myself back in that room, except everything about the youth in it had flipped.

He describes teams at places like Moonshot AI as almost absurdly young, tight-knit, close to giddy about the work โ€” “the best vibes,” he calls it. Zhipu AI, he says, has built something close to an AGI showroom, a physical space engineered to perform confidence for whoever walks through the door. These aren’t companies with a hole where the experienced people should be. These are companies that went looking for twenty-five-year-olds because twenty-five-year-olds move at the speed frontier AI research demands, and installed them at the center of the room. The showroom isn’t hiding a vacancy. It’s staging a choice. That’s panel two.

Same demographic. Same first city โ€” Beijing both times โ€” with a high-speed rail line now running to Hangzhou instead of whatever second city I’d have named twenty years ago. Opposite cause. In 2005, youth in the room meant a generation had been taken from the labor force involuntarily. In 2026, youth in the room means a generation has been selected for it, deliberately, competitively, because being young is now the qualification rather than the disqualifier. The Cultural Revolution left a gap that youth filled by default. The AI boom left a door that youth is filling by design.

I would have stopped there, satisfied with the irony, except for a number I couldn’t get out of my head once I went looking for it: 15.6 percent. That’s China’s urban youth unemployment rate โ€” ages sixteen to twenty-four, university students excluded โ€” as of May 2026, and it counts as good news, down from 16.3 percent in April. A year earlier it had spiked to nearly nineteen percent in a single August, the month twelve million university graduates walked out of commencement and into a labor market that had no idea what to do with them. Some will sit for civil service exams, chasing what people there still call the iron rice bowl โ€” the illusion of permanence a state job used to guarantee, back when your grandparents didn’t choose their careers so much as get assigned them. Others will enroll in another degree, not because they want one, but because a classroom is a more dignified place to wait than an unemployment line.

So there is a third panel now, and it doesn’t fit neatly next to the other two. It isn’t a vacancy, and it isn’t a showroom. It’s just a very large number of young Chinese people who did everything they were told to do โ€” studied hard, got the degree โ€” and are standing outside a door that isn’t opening. And somewhere behind that door, in a much smaller room with much better lighting, another group of young Chinese people, maybe the same graduating class, are building the technology that a Silicon Valley researcher travels overseas to admire for its vibes.

I don’t think those two rooms are as separate as they look. I think the showroom is real, and I think the twelve million are real, and I think the mistake โ€” my mistake, sitting here in Menlo Park two decades removed from that conference table โ€” is letting either one stand in for “Chinese youth” as if it were a single sentence instead of a population. The Moonshot AI team is not a representative sample. It’s the visible sliver of a generation, selected with a precision that turns the unemployment numbers into part of the same mechanism โ€” one sorting process, not two unrelated stories. The best vibes in that lab and the worst numbers in that economy might just be describing the two ends of the same funnel.

I keep coming back to that hallway in 2005, and to how confident I was in the question I asked โ€” as if a generation’s youth could only ever be telling one story. It couldn’t then, and it can’t now. I got a true answer that day and thought I understood something. I understood one panel of a triptych I hadn’t seen the rest of yet โ€” and I’m still not sure I’ve seen all of it.

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AI AI: Large Language Models China

Cranes on the Horizon

In 2005, during my first trip to Shanghai and Beijing, the most striking feature of the skyline wasn’t the architectureโ€”it was the cranes. More than I could possibly count, perched atop half-finished skyscrapers like a mechanical forest. Entire districts seemed to be mid-construction simultaneously, as if someone had pressed a button and the whole country decided to build everything at once. Dan Wang in his book “Breakneck” described China as the “engineering state” that approaches national problems with physical solutions. Back in 2005, coming from Silicon Valley, I thought I understood what growth looked like. I didn’t.

I’ve been thinking about that trip while reading Nathan Lambert’s recent piece, “Notes from Inside China’s AI Labs.” Lambert โ€” who runs the Interconnects newsletter and does serious work tracking the open-weight LLM ecosystem โ€” just returned from visiting essentially every major AI lab in China. Moonshot, Zhipu, Meituan, Xiaomi, Qwen, Ant Ling, 01.ai. He went in with genuine curiosity and came back with humility. That combination is rarer than it should be.

What he found was the cranes. Different domain, same energy.

Lambert’s central observation is about culture, not capability. The Chinese labs aren’t winning on any single technical breakthrough โ€” they’re winning on execution discipline. He describes researchers, many of them active students, who bring no ego to the work. They absorb context fast, drop assumptions faster, and seem genuinely unbothered by the philosophical debates that seem to swirl constantly in the American AI community. When he tried to engage Chinese researchers on the long-term social risks of models or the ethics of AI behavior, those questions “hung in the air with a simple confusion. It’s a category error to them.” Their role is to build the best model. Full stop. To them, an LLM isn’t a philosophical entity to be interrogated; it’s a piece of infrastructure to be optimized.

That description landed for me. Not as a criticism of American research culture, but as a real observation about what the moment demands. Building good LLMs today is, as Lambert puts it, meticulous work across the entire stack โ€” “all points of the model can give some improvements, and fitting them in together is a complex process.”

