This is a super exciting release - Claude Fable 5 is the same underlying model as Mythos but with added safeguards. The benchmarks are great and it's SOTA on everything by a margin but I'll add that *qualitatively* also, this is a major-version-bump-deserving step change forward (imo of the same order as Claude 4.5 was in November), peaking especially for long problem-solving sessions on very difficult problems. You can give it a lot more ambitious tasks than what you're used to, the model "gets it" and it will just go, and it's never felt this tempting to stop looking at the code at all (but don't do this in prod!). The model still has quirks that people will run into and the safeguards are configured to be a little too trigger happy for launch, which can hopefully be tuned over time.
I feel a lot of things changing as working software increasingly comes out on a tap. The Jevon's paradox kicks in and I feel my own demand for software growing substantially. You can ask for anything - explainers, visualizers, dashboards, bespoke single-use apps (e.g. a full wandb that is hyper-specific just for your project), you can 10X your test suite, auto-optimize code, run giant research projects with custom HTML for the results, anything! "Free your mind" (Matrix ref). Really looking forward to all the things people build!
Fable 5 is now available in Claude Code and Cowork
Fable is the best model I have used for coding, by a wide margin. It is a big step up, enabling less prompts and steers, more efficient token use, better code quality, better tool use, more intelligent self-verification, longer running sessions, and higher trust & autonomy.
Happy coding!
.@WifeDirtyTesla and I successfully made it from one side of Michigan to the other with with 0 interventions. FSD dealt with heavy rain and even avoided an accident on the way (clip later).
Great job for this amazing achievement @Tesla_AI!
Jensen Huang, CEO of Nvidia:
"Every engineer is going to have and manage hundreds of agents."
The most valuable engineering skill of 2026 is not taught in any university.
No CS program teaches harness engineering.
No bootcamp teaches agent memory architecture.
No degree prepares you to build systems that survive production.
One builder mapped the entire thing out — free, step by step, no degree required.
This is the roadmap ↓
Bookmark this for the weekend.
World Labs CEO Dr. Fei-Fei Li: "The world is not made of words."
"Language models have given machines an extraordinary command of concepts, vocabulary, and reasoning, but the physical world, virtual or real, runs on a different substrate."
"Where language models learn the statistical structure of text, world models learn the statistical structure of space and time: how light falls on a surface, how a garden looks from an angle no camera has captured, how objects respond to force and follow the laws of physics."
"Language gave machines a way to talk about that world. World models are how machines will finally come to understand, imagine, reason and interact with it."
Full piece: https://t.co/C9qOJg5wuc
Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor.
It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx
NVIDIA just announced the first PC built specifically to run AI agents, and it's a big deal.
The new RTX Spark chip can run powerful AI models locally on your laptop, no cloud required, with enough memory to handle tasks most current machines would choke on.
Microsoft is rebuilding Windows around it. Adobe is rebuilding Photoshop and Premiere for it. Every major PC maker is building hardware for it.
The idea is simple: your next computer won't just do what you tell it, but work alongside you.
The huge braking in 14.3 is getting a little crazy. This seemingly for a shadow.
Since video doesn't show it well, for context...
Normal, comfortable braking: 0.1g - 0.2g
This Video: Aggressive, hard braking ~0.6g - loose items go flying
Emergency panic stop: 0.8g - 1g
@DevinOlsenn Would be helpful to track the longitudinal acceleration profile from the consol3 app and see if future releases will adjust to react to them
BREAKING: Anthropic just released a study showing which jobs its own AI is already replacing—right now.
And the workers most at risk aren’t who anyone expected: they’re older, more educated, and higher paid. They earn 47% more than average—and they’re nearly four times more likely to hold a graduate degree than workers AI isn’t touching.
The case is simple. Anthropic built a new metric called “observed exposure”—not what AI might do in theory, but what it’s actually doing today on the job—measured across millions of real Claude conversations from enterprise users.
For computer and math workers, AI could theoretically handle 94% of their tasks. Today, it’s doing 33%. In office and administrative roles, the ceiling is 90%, and current usage is 40%. The gap between what AI can do and what it’s actually doing is massive—and the researchers don’t mince words about what happens next: as capability improves and adoption spreads, the red area expands until it swallows the blue.
What makes the paper unsettling is the demographic twist. The most AI-exposed workers earn 47% more, on average, than the least exposed. They’re more likely to be women. More likely to be college educated. This isn’t a story about warehouse floors or long-haul routes. It’s about lawyers, financial analysts, market researchers, and software developers—the very people who were told their education would protect them.
Computer programmers show the highest measured AI exposure: 74.5%. Customer service reps: 70.1%. Data entry: 67.1%. Medical records: 66.7%. Marketing and market research: 64.8%. These aren’t forecasts. They’re measurements of work already being done on AI platforms today.
Then there’s the pipeline problem—still not getting nearly enough attention.
Anthropic researchers found a 14% drop in the job‑finding rate for 22–25‑year‑olds in highly exposed occupations since ChatGPT launched. No comparable effect for workers over 25. Entry-level roles were never “just jobs.” They were the apprenticeship layer: where junior analysts became senior analysts, where junior lawyers learned how arguments actually
PDF: https://t.co/tnk5Ri7CoP
🇯🇵A Japanese developer built an app that puts a fat cat on your screen and forces you to take a break
Silicon Valley spent billions on wellness platforms, mindfulness subscriptions, and digital detox retreats
A guy in Japan said: fat cat, problem solved