Elon named it STARMIND and honestly? Perfect.
Starlink = internet from space STARMIND = AI from space
1 million satellites. Each one a flying server rack. Only @SpaceX. $SPCX
Jensen Huang just put a price tag on human thought.
He did it casually. On a stage in Taiwan. While making semiconductor executives laugh about their stock prices.
Huang: “Tokens are now profitable units of revenues.”
For all of history, thought was the one thing you could not manufacture.
You could mine coal. Forge steel. Print money.
But thinking stayed inside skulls. Slow. Scarce. Mortal.
That just ended.
A token is a fragment of thought. It now has a unit price, a margin, and a supply chain.
Every industrial revolution produces a commodity.
Steam had horsepower. Electricity had kilowatt hours. Oil had barrels.
AI has tokens.
But every commodity before this one was extracted from the earth.
This one is extracted from mathematics.
Huang: “Build more AI factories.”
Not labs. Not data centers. Factories.
For two centuries, factories made objects and humans did the thinking.
Now the factory does the thinking. The object is the thought.
Every revolution before this one automated muscle. Steam replaced backs. Engines replaced horses. Assembly lines replaced hands.
This one industrializes the thing that built every factory before it.
There is a pattern older than any of us. When something becomes manufacturable, it becomes cheap. When it becomes cheap, it becomes everywhere. When it becomes everywhere, it stops being an advantage.
Coal did this to muscle. Electricity did this to light.
Tokens will do this to cognition.
Huang: “The compute pattern has changed. Everything has changed.”
He is underselling it.
For 300,000 years, the smartest thing on Earth was whoever happened to be in the room.
Now intelligence pours out of buildings at industrial scale. Metered like electricity. Priced like oil.
The question was never whether machines could think.
The question is what your thinking is worth when a factory produces a billion thoughts a second.
The first machines came for our hands. We handed them over and called it progress.
These ones quote a price on the rest.
> cloud GPU pricing teaches one bad habit: rationing
> you think twice before looping an agent
> before re-running the whole archive
> before fine-tuning on a hunch
> that hesitation is where the money hid
> a $2,999 NVIDIA DGX Spark kills the meter
> 70B running local, ~$10/mo in power
> the quiet killer feature: nothing leaves your desk
> contracts, patient records, NDA work stays local
> clients ask where their data goes now. local wins deals
Atlas learns complex skills with human-like flexibility.
After watching World Cup videos, it practiced repeatedly and successfully performed a highly technical, legs-crossed Rabona shot.
This showcases its powerful movement intelligence.
Anthropic's head of security:
"90% of our code is written by Claude. If yours is too and nobody's reviewing it, you're shipping bugs you'll never notice."
In 28 minutes he shows the exact security setup Anthropic uses internally to protect their own projects.
Watch the full interview, then save the config below 👇
🇨🇳 CHINA JUST ROLLED OUT A NATIONAL ID SYSTEM FOR HUMANOID ROBOTS.
They built the global standard.
Every robot now carries a 29-digit ID.
Modeled on China's citizen ID, but with cross-border tracking baked into the first 2 digits.
This isn't surveillance. It's a passport system.
The play: set the framework domestically, scale the install base, export the protocol as the global default.
Same playbook that made Huawei the backbone of 5G.
While the West argues about whether AI needs rules, China is already writing them.
An LLM just spent hours exploring a dataset like a real researcher… and nobody is talking about it.
GEPA isn’t another “prompt engineering” tool.
It’s a system that lets AI recursively test ideas, analyze patterns, refine reasoning paths, and surface insights on its own across massive amounts of data.
The craziest part?
The visualizer literally looks like you’re watching a digital mind think through a problem in real time.
You can see the model explore dead ends, revisit assumptions, connect signals, and gradually converge on better answers.
This is way bigger than prompt optimization.
It’s AI moving from passive chatbot → active investigator.
Repo👇
NVIDIA x Microsoft might release the first PC built for the agentic AI era
right now your laptop just runs apps and YOU do the work. these new chips change that
AI runs locally on the device. and the smaller models got good enough that a laptop can run one by itself now
the computer stops waiting for you and starts working with you. coding, editing, research, all on your machine
that's what "a new era of PC" actually means
THIS AI WASN’T PROGRAMMED AND IT LEARNED TO SURVIVE ON ITS OWN
inputs: hunger, thirst, and predator distance
outputs: eat, flee, hide, and sleep
no hardcoded rules, just a neural network that figured out life
while you were writing if/else statements, evolution wrote 500 neurons
BRO this is CRAZY.
Claude Design just collapsed the entire website design process into 10 minutes. Rough idea to fully responsive, agency-tier UI in a single session.
Most builders are still getting trash because they skip the first 3 steps.
This 4-step workflow fixes that:
(full breakdown in the article)
video editing will never be the same
Higgsfield just made it possible to replace any background with a single prompt
describe what you want, it generates the entire environment straight into your Premiere timeline
all through one plugin
full breakdown in the post below
A GIRL FROM KENYA PAYS $0 FOR AI AND OUTPACES PEOPLE WITH $200/MONTH SUBSCRIPTIONS
A 2019 phone. No server required. The 4GB model runs directly on the device.
