🎨 One of the funniest AI social experiments just happened on x.

A user named SHL0MS posted a painting and wrote: “I generated a Monet-style image with AI. Please explain in detail why it’s worse than the real Monet.”

Except… the image was an actual Claude Monet painting.

And people instantly took the bait.

Art critics, AI skeptics, and self-proclaimed experts flooded the replies explaining why the “AI art” lacked soul, depth, emotion, composition, and understanding of light.

Some of the responses were incredible:

• “It looks like a first-year art student made this.”
• “The reflections in the water make no sense.”
• “There’s no depth or composition.”
• “A soulless forgery.”
• “Obviously not made by a human.”

They were confidently criticizing one of the most celebrated painters in history.

The experiment perfectly exposed how much expectation shapes perception. Tell people something is AI-generated, and many will start seeing flaws that don’t exist.

Turns out humans hallucinate pretty hard too.

@aipost 🏴

🇺🇸 Elon Musk made one of the strongest defenses of America you’ll hear anywhere.

After WWII, the US had total dominance: Nukes, unmatched industry, and no real rival.

Every empire in history used that kind of advantage to conquer. America rebuilt its enemies instead. Germany became Europe’s economic engine. Japan became an economic superpower. The US even flew food into Berlin just years after the war. Musk’s point is bigger than history. AI is about to create another massive power imbalance.

And the real question is: When someone has unstoppable power, what do they choose to do with it?

America’s most important act wasn’t building the bomb, it was choosing restraint after.

@aipost 🏴

🇨🇳 Robots in China are already chasing down traffic violators and forcing them to pull over at the roadside.

@aipost 🏴

The next pandemic might not trigger lockdowns first. It could trigger the largest AI + biotech acceleration in human history. — Bryan Johnson

@aipost 🏴

🤖 Claude Opus 4.7 just replaced every video editor!!

Claude can now:

• Analyze long-form videos
• Find clip-worthy moments
• Add hooking captions
• Schedule and post for you

This is actually insane!

@aipost 🏴

On May 19, SpaceX plans to launch a new Starship V3 test flight — the super-heavy rocket designed to become the foundation for future missions to the Moon, Mars, and beyond.

But this time, the context is even more interesting.

After the SpaceX and xAI merger, this is no longer just a rocket launch. It is part of Elon Musk’s larger system, where rockets, satellites, data, compute, and artificial intelligence are increasingly converging into one infrastructure layer.

AI used to live in the cloud. Now it is getting closer to hardware, orbit, and space logistics.

Starship is not just about space.
It is about who builds the infrastructure for the next technological era.


@aipost 🏴

This metaphor in Musk v. Altman closing statements is hilarious..

@aipost 🏴

🤖 OpenAI introduces personal finance

A preview for Pro users: a new personal finance experience in ChatGPT.

Pro users in the U.S. can securely connect financial accounts, see where their money is going, and ask questions based on the information they choose to connect.

Fintech startup mass murder

Source.

@aipost 🏴

🔥Google Gemini can now completely rewire your brain so you can learn anything at lightning speed.

Here are 7 Gemini prompts to learn anything 10x faster:

1. Feynman Learning Method

"Teach me [insert topic] in simple language as if explaining to a beginner. Then ask me to explain it back in my own words and point out gaps in my understanding."

2. First Principles Breakdown

"Act as an expert instructor. Break down [insert topic] into its most fundamental building blocks using first principles thinking so I understand the core logic instead of memorizing surface-level facts."

3. Active Recall Coach

"After teaching [insert topic], quiz me with challenging questions that force me to recall information without looking at notes, then evaluate my answers with detailed corrections."

4. Spaced Repetition Schedule

"Create a spaced repetition revision schedule for learning [insert topic], including what to review daily, weekly, and monthly so information moves from short-term memory into long-term retention."

5. Smart Knowledge Summary

"Summarize [insert topic] into clear frameworks, mental models, and simplified structures so the most important information becomes easier to remember and apply."

6. Learning Acceleration Plan

"Create a learning roadmap for mastering [insert skill] that includes stages, milestones, and checkpoints so I always know what to learn next without wasting time."

7. Weakness Assessment

"Ask me diagnostic questions about [insert topic] to identify my weakest areas, misunderstandings, or blind spots, and recommend targeted improvements."

@aipost 🏴

❗️Ray Kurzweil believes humans could reach “longevity escape velocity” by around 2032.

His idea is simple but wild: Science may soon extend human life faster than time takes it away.

In practice, that means every year you survive, medical breakthroughs could add more than a year back to your life expectancy.

Kurzweil thinks AI is the key.