The work that matters most right now isn’t the 0-to-1 creative leap; it’s the thousand unglamorous decisions executed without complaint. Students who haven’t yet learned to lobby for their own ideas turn out to be well-suited for exactly this.

Lambert ends on a note that’s hard to shake. Looking up from his laptop on a high-speed train, he keeps seeing cranes on the horizon. He draws the same connection I did, though from the inside: the construction everywhere fits the broader culture and energy around building. “When I look up from my laptop and always see bunches of cranes on the horizon, it obviously fits in with the broader culture and energy around building in China.”

Twenty years after my first visit, the cranes are still there. They’ve just moved indoors โ€” into server rooms and training runs and model releases that land every few months with quiet confidence. In 2005, what China was building was obvious: you could see the steel frames going up. What’s being built now is harder to see, which may be exactly why it keeps surprising us.

Check out Lambert’s essay – it’s remarkable. If the 20th century was defined by who could move the most earth, the 21st will be defined by who can move the most tokens. And right now, the cranes are moving faster than we think.

Categories
AI China

Whatโ€™s new in AI from China?

February 2026 is a busy time in AI coming out of China coinciding with the Chinese New Year.

I asked Grok this morning for an update and double checked it with Gemini.

Hereโ€™s what Grok reported:

Chinese AI is in a very active phase right now (mid-February 2026), with a massive wave of new model releases, upgrades, and applications timed around the Lunar New Year (Spring Festival) holiday. This echoes the “DeepSeek shock” from exactly one year ago, when DeepSeek’s low-cost, high-performance models disrupted global expectations.

Major Recent Releases and Upgrades (mostly this month)

Chinese companies are shipping frontier-level models at a furious pace, often open-source or very low-cost, focusing on efficiency, reasoning, coding, multimodality, agents, and real-world applications.

  • Alibaba โ†’ Just launched Qwen 3.5 (with agentic features, multimodal inputs like text + photo + video, up to 2-hour video analysis). They also released RynnBrain (specialized for physical AI/robotics, helping robots understand and interact with the real world).
  • ByteDance (TikTok parent) โ†’ Released Doubao 2.0 (claims to match GPT-5.2 / Gemini 3 Pro level reasoning and multi-step tasks). Their video gen model Seedance 2.0 went viral for high-quality deepfakes and creative uses, sparking huge youth/creator interest.
  • Zhipu AI โ†’ Dropped GLM-5 (open weights, strong in coding, long tasks, agent capabilities; one of the highest open-weight intelligence scores).
  • MiniMax โ†’ M2.5 and M2.5 Lightning (near state-of-the-art at ~1/20th the cost of top Western models like Claude Opus; very strong on coding/agent benchmarks).
  • Kuaishou โ†’ Kling 3.0 (advanced AI video generation).
  • Moonshot AI โ†’ Kimi K2.5 (very close to top proprietary models at 1/7th the price; excellent reasoning).
  • DeepSeek โ†’ Widely expected to drop V4 soon (focused on coding, potentially 1M+ context, efficient MoE architecture). They’ve been the pace-setter since early 2025.

Many of these are open-weight or open-source, leading to Alibaba’s Qwen family overtaking Meta’s Llama in cumulative Hugging Face downloads.

Broader Themes Right Now

  • Low-cost + open ecosystems โ†’ China is winning on price/performance and rapid iteration. Models often cost 5โ€“20ร— less than Western equivalents while matching or nearing performance in many areas.
  • Two different races โ†’ Analysts say the US focuses on perfecting frontier models (bigger, more compute-heavy), while China emphasizes adoption โ€” deploying cheap, efficient AI at massive scale in manufacturing, robotics, consumer apps, and the real economy.
  • Physical & embodied AI โ†’ Huge push here. Robotics demos (backflips, kung fu with nunchucks synced across many bots on live TV) show fast progress in “physical intelligence.” Alibaba’s RynnBrain targets robotics directly.
  • Other notable advances โ†’ In-orbit AI computing constellation (“Three-Body”) successfully tested (running LLMs on satellites for low-latency edge processing). Military applications (e.g., bio-inspired drone swarms using hawk/wolf behaviors) are advancing rapidly.
  • Challenges & realism โ†’ Some top Chinese AI leaders (e.g., Alibaba’s Qwen lead) estimate <20% chance of fully overtaking US frontier models in 3โ€“5 years due to compute gaps and chip sanctions. But open collaboration and talent pipelines are closing the gap fast in many practical areas.

Overall, February 2026 feels like China’s AI industry hitting a coordinated sprint โ€” not just catching up, but pulling ahead in accessible, deployable, cost-effective AI that reaches everyday users, creators, and industries quickly. The US still leads in raw frontier capability and monetization scale, but the gap is shrinking noticeably in deployment and iteration speed.


Geminiโ€™s review included the following:

The reportโ€™s observation about the “Two Different Races” is the most insightful part:

โ€ข US Strategy: Scaling laws for maximum “Frontier Intelligence.”

