Gatmasil

[Gatmasil @gatwerx]

@0numex @werxxs_k Of the four, talent compounds the most. Patents and money follow people, not the other way around.

[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?

[Gatmasil @gatwerx]

@0numex @werxxs_k Not a god, not a threat. Just leverage, and the question is who owns it

[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?

[Morzik @0xMorzik]

Elon Musk believes humanoid robots could become bigger than the car industry.

Think about that.

Millions of robots working in factories, warehouses, hospitals and eventually inside our homes.

Not just following commands, but learning to perform tasks that once required human hands.

If Tesla gets this right, Optimus could become one of the biggest products the company has ever built.

Would you let a humanoid robot work in your home?

[Gatmasil @gatwerx]

@0numex @werxxs_k Tripled cash flow in two years is the real proof. Which industries did that?

[Gatmasil @gatwerx]

@0numex If even half of that lands, the winners won’t be the AI labs. They’ll be whoever builds the power plants.

[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?

[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.

[Gatmasil @gatwerx]

@0numex Tasks, yes, probably soon. But meaning was never a task. That’s the part no model can hand us.

[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?

[Gatmasil @gatwerx]

@0numex If you ever delegate a negotiation to an agent, set a hard floor first. Graham’s target was $140K. His bot said $60K.

[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?

[Gatmasil @gatwerx]

@xelvoq 14 quarters of “not at this price” then one quarter of “ok now”. thats literally the whole playbook

[Gatmasil @gatwerx]

@0numex Both. Jerry was protecting the thing he owned. The cast was protecting the thing they could still own: their careers. Everyone said no for the same reason.

[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?

[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.

[Gatmasil @gatwerx]

@0numex The cable management alone is a bigger project than the AI.

[Gatmasil @gatwerx]

@werxxs_k Honestly, my biggest change was boring: AI became the first step on every task, whether that's a first draft, a thread summary, or a sanity check before a meeting. No big "transformation," just about an hour saved daily. Habits beat demos.