He says future AI systems will rapidly test billions of molecular combinations to discover treatments for diseases humans struggle to cure today.

But he sees this as bigger than medicine. Kurzweil believes humans are evolving into a hybrid species, still human, but deeply enhanced by AI.

His vision of the future isn’t really about immortality, it’s about removing biological limits so people can keep creating, exploring, and spending time with the people they love.

The craziest part? 2032 is only six years away.

@aipost 🏴

🔥 Xynova launched Flex 2, its second-generation hybrid dexterous robotic hand.

The hand is built for precise manipulation, with 23 degrees of freedom, a 400g palm, ±0.1mm repeatability, 0.05N force control, 12kg single-hand grasp load, and multimodal sensing for adaptive grasping and slip detection.

@aipost 🏴

🗣 Jeff Bezos once asked people to imagine going back 100 years and telling farmers that one day “massage therapist” would be a real job.

Then he found out something even crazier exists today: Dog psychiatrists. That’s the pattern with every technological revolution.

We obsess over the jobs technology will destroy. We almost never notice the jobs it will create because they don’t even have names yet. A farmer in 1920 could understand a tractor replacing workers.

But there was no way he could imagine careers like:
• Social media manager
• App developer
• YouTuber

Too many inventions had to happen first. That’s where we are with AI right now.

Everyone is staring at the jobs AI may replace. Nobody can yet see the billion-dollar industries and professions sitting “seven inventions ahead.”

The future always sounds ridiculous before it becomes normal.

@aipost 🏴

China expands use of agricultural robots

China is introducing automated systems in agriculture, establishing nonstop robotic harvesting as the new operational standard for food production.

Vision technologies now identify ripe produce, while robotic arms perform the picking and placement. Logistics teams ensure coordination, and human personnel intervene only when necessary.

This development aims to lower fruit prices, reduce produce damage during handling, and support greater supply chain efficiency.

📰 @aipost

"You're going to have a relatively small number of very large companies and a very large number of very small companies because you don't need as many people."

~ Eric Schmidt, Ex CEO of Google

@aipost 🏴

The robot that wakes you up, makes breakfast, and cooks dinner.

@aipost 🏴

🇺🇸🇨🇳Anthropic dropped one of the clearest warnings yet about the US-China AI race.

Their new paper argues the US and its allies could lock in a 12–24 month lead in frontier AI by 2028, but only if they successfully cut China off from advanced chips and American model capabilities.

The report paints a picture of a technological cold war already happening behind the scenes.

According to Anthropic, Chinese labs are staying close to US frontier models through loopholes, smuggled GPUs, offshore data centers, and “distillation” attacks, where companies use outputs from leading American models to cheaply copy capabilities without paying the massive training costs.

Anthropic calls compute the real currency of AI power.

Not just another resource, but the bottleneck controlling everything: training, deployment, experimentation, revenue, and the creation of future generations of models.

One of the paper’s boldest claims is about China’s semiconductor gap. Anthropic estimates Huawei may produce only 4% of NVIDIA’s aggregate compute capacity in 2026, falling to roughly 2% in 2027.

The paper also warns that whoever wins frontier AI may gain something historically unprecedented:

A “country of geniuses in a data center.”

Anthropic believes future model clusters could function like enormous expert workforces capable of accelerating cyber operations, scientific discovery, engineering, military R&D, and state influence at massive scale.

Source.

@aipost 🏴

A delivery robot in Philadelphia was struck by a truck while crossing a street.

Immediately following the collision, the robot displayed heart-shaped symbols on its LED panel. The unit then regained its course and continued on its planned route.

📰 @aipost

Zipline introduces next generation drone infrastructure

Zipline, a leading company in drone delivery, has launched infrastructure designed for automated aerial logistics. The system is structured to operate similarly to a robotic hive, supporting efficient deployment and coordination of delivery drones.

This advancement is intended to increase the speed and reliability of drone-based shipments. The new infrastructure allows for continuous drone operations with minimal human intervention, offering a scalable model for logistics in various sectors.


📰 @aipost

🇨🇳 China is reducing its reliance on foreign AI chips.

China's AI chip self-sufficiency ratio is up to a record 41%. This measures the proportion of domestic AI chip demand met by locally produced chips, rather than imported ones.

This ratio has QUADRUPLED over the last 5 years. The AI chip self-sufficiency ratio is now projected to more than DOUBLE to ~85% by 2030, according to Morgan Stanley. In other words, China could meet nearly all of its own AI chip demand domestically within 5 years.

@aipost 🏴

Vibe coders clicking "accept all" on 22,469 Claude Code changes without reading a single one. 😂

@aipost 🏴