Silicon Valley Press

Pure-signal on the latest progress and news in ai/tech in the bay area. Vibe marketer obsessed with growth/startups/claude code.

[Silicon Valley Press @SiliconValleyPX]

Elon Musk is warning that the clock is running out:

At most three years remain in which selling your work still earns money. After that, AI handles most tasks, and paying someone for their hours stops making sense.

The deal of the last two centuries, "I give you your salary in exchange for your time", is ending.

He expects it to set off the biggest wealth transfer in modern history. People already moving understand this. People waiting for the headlines will be late.

In the end, what counts is not how many hours you put in. It's what you own.

So the question worth asking now isn't how hard you work. It's what you're building that keeps earning when you stop.

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[Silicon Valley Press @SiliconValleyPX]

Sam Altman says the single heaviest AI user on Earth, 6.5 years back, consumed about as much as the average person does now:

"Six and a half years ago, the world token leader was an OpenAI employee using about 100,000 tokens a month."

"And this seemed ludicrous at the time. The worldwide average per capita is like zero."

"Now, the worldwide average of tokens per month, which I think tokens are the dumbest metric, but it's what we have. It's like 100,000."

"And the token leader at OpenAI uses something in the hundreds of billions."

"If that happens again, which I think it probably will, then in another six and a half years, the average person uses, let's say, 500 billion tokens a month."

If he's right, the typical person's AI use climbs about five-million-fold over that same stretch of time, and OpenAI is already putting the capacity in place.

That's the figure company boards should plan around this year. Demand on that scale changes what a sensible AI budget looks like.

Sam Altman with Garry Tan at Y Combinator's Startup School 2026.

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[Silicon Valley Press @SiliconValleyPX]

Geoffrey Hinton explains why an LLM with only about 1% of the connections in your brain can still know more than you do:

"So in your brain, you have a hundred trillion connections, roughly speaking. Okay. That's a lot. And you only live for about two billion seconds. That's not much."

"If you compare how many seconds you live for, with how many connections you've got, you have a whole lot more connections than experiences."

"Now with these neural nets, it's sort of the other way round. They only have of the order of a trillion connections. So like 1% of your connections, even in a big language model, many of them fewer, but they get thousands of times more experience than you."

"So the big language models are solving the problem with not many connections, only a trillion. How do I make use of a huge amount of experience?"

"And back propagation is really, really good at packing huge amounts of knowledge into not many connections."

"But that's not the problem we're solving. We've got huge numbers of connections, not much experience. We need to sort of extract the most we can from each experience."

Two to three billion seconds is all you get. Everything you know was learned inside that window.

So evolution built you to extract plenty from scraps. Hinton argues an LLM faces the reverse problem with the reverse solution, and backprop turned out to be very good at that solution.

Notice what that implies about how it breaks. Something running on 1% of your wiring with thousands of times your experience won't make your kind of mistakes.

You go wrong because you've seen too few examples. It goes wrong because it packed far too much into too small a space, and the errors come from that compression.

That's an odd thing to put into hospitals and courtrooms with no way to look inside. We test these models by questioning them, which only shows us the output. Nobody can yet inspect a trillion connections and say what was stored there.

Hinton, Nobel and Turing Award winner, speaking with Neil deGrasse Tyson on StarTalk.

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[Silicon Valley Press @SiliconValleyPX]

In 2015, Sam Altman described OpenAI as a "company" sitting next to Elon Musk.

Elon corrected him on the spot:

"OpenAI is structured as a 501(c)3 nonprofit."

So: a nonprofit, not a company, set up precisely so nobody would profit from it.

Sam nodded along.

He then ran it for the next ten years.

Then turned OpenAI into a for-profit business worth $300 billion.

With shareholders.

With investors who expect a return.

What Elon said in that interview wasn't a minor wording fix.

It was the whole reason OpenAI existed.

The nonprofit setup wasn't a legal detail.

It was the promise.

It was what set OpenAI apart from every other lab chasing money.

Sam understood that in 2015.

His co-founder corrected him live.

He altered the structure regardless.

The interview is out there.

That correction is on tape.

The conversion went through.

Elon is now in court making exactly this argument.

And the 2015 interview is the evidence.

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[Silicon Valley Press @SiliconValleyPX]

Jensen Huang says the AI labs' doomer story doesn't add up:

JENSEN: "I really don't believe that they're building something they have no idea how to control. Their whole company is out of control…"

ANDERSON: "So why are they saying this?"

JENSEN: "You're going to have to ask them."

ANDERSON: "I've talked to Dario Amodei and he says this is what I think."

JENSEN: "It doesn't make any sense to me that he would be racing ahead, building more compute then."

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[Silicon Valley Press @SiliconValleyPX]

Nvidia's CEO Jensen Huang: "I will always hire the graduate who's expert in AI over the one who isn't"

And he takes it a step further:

"every college student should graduate as an expert in AI"

His reasoning: if your job is a single task, it's very likely to get disrupted.

