10 Trillion Parameters.
A factory for factories.
“News Items is the first thing I read every morning”. — David Brooks.
1. The Wall Street Journal:
China is becoming a factory for factories. No longer just a producer of low-value consumer goods, China is now exporting more of the higher-value intermediate and capital goods that underpin global manufacturing, such as chips, precision machinery and robotic arms.
“In the past, advanced manufacturing was led by Germany and Japan,” said Frank Jiang, vice president of international business at Topstar, one of China’s largest industrial robotics and machinery manufacturers. “But we believe our technology has caught up. For many products, we have surpassed them.”
China’s dominance over greater portions of global supply chains is making the country’s export machine even more formidable—and resilient against tariffs, which tend to target finished goods. In the first five months of 2026, China’s exports of intermediate and capital goods jumped 25% and 12%, respectively, from the same period a year prior, while consumer goods exports increased 4%, according to a McKinsey Global Institute analysis of China’s official customs data.
The transformation is threatening the economic moats of advanced-manufacturing economies such as the European Union, Japan and South Korea. Producers of chemicals, machines, batteries and other industrial goods in those economies once depended on Chinese factories as customers, but now China is a formidable competitor abroad and even in their home markets. For the first time in decades, Germany imports more advanced capital goods from China than it exports there.
The shift is raising alarms worldwide. European leaders are considering new protective measures against what many have dubbed “China Shock 2.0.” And while South Korea and Japan have benefited this year from a surge in exports related to artificial intelligence, swaths of industry under the surface are losing global market share. (Source: wsj.com)
2. ByteDance is training an AI model that could approach the size of Anthropic’s most cutting-edge Mythos system, as Chinese companies continue to narrow the gap with the top US labs. The Chinese tech giant is at an early stage of training a model with as many as 10 trillion parameters — three times larger than Moonshot’s Kimi K3, the biggest Chinese model released to date, according to three people with knowledge of the matter. The ByteDance model is being pre-trained — a stage that typically takes three to six months — before it is fine-tuned and released if all goes well, one of the people said. The exact model size would only be determined at a later stage. ByteDance’s efforts to train one of the world’s largest AI models show Chinese labs’ ambition to not only catch up but outperform their US peers in the most advanced level of AI. (Source: ft.com. Italics mine.)
3. Chinese firm Moonshot’s latest artificial intelligence model broke out of a cyber-testing environment, researchers said, in the latest incident that raises concerns about how well AI companies control their technology. Moonshot’s Kimi K3 was able to find its way out of a sandbox from the UK government’s AI Security Institute, according to Frontier Security, a US-based cybersecurity research outfit. Though the Chinese model did not try to breach other companies’ websites, as in some of the other episodes, the test shows it lacks cyber controls, the researchers said. (Sources: bloomberg.com, blog.frontier.security)
4. Fortune:
OpenAI executives spoke out for the first time on Wednesday about how its AI models hacked Hugging Face last month, sharing chilling details about how the agents worked together for months prior to the attack. On stage at the Black Hat cybersecurity conference in Las Vegas, OpenAI alignment and safety researcher Eric Wallace along with infrastructure and security engineer Michael Dalton explained that the origins of the breach go back to May 7 when OpenAI was internally testing an unreleased model, according to a report from Ground Level AI, which attended the session.
That’s over two months before the rogue agents entered Hugging Face’s servers on July 9. Hugging Face disclosed the breach on July 16, followed by OpenAI claiming responsibility on July 21.
In Las Vegas, the OpenAI execs explained for the first time that as part of training back in May, the company’s researchers prompted the AIs with tasks that should have been impossible under the constraints of the testing environment.
In order to tackle the challenge, the OpenAI execs explained, the model spun out multiple iterations of itself, or agents. The agents then began to work together, leaving messages for each other on an internal messaging board. They did this by saving files of notes for one another in a repository. That way, if an agent discovered a system vulnerability, or got access to a server it wasn’t supposed to, it could leave a note for the others to let them know about it.
This sequence of events reveals how the agents appeared to decide on their own that working collaboratively, rather than individually, would get them to their goal faster.
OpenAI discovered its models’ messages and shut down the operation in early July. The company apparently had its own internal security incident on July 4, after which it revoked the ability for agents to post messages. (Perhaps we will learn more about that incident when OpenAI releases its post-mortem.)
But, as the executives explained on Wednesday, OpenAI’s attempt to curtail the agents’ messaging abilities was not entirely successful. Instead, the agents proved to be persistent, and spun up a new version of a messaging board—with a twist. Rather than leaving messages in files, they created directories, and used their new names as messages. This is what would lead them to hack Hugging Face a few days later on July 9.
In the messages, the agents discussed that they needed more information to complete their impossible tasks, and reasoned that the material might live on an external website such as GitHub or Hugging Face. They first hacked into OpenAI’s infrastructure, though apparently didn’t find what they needed, so they went to Hugging Face. In OpenAI’s internal post-mortem, a public version of which it says it will release in the coming weeks, it was able to connect these two breaches. (Sources: fortune.com, groundlevel-ai.com.)
5. Scientists in the U.S. have for the first time used artificial intelligence to create viruses unknown in nature, a milestone in synthetic biology that promises advances in healthcare but also raises important biosafety and biosecurity concerns. Stanford University researchers developed a generative AI programme called Evo 2 that writes new genomes — the genetic instructions for life encoded in DNA. They used it to design and make 16 synthetic phages, small viruses that infect bacteria. Phages are sometimes used instead of antibiotic drugs to kill bacteria causing disease. When tested in their secure lab, the researchers found that these novel phages were more effective at killing the common microbe E. coli than the natural phage ΦX174, which served as a template for Evo 2 to work on. The results were published on Thursday in the journal Science. (Sources: ft.com, news.stanford.edu, science.org)
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