Pre-release testing of frontier AI models has so far rested on a loose set of voluntary arrangements. Labs share early versions with government testers, the testers probe them for risk, and the results inform both the companies and the public officials watching them. That model assumed allies would cooperate. A new request from Washington suggests the order of access now matters as much as access itself.
According to a report by Politico, the White House has asked OpenAI and Anthropic to hold back new models from the UK's AI Security Institute (AISI) until the US government has completed its own review. The request came from the Office of the National Cyber Director.
Most text-to-speech systems have been judged on one thing: whether the voice sounds human. That matters, but it is less useful to a studio producing an audiobook or a game character, where the voice also has to laugh on cue and slow down when the scene calls for it.
Alibaba's new Qwen-Audio-3.1-TTS is built with that second group in mind. The model turns written text into speech across several languages and Chinese dialects, and it lets users shape the delivery with plain-language instructions. Tone, tempo and speaking style do not require technical parameters. A short description is enough.
Most debates about AI and jobs focus on the workplace: which roles will shrink, which will change and which will survive. At the Communication University of China (CUC) in Beijing, that debate has already reached the course catalogue.
In 2025, the university cut or merged a total of 16 bachelor's programmes. Photography and translation no longer exist as standalone degrees. Comics, fashion design and visual communication design were also among the affected programmes. According to Liao Xiangzhong, the university's Party secretary, the reason is the progress of artificial intelligence.
"A waste of resources"
Liao's argument is blunt. In his view, AI has already largely taken over translation, so a four-year degree devoted only to that skill wastes resources. He applied similar reasoning to photography, saying the classic form of the discipline can no longer stand on its own as a separate subject.
Most workplace messaging tools were designed for people typing to other people. AI agents came later and were added as apps. Ando, a startup that came out of stealth on Thursday, wants to reverse that order. It is building a team messaging platform designed for human and AI workers from the start.
The company also said it has raised $20 million in pre-seed and seed funding. Accel, Index Ventures and Emergence are among the investors.
From MCP servers to a messaging platform
The idea came from founder Sara Du's work in 2025, when she was helping companies build MCP servers. Customers kept asking how they could use AI agents inside Slack. The obstacles were technical. Messages had to pass back and forth, agents needed the right context, and all of it had to happen without exhausting token budgets.
Predicting how fast artificial intelligence will improve usually falls to a familiar group: professors at leading universities, heavily cited AI researchers and seasoned economists. They are the people policymakers and businesses turn to when they want a sense of what comes next.
According to a detailed interim report from the Forecasting Research Institute (FRI), that group has often been too cautious. On benchmarks and on some adoption indicators, progress over the past few years has run well ahead of what experts expected.
Who was asked: a panel built from the top of the field
The FRI has been gathering forecasts on AI progress since mid-2022 through several studies and projects. The first round of its Longitudinal Expert AI Panel, or LEAP, included 339 experts: 76 computer scientists, 76 industry specialists, 68 economists and 119 AI policy professionals. Among the computer scientists were 30 professors at top-20 institutions and 10 of the 200 most-cited AI authors.
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