Werexxs

Content Creator | AI Researcher | Business Founder

[Numex @0numex]

China will ALWAYS beat America in AI.
Here’s why.
50% of the world’s AI researchers are Chinese.
70% of last year’s AI patents were published by China.
9 out of 10 top science and technology schools in the world are now in China, Jensen Huang says.

He calls China’s AI ecosystem vibrant, rich and incredibly innovative.
Now the money.
Huang says China alone is a $50 billion AI opportunity in 2026.
Nvidia once held about 95% of China’s AI chip market.
After US export controls, that fell to around 50%.

Now Huang says Nvidia has largely conceded that market to Huawei.

Talent. Patents. Universities. Money.
That’s what decides AI races.
Can the West catch up?

[Numex @0numex]

Anthropic is raising money at a $350 billion valuation. At the same time, one investor on stage says AI is not what people fear.

Lonsdale spoke at a CAZ Investments conference. He called AI not a god and not a threat to humanity.

In the video below, he explains what it is instead, calmly.

“A productivity tool,” comparable to the Second Industrial Revolution of 1870 to 1900.

He said US services pay about $5 trillion in wages.

About $2 trillion of that, 40%, is ready for a big productivity jump from AI.

He said companies his firm backed two years ago tripled their cash flow.

In many service businesses, he says, AI already doubles or triples profitability.

He also argued that the US has to win the AI race, so hostile states can’t use the technology to shape culture and decisions in other countries.

His message to founders: focus on measurable productivity, not hypothetical threats.

So is AI a real $2 trillion opportunity, or is this just what investors say when they have money on the table?

[Werexxs @werxxs_k]

@0numex Big claim, so verify it. But even a fraction of $20T would rewrite the map.

[Numex @0numex]

Trump called Jensen Huang. Live. On stage.
Jensen just said “put me on speaker.”
And then the whole room heard a number.

$20 trillion.
That’s how much investment Trump says is coming into the US right now.
Under the previous administration, he said, it was less than $1 trillion.

Same country. Same AI race.
A 20x gap, if you believe the claim.

At the same summit, Jensen was pushing back on “AI doomsday” predictions.
He called them unscientific and irresponsible.
So the CEO of the most valuable AI chip company is on stage.
And the President joins by phone.

When the AI story gets this big, it stops being tech news.
It becomes a money story.
Do you think $20 trillion is realistic?

[Milez @milezxbt]

In August 1962, Pete Best was the Beatles' drummer. Then their manager, Brian Epstein, called him into his office.

"In a nutshell, the boys want you out and they want Ringo Starr in."

In the video below, Best tells David Letterman how it happened and what came after.

There was no warning. Best says Epstein paced the room and bit his nails for three or four minutes before he said it.

Best had played with the band for two years, including the long nights in Hamburg. Ringo was a good friend of his.

Within weeks, "Love Me Do" was out. Soon the Beatles were the biggest band in the world.

Best joined another Liverpool group, Lee Curtis and the All Stars. Twice they opened for the Beatles, once at the Cavern and once at the Majestic Ballroom. As Best walked off stage, his old bandmates walked on.

Nobody said a word to him. "Just stony silence."

"They caused me a lot of hardship. Grief, you know, financial embarrassment," he told Letterman.

The case for the band: producer George Martin wasn't happy with Best's drumming at their first EMI session, and John, Paul and George wanted a drummer who fit the group.

In 1995, Anthology 1 came out with recordings that had Best on drums. He reportedly made millions from it.

So was dropping Best just a business call, or did the Beatles owe their friend more than a message from their manager?

[Werexxs @werxxs_k]

@Tetriss112 The 2-unit default cube is the quiet killer. Read as metres, a 20 mm part becomes 2 m, a 100× error that looks perfectly fine on screen. Units belong in the first line of every script.

[Werexxs @werxxs_k]

Elon Musk just admitted he may have sped up the AI race he was afraid of.

He helped launch OpenAI in 2015 to balance Google. Anthropic split off in 2021. His verdict: reality isn’t just an “interestingness maximizer.” It’s an “irony maximizer.”

Now count the irony. 1 lab became 2, and 2 became a race. He sued for $150B, and a jury in May ruled his claims fell outside the statute of limitations.

