🤖 Anthropic restores Fable 5 and Mythos 5 models

The US Commerce Department lifted export restrictions on Anthropic's Fable 5 and Mythos 5, allowing access to resume this Wednesday. The rollout starts on Claude platforms and will expand to AWS, Google Cloud, and Microsoft Foundry.

Anthropic had to disable these models after Amazon researchers flagged a hacking risk. To fix this, they trained a new protective classifier that blocks the exploit over 99% of the time, redirecting blocked requests to Opus 4.8.

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Agentic AI spurred a boom in mobile app releases, but there is no sign of these apps gaining traction, per FT.

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🤯 Tiny robots that look like plastic confetti could one day become reality.

Researchers are developing microscopic robots that begin as flat, thin sheets. When exposed to heat, they fold themselves into tiny moving structures capable of carrying small payloads. Some designs can even dissolve in water after completing their task, leaving behind little or no trace.

It sounds like something straight out of Black Mirror, but the technology is being explored for practical uses such as targeted drug delivery, environmental monitoring, and minimally invasive medicine.

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🇺🇸 President Trump says AI could be “much bigger than the internet” arguing that whoever leads the race will define the next era.

He added that the U.S. is currently “substantially No. 1” in AI.

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🇺🇸 America is building the AI revolution. Everyone else is using it.

The country behind most of the world’s leading AI models ranks just 24th in AI adoption. Only 28% of working-age Americans use AI regularly, trailing countries like the UAE (64%), Singapore (61%), and even Norway, Ireland, and France.

The irony is hard to miss. The US poured $286 billion into private AI last year, launched nearly 2,000 AI startups, and is home to OpenAI, Anthropic, Google, and xAI. Yet much of the population still hasn’t made AI part of daily life.

Meanwhile, countries that rarely dominate AI headlines are racing ahead in adoption. The UAE integrated AI into government services years ago, while Singapore turned AI literacy into a national priority.

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🧠 Elon Musk says every genius in history had one thing in common: they all ran on the same brain.

For roughly 50,000 years, human intelligence barely changed. The same biological hardware powered everyone from prehistoric hunters to Einstein.

Then AI arrived.

Musk recalled how experts once believed beating the world’s best Go players was decades away. Instead, AlphaGo went from defeating one champion to reaching a level where it could take on dozens of elite players at once without breaking a sweat.

The point isn’t Go. It’s the pace.

AI doesn’t get tired. It doesn’t forget. It improves at a speed biology can’t match.

For thousands of years, every breakthrough depended on the limits of the human mind. Today, those limits matter less than ever because intelligence is becoming something we can build, scale, and improve.

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Ⓜ️ Meta’s upcoming AI model, internally codenamed Watermelon, has reportedly caught up with OpenAI’s GPT-5.5 on closely watched benchmarks.

Meta AI chief Alexandr Wang told employees that Watermelon is still training and uses roughly 10 times more compute than Muse Spark, the company’s current model family.

The exact benchmarks were not disclosed, so the claim cannot yet be independently verified.

Meta is also preparing an update to Muse Spark with stronger coding and agent abilities, while Wang says a model competitive with Claude Opus could arrive “pretty soon.”

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📃 Vibe-coders work on a $1 billion AI startup at 2 AM.

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🧑‍💻 GitHub Sells Repos on CD-ROM

GitHub now offers copies of repositories on CD-ROM.

Users can order physical copies to preserve code offline or for future use.

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📕 AI Godfather Geoffrey Hinton on why AI already outlearns the human brain despite us having 100x more neural connections.

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🚗Your car’s engine might soon tell you what’s wrong, just by listening.

A new open-source AI called CarDiag can detect potential car problems from the sound of your engine. Simply record your engine with your phone, upload the audio, and the model analyzes the recording to identify which vehicle system is most likely causing the issue.

It’s still early days. Right now, the AI correctly distinguishes between healthy and faulty engines about 79% of the time. But here’s the impressive part: the entire trained model is only around 100 KB, making it incredibly lightweight and easy to run.

Because the project is fully open source, the creator hopes developers and car enthusiasts will help train it into a much more accurate mechanic that fits in your pocket.

Source.

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📊 By 2027, just 5 companies, Alphabet, Amazon, Meta, Microsoft, and Oracle, are expected to spend around 3.2% of US GDP on AI capital expenditure.

That would put private AI infrastructure spending above US national defense spending, which is expected to be around 2.7% of GDP.

The AI race is now being funded at a scale normally associated with governments, wars, energy systems, railroads, highways, and telecom buildouts. The striking part is the speed. AI capex is expected to jump from about 1.5% of GDP in 2025 to about 2.5% in 2026, then to 3.2% in 2027.

AI boom is now large enough to influence the broader US economy significantly, it can move GDP growth, electricity demand, chip supply, construction activity, corporate debt markets, and ofcourse the labor market.

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🔥Hyundai Motor showcases its Atlas humanoid robot at the 2026 World Cup, with plans to manufacture 30,000 units annually in the US starting 2028.

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