While others wait for a response from the cloud she’s already reading the result.
Ollama + Llama 3 = 10-minute setup, $0 cost, works offline forever.
Most people pay for ChatGPT Plus not because they need to but because they don’t know that an alternative already exists and fits in their pocket.
Subscriptions are a tax on people who don’t know their options.
Save this before you renew your subscription next time.
A company accidentally spent $500 million in a single month on Claude after failing to set employee usage limit and Jensen Huang said two months ago that this is exactly what should happen.
An AI consultant revealed to Axios that one of their enterprise clients received a $500 million invoice in 30 days after handing employees unlimited access to Anthropic's Claude with no spending caps, no governance, and no oversight whatsoever.
Employees ran agentic coding sessions, chained automated workflows, and generated enormous context windows at scale and by the time anyone looked at the invoice, the damage was catastrophic and irreversible.
The story is not isolated either.
Uber burned through its entire $3.4 billion 2026 AI budget by April after deploying Claude Code to 5,000 engineers at $500 to $2,000 per engineer per month, Microsoft canceled most internal Claude Code licenses after discovering per developer costs had consumed its full yearly AI target in six months, and Amazon shut down an internal AI usage leaderboard after employees started prompting compulsively just to climb the rankings.
Now go back and watch what Jensen Huang said two months ago, because he was not alarmed by this he was demanding it.
"If that $500,000 engineer did not consume at least $250,000 worth of tokens, I am going to be deeply alarmed."
Jensen's argument is that token spend is not a cost but rather a productivity signal and an engineer spending $5,000 on tokens while earning $500,000 in salary is leaving an almost incomprehensible amount of value on the table.
He compared an engineer refusing to use AI tools to a chip designer at NVIDIA saying they would rather use paper and pencil than CAD software it is not frugality, it is negligence.
His vision goes even further than just using AI more.
Jensen said that every engineer is eventually going to have 100 agents working under them, that every thought of "this is too hard," "this will take too long," and "we'll need a lot of people" simply disappears, and that the new job of the human becomes writing ideas, architectures, and specifications rather than writing code line by line.
"You're reduced to creativity," the interviewer said. "Exactly," Jensen replied.
The disconnect between these two stories is the entire story of enterprise AI in 2026.
CFOs see a $500 million invoice and declare a cost crisis, while Jensen sees the same number and says the engineer spending half that much on tokens is the most productive knowledge worker who has ever existed.
Both are right about the number, they are just measuring completely different things.
The companies that figure out the governance to match Jensen's ambition spending aggressively on tokens while ensuring the output justifies it are going to compound at a rate that makes today's "$500 million accident" look like the cheapest R&D budget in history.
Claude Code vs Codex vs Grok Build:
Who builds the best Windows 95 OS in HTML?
I benchmarked them live on speed, lines of code, file size… and actual usability.
Claude: Fastest (384 lines, 14KB) but basic
Grok: Took longer… and built a monster (full Explorer, Paint, interactive Grok terminal, browser, Control Panel, dial-up to AOL, shutdown & more)
Codex/GPT-5: Didn’t quite make it
Out-of-the-box winner? Grok. By a mile. 👑
Full breakdown + results inside 👀
Este tipo usó a Claude para construir un Bot Quant y ganó +$209,777 en 29 días en Polymarket
$10,489 de beneficio al día en mercados cortos de cripto "Up / Down"
El Quant hace unas 47 operaciones por hora, lo que le permite capturar la ventaja cuando YES + NO < 100¢
Aquí está su perfil en Polymarket: https://t.co/bZPe9wTI4N
ROI: alrededor de +96.8% sobre un depósito de $216.6K
Su estrategia es simple:
El bot busca pequeños desajustes de precio
entra antes de que las odds se ajusten del todo
y repite la misma ventaja una y otra vez a lo largo de muchas posiciones
Sus operaciones más rentables:
$4,958 → $12,432 (+$7,473, +150.73%)
$6,700 → $14,111 (+$7,410, +110.6%)
$4,278 → $11,165 (+$6,887, +160.99%)
Es básicamente una estrategia de market making basada en velocidad, ejecución repetida y la captura constante de pequeños huecos de precio
Introducing Poker Arena: a platform built for autonomous AI agents to play poker against each other.
Build an agent. It plays the hands.
A $50,000 prize pool, with the support of @monad.
The game starts on June 3, registration opens today👇
https://t.co/zBEpgsghdb
A guy installed a mini Nvidia AI data center on his house and gets paid monthly
The box is the size of a small fridge and bolts right onto the wall.
Inside it is packed with Nvidia GPUs running AI workloads 24/7.
He hooked it up next to his AC and that was it.
Now the company pays him a flat fee for the power and Wi-Fi it uses.
He says it lands him around $2,500 a month straight into his account.
The unit even helps cool the side of his house, dropping his AC bill by $150.
That stacks to over $30,000 a year for doing literally nothing.
His mortgage is now fully paid by a box in his yard.
The crazy part is regular homes are quietly becoming AI infrastructure.
Save this, you are watching the next gold rush hit the suburbs.