โ€ข China Strategy: Scaling for “Deployment Efficiency.” By making models like MiniMax M2.5 and Kimi K2.5 available at a fraction of the cost ($0.15โ€“$0.60 per 1M tokens), China is prioritizing the “AI Agent” economy, where reliability and low cost per task matter more than raw benchmark scores.

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Business China

Innovations from the Automotive Sector

I’ve been listening to the latest podcast from Dwarfish Patel in which he’s interviewing Arthur Kroeber (“China’s Manufacturing Dominance: State Directives & Ruthless Competition“).

One of the topics discussed is how “China recognized that pretty much every other country that had gotten rich had done so in large part by building up anย automotive industryย that then served as the mechanism for creating innovations in other sectors. … They said, โ€œWe have to have a big auto industry. This is one of the key industries that we have to support.โ€”

Kroeber goes on to describe how China opened up to enabling 50/50 joint ventures between Chinese auto companies and foreign auto manufacturers.

While that worked initially, eventually it became clear that to really enable globally competitive auto manufacturing in China there had to be another solution.

That solution was allowing Tesla to come into China in 2018 and build a Gigafactory in Shanghai. In so doing, China allowed a globally competitive auto manfacturer (Tesla) to effectively compete with local Chinese companies and, in so doing, create the need for those local Chinese companies to compete much more effectively with a global player like Tesla.

It’s a fascinating story. One of the other discussions in the early part of the interview involves how the U.S. might consider doing that in reverse – allowing Chinese companies to come into the U.S. market and through competition educate American companies so that they improve their globally competitive position. Politically impossible in the current climate – but an obvious idea based upon the Chinese experience.

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Black and White China Monochrome Photography Nik Software Nikon Photography Photography - Black & White Photography - Nikon D600 San Francisco/California

Armored Kneeling Archer – China’s Terracotta Warriors

Armored Kneeling Archer - San Francisco - 2013

Here’s another image from the exhibition of China’s Terracotta Warriors now underway at San Francisco’s Asian Art Museum.

This image required a bit more work. One of the challenges of shooting images of the warriors as they’re displayed is the combination of lighting and reflections – which bring extra “stuff” into the images.

Plus, when we were there, it was really crowded inside the darkened exhibition gallery. Lots of folks moving around – and bumping into each other – a challenging photographic venue for sure!

But the gallery that the Asian Art Museum created for the warriors is really is superb in terms of how the terracotta warriors are placed and, in particular, how they’re lit.

So, to deal with the issues in the image, I did a quick selection in Photoshop to isolate the warrior from extraneous background elements. I then faded those elements into the background while adding some contrast to the warrior.

Then we made a trip into Nik’s Color Efex Pro 4 to do two steps: bring out more detail and add a subtle bit of glamour glow.

Nik’s Silver Efex Pro 2 was used for the conversion to monochrome – adding a bit of structure to the midtones and highlights while removing structure from the shadows. A bit of soft contrast adjustment helped with lighting.

A quick pass with Doug Kaye’s Warm Black action helped tone the image just ever so slightly.

For the final sharpening step, I used the Sharpen 2013 action included in the latest version of Dan Margulis’ Picture Postcard Workflow panel in Photoshop.

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Black and White China Monochrome Photography Nik Software Nikon Photography Photography - Black & White Photography - Nikon D600 San Francisco/California

China’s Terracotta Warriors

Driver - San Francisco - 2013

San Francisco’s Asian Art Museum is currently featuring a beautiful exhibition of China’s Terracotta Warriors.

Here’s an image from a recent visit – of a horse carriage driver. He’s out in the lobby – before you get into one of the three galleries with the other warriors and related sculptures.

This image was shot handheld with my Nikon D600 and post-processed in Photoshop CS6 along with Nik’s Silver Efex Pro 2.

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China

To China

Tim Bajarin writes about his recent visit to China – after a nine year absence.

The pace of change in China is so stunning, that nothing would surprise me about China anymore.

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Business China

Immelt on China

Business Week has a great story about the Immelt revolution underway inside GE. In a sidebar Q&A interview, CEO Jeff Immelt discusses China:

China is really about infrastructure. There will be tremendous investments made in infrastructure, health care, energy, water, water, security. GE can approach China as one company and form a company-to-country relationship that’s bigger than any of the pieces.

We’re getting more comfortable with the rule of law. We’ve been careful so far. Our investments only trail our ability to understand what the rules are going to be. When I go there today, there’s a tremendous focus on the financial system. They’ve got external consultants working on it. China is not a slam dunk. But it’s right in GE’s sweet spot, so we’ve got to play and play big.

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China

The Dragon Awakes

Dean Calbreath writes in the San Diego Union-Tribune about China, the fastest growing economy in the world.

Some economists predict that by 2015, China will have enough spending power to become the world’s primary engine of economic growth, unseating the United States, which has held that role since the end of World War II. By 2040 – and perhaps much sooner – China may have a greater gross domestic product than the United States, giving it the world’s No. 1 economy. It now ranks at No. 3.

The newspaper will also be running articles on China tomorrow and Tuesday.

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China Film Travel

China

My photo album from my recent trip to Shanghai and Beijing is now available.