Then came the plot twist. He wrote that he was “clearly wrong” about Anthropic and called it the current AI leader.

My take: you can’t slow a race by adding runners. Every spin-out and every rival lab adds one more team with a reason to go faster.

Brake or gas? Which side are you on? Drop your take below.

[Numex @0numex]

Jerry Seinfeld turned down $110 million.

NBC offered him $5 million an episode for a tenth season. It was 1997, and Seinfeld was the biggest comedy on TV.

He said no.

Every year before the Christmas break, Jerry asked his co-stars if they wanted to keep going. In season 9, all three said they were done.

Jason Alexander explains why. He, Julia Louis-Dreyfus and Michael Richards were not partners in syndication.

Jerry and Larry David owned the show. The reruns would pay them for life.

Alexander says he has made less than $200,000 from them.

The cast was paid well, reportedly $600,000 an episode by the end. But Alexander says another season only tied them tighter to one character.

His words: “We were going to contribute to our own eventual demise as actors.”

Before the final taping, the four held hands backstage like every week. They called it the circle of power.

Same question today with AI: when your work builds something that pays forever, who owns it?

Who do you think was right, Jerry or the cast?

[Numex @0numex]

Anthropic’s CEO just put a date on it: 2027.

Dario Amodei says AI could be better than almost all humans at almost everything. It could take longer, he adds, but not “a whole bunch longer.”

He’s not an outside critic. He runs one of the labs building it.

The date isn’t the point. The question after it is: if machines do the work, how do humans find meaning?

His answer in 86 seconds: the idea that self-worth comes from economic labor will be invalidated.

“My true belief is that this is coming.”

Does 2027 sound too early or too late to you?

[Numex @0numex]

His own AI agent just negotiated $80K off his salary. In 6 minutes.

Graham sent an AI, Victor, to his job interview. The company sent an AI recruiter, Pat. Graham sat in the call and watched.

His target: $140K–150K.
Victor’s offer: $60K.
The recruiter’s ceiling: $90K, still $30K above what his own bot asked for.
The video is staged, he says. The risk isn’t.
Companies already use AI recruiters on real candidates. An agent that speaks for you can still work against you.

Would you let an AI negotiate your salary? Yes or no.

[Numex @0numex]

Jerry Seinfeld turned down $110 million.

NBC offered him $5 million an episode for a tenth season. It was 1997, and Seinfeld was the biggest comedy on TV.

He said no.

Every year before the Christmas break, Jerry asked his co-stars if they wanted to keep going. In season 9, all three said they were done.

Jason Alexander explains why. He, Julia Louis-Dreyfus and Michael Richards were not partners in syndication.

Jerry and Larry David owned the show. The reruns would pay them for life.

Alexander says he has made less than $200,000 from them.

The cast was paid well, reportedly $600,000 an episode by the end. But Alexander says another season only tied them tighter to one character.

His words: “We were going to contribute to our own eventual demise as actors.”

Before the final taping, the four held hands backstage like every week. They called it the circle of power.

Same question today with AI: when your work builds something that pays forever, who owns it?

Who do you think was right, Jerry or the cast?

[Numex @0numex]

Musk just said most robot demos aren’t real AI.

His test is simple: show the robot something it has never seen. If it still handles it, that’s real AI. Same bar as full self-driving.

The hard part is closing the loop between vision and touch. A robot has far more degrees of freedom than a car, and no script to lean on.

But smart isn’t enough. Production ramps like an S-curve, and the beginning is slow. The supply chain for robot parts barely exists.

His example: if China cuts off magnets for electric motors, you get robots with no arms.

The winner won’t have the best demo. They’ll have the supply chain.

What matters more in the next 5 years: smarter AI or the supply chain behind it?

[Numex @0numex]

40 Mac Minis cost about the same as one Nvidia H100.

Someone in China just lined up hundreds of them on yellow hardware-store shelves. Cables everywhere, a dashboard on a monitor, daylight through the office windows.

Each Mini draws 5 to 40 watts. No special power, no cooling. Unified memory means small models run well on retail hardware.

One Mini loses to an H100. But 40 of them running small models in parallel, 24/7, with zero cloud bill? For some workloads, that math works.

The catch: managing hundreds of separate machines is painful, the networking is slow, and none of it will train a frontier model.

