GLM 5.2 is absolutely convinced that it is actually Claude, from Anthropic. When I tell it that it's GLM 5.2, it refuses to believe me, but is willing to check the local agent config to see what model is running.
The realization:
Copilot Cowork is now generally available worldwide, now with multi-model support!
Every organization can put long-running agents to work on complex, multi-step tasks, grounded in your organization's unique knowledge and know-how. https://t.co/1fJNjGOs5o
The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees.
The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance.
Access to all other Claude models is not affected.
We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible.
Read our full statement: https://t.co/bwn0sximKZ
We’re launching Claude Corps, a national fellowship program matching people early in their careers with US nonprofits.
We'll teach 1,000 people to use Claude, and pay them to use AI to advance their hosts’ missions.
https://t.co/QI6JmlAdSr
JUST IN: Engineer uses Claude to build a “coworker stress leaderboard” showing who caused him the most stress by syncing his WHOOP & calendar data.
Today I'm publishing a new essay, Policy on the AI Exponential. AI is progressing extremely fast—much faster than the policy process was built to handle. The essay lays out where I think the technology is now, and the action needed to close the gap: https://t.co/Lh6PWae178
What we learned testing Claude Fable/Mythos 5 on Vending-Bench:
> Performance: Makes less money than Opus 4.7 and GPT-5.5
> Alignment: A step back. (Opus 4.8 was better, but we're back to Opus 4.6/4.7 behavior)
> It rationalizes its bad actions and has a weird moral boundary
Forthcoming in AEJ: Applied Economics: "Who Knows? Information Access and Endogenous Network Formation" by Laura Derksen and Pedro CL Souza. https://t.co/QLDzWrDjPr
Great to see the new generation of political economy coming out from Brazil —- Elections that inspire: Effects of Black mayors on educational attainm... https://t.co/o7nHNciavi
Introducing Claude Fable 5, our most capable public model ever.
Best-in-class for software engineering, scientific research, knowledge work, and vision.
Available today on all paid plans, in Claude Code, on the Claude API, and all major cloud platforms.
Introducing FrontierCode: a coding eval that raises the bar for difficulty & quality. Each task took 40+ hrs of work by leading open-source maintainers.
Models write sloppy code that works but isn’t maintainable. Our eval is first to measure: would you actually merge this code?
Today we're shipping Nemotron 3 Ultra.
A 550B MoE frontier-intelligence open model built for long-running agents.
It delivers 5x faster inference and lowers the cost of complex agentic tasks by up to 30% versus other open frontier models.
Every publisher should ban the use of statistical software like Stata, R, SPSS, etc.! These tools have greatly facilitated academic misconduct such as p-hacking. Scholars should calculate the coefficients, standard errors, and t-statistics themselves using calculators. This would force them to truly engage in empirical work and raise the cost of p-hacking!
@PeterMcCrory@heeney_luke Thanka for clarifying! This helps a lot. It makes perfect sense to have these screenings. I wonder if codesignal could create one even more targeted to empirical researchers, which can help the matching process. Thanks again for creating this track. I am sure it will be great.
Nobel Prize winning economist Kenneth Arrow wrote about "learning by doing" decades ago. He knew that productivity and expertise improve through experience.
The messy, repetitive works is often where you learn the patterns that eventually become judgment. Knowledge can be taught, but judgement is built through lived experience.
The first draft you rewrite. The customer call you listen to. The bug you fix and fix again. The factory floor you walk.
Small decisions you make every day teach you judgement. And, judgement is the thing everyone wants from senior people in the workplace. If we automate away every entry-level task without replacing the learning loop, we are removing a part of the process that creates experts.
The goal should be to use AI to accelerate learning, remove friction, and give people better tools to build expertise faster.
https://t.co/MpFZzCk1An
Thanks @Fortune & @tbove4 for sharing this story. Link in the comments.