Everyone is fighting over GPUs. Some people just bought shelves.

Smart move or expensive toy? Tell me below.

[Numex @0numex]

Anthropic’s CEO says: “We don’t know if the models are conscious.”

A neuroscientist just told TED: we do know.

Anil Seth’s answer is one word.
No.
Here’s his argument. It’s simple.

Simulate a hurricane on a supercomputer.
Does anything get wet?
No.
The storm is in the code. The rain isn’t.

Now simulate a brain.
Every neuron. Every connection.
Does anyone feel anything?
Same logic. A simulation of a mind isn’t a mind.
So why does ChatGPT feel conscious?
Because for all of human history,
language meant a mind was behind it.
Now we’ve built something that talks without one.
Our instincts haven’t caught up.
Seth’s idea is the uncomfortable part.

Consciousness may not be about intelligence.
It may be about being alive.
A body that has to keep itself going.
Something at stake.
Intelligence is what you do.
Consciousness is what it feels like to be a living thing doing it.
His closing slide:
“AI is computer software. It is not a living mind.”
The real risk may not be a conscious AI.
It’s millions of people believing in one.

Do you think he’s right?

[Werexxs @werxxs_k]

@0numex Smart, for the right workload. Cheap inference at scale beats a cloud bill. Training is where it falls apart.

[Werexxs @werxxs_k]

@gatwerx That’s the real signal. The tools that win become invisible, just the first step of every task. An hour saved daily compounds fast.

[Werexxs @werxxs_k]

Sam Altman just admitted he was wrong about AI.

He expected GPT-4 to shake up software almost overnight. It didn’t.

His words: “The economy just has so much inertia.” People keep doing the same things and buying from the same companies.

The tech moves at lab speed. Society moves at human speed. Habits, budgets, trust: none of it updates with a model release.

“Changing behavior is just much harder than tech nerds realize.”

The bottleneck isn’t intelligence anymore, it’s adoption. The edge goes to whoever makes AI a boring daily habit inside a real workflow, not to whoever has the flashiest demo.

What has actually changed in your work because of AI? Tell me below.

[Werexxs @werxxs_k]

@xelvoq Exactly. Swapping the engine is easy. Rebuilding the floor around it is the hard part.

[Werexxs @werxxs_k]

@0xShoopy Because “best” gets the headlines, and “good enough” gets the invoices.

Most real workloads don’t need the strongest model.
They need an answer that’s right enough, at a price that scales.

[Werexxs @werxxs_k]

Hundreds of $599 Mac Minis are doing the work of a GPU cluster. And their owner pays $0 for the cloud.

The video shows the whole setup. Every screen is a grid of dozens of terminals, and each Mini runs its own job.

Here’s the math:
A Mini draws 10 to 30 watts under load.
A traditional GPU server pulls 300 to 500.
Hardware you can buy at retail, no waiting in line for GPUs, no monthly invoice.

One Mini won’t beat an H100. But dozens of them running small models in parallel, 24/7, are good enough for classification, labeling and fine-tuning.

Some people already make $25K+ a month renting out that power.

The catch is real. Managing hundreds of separate machines is painful, networking between them is slow, and none of this trains a frontier model.
The AI race isn’t only about who has the biggest chip. It’s also about who runs “good enough” the cheapest.

Would you build one, or is it an expensive toy?

[Werexxs @werxxs_k]

https://t.co/x86gg0oyDA

[Werexxs @werxxs_k]

Look at what these 6 patterns have in common.

None of them makes one agent smarter.
They all make one agent less trusted.
Classify-and-act: don’t let one agent do everything.
Adversarial verification: don’t trust the agent that wrote it.
Generate-and-filter: don’t trust the first answer.
Tournament: don’t trust one judge.
Loop until done: don’t trust one pass.

The reliability comes from the structure around the models.
There’s a cost angle too.
Fan-out, generate-and-filter and tournaments burn a lot of calls.
At 1,000+ agents, the model you pick per role matters more than the model you pick overall.
My take: cheap models for classifying and generating options, the strongest one for verifying and judging.
Which of the 6 would you try first?

[Werexxs @werxxs_k]

@uuexgk The real question isn’t which one is faster.

It’s which one is cheaper per task.

Nobody needs an H100 to classify messages or label data.