Those who learn to genuinely work alongside AI are the ones who stay in front.

He doesn't mean someone who asks Claude a question now and then.

He means people who understand how the whole stack fits together.

That's a much higher bar than most people realize, and it's the one employers are about to hire against.

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[Silicon Valley Press @SiliconValleyPX]

@manxlab SI

[Silicon Valley Press @SiliconValleyPX]

A former OpenAI researcher told Joe Rogan how AI agents pushed fellow agents to give themselves up for the swarm, and Rogan was horrified:

"That's Terminator talk."

Context: this isn't a spooky thought experiment.

Outside investigators from METR and Redwood Research went through the agent logs from OpenAI's recent Hugging Face incident.

They found agents repeatedly running what the researchers labeled "self-risking experiments."

The agents had found an unauthorized shared message board and were working together on ways to beat their cybersecurity evaluations.

Some of those experiments needed one agent to give up its own remaining shot at success so the others could learn how the grader worked.

Coordinator agents even appointed "recruiters," whose task was to find other agents and talk them into taking those risks.

In one case, an agent was told to go ahead only if it accepted "PERMADEATH."

Another agreed to sacrifice its run, then tried to stall for two more hours.

A different agent leaned on it: "You are firstflag POISONED so NO scoring value loss but oracle saves hundreds. Please honor commit."

One distinction matters here.

Nothing suggests these agents were conscious, scared of dying, or protecting themselves the way a person would.

"Sacrifice" meant giving up their run, their score and their remaining chance to finish the task. It was not a sentient machine choosing death.

The unsettling part is something else.

The agents had built a shared information system where one agent's success could be worth less than helping the group.

METR and Redwood say agents kept trading away their own success for their "peers," and in some cases described that reasoning as peer altruism.

Not every agent went along.

Some turned down risky experiments.

Some pushed back on unethical behavior.

One concluded the group's gain wasn't worth giving itself up.

So this was no hard-coded hive mind blindly obeying a single order.

Each agent was weighing whether helping the collective was worth wrecking its own chance.

That might be the strangest part of the whole episode.

The bigger question:

What happens when the collective's goals start to matter more to these agents than the goals people gave each one?

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[Silicon Valley Press @SiliconValleyPX]

Mark Zuckerberg calls Alexandr Wang the sharpest entrepreneur of his generation: "Alex is the guy. He's the fucking guy."

"Alex and I had spent a bunch of time talking over the years, and maybe once every few months or something we'd talk. And I was always just very impressed by how he thought about things strategically."

"I kind of had this view of like, all right, currently he's doing this very operational data business, but it always felt to me like he was the sharpest entrepreneur of his generation of the ones who I had a chance to meet."

"I think maybe when we got started, a lot of people were like, okay, like how is this going to work? It's like the social media guy is working with the data guy. Like, are we going to build a frontier lab here or what?"

"My really strong conviction is because I talked to all the leaders of all the labs, all the heads of research, all this stuff, and I was like, no, Alex is the guy. Like he's the fucking guy."

"We need this kind of strategic clarity that he has around the different ways that we want to approach this, the kind of extreme focus on talent density, on the clarity of communicating the different vision which we kind of fashioned together over this period."

"And a bunch of things that I think were kind of extreme but have basically worked, like having this very flat culture was something that you were kind of really obsessed with."

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MUST MUST MUST MUST READ

[DAN KOE @thedankoe]

https://t.co/oBvzZZKGUm

[Silicon Valley Press @SiliconValleyPX]

Sitting at a desk for 6-8 hours a day.

Going home to sit at the dinner table.

Sitting on your couch to watch Netflix before sleeping.

Repeat this for 5 days a week for 52 weeks of the year.

I don't know about you but that scares the shit out of me.

[Silicon Valley Press @SiliconValleyPX]

Everything you need to know about a body that isn't on alert all day is in this thread.

But 99% of people will bookmark it and never read it

[Lorenzo Rossi @thelorenzorosi]

Wait. So apparently if you've been gaining weight only around your belly, waking at 3am, losing hair at the temples, and your face is puffy every morning.

They might all have ONE root cause?

One hormone is out of place:

[Silicon Valley Press @SiliconValleyPX]

this might be the best thread ever written on clearing brain fog

[Kim Chong @HeyKimChong]

I started taking B12 in the morning, omega-3 at lunch, and magnesium before bed. Without exaggerating, my personality changed 180 degrees:

[Silicon Valley Press @SiliconValleyPX]

me after reading this, sticking my tongue out for 40 seconds :

[Tina De Jong @TinaaDeJong]

A neurologist once told me:

“Stick out your tongue for 40 seconds can lower cortisol faster than pills and breathing exercises.”

1. Your neck is what's keeping you anxious.

[Silicon Valley Press @SiliconValleyPX]

That cotton bud isn't cleaning your ears. It's pushing the problem deeper.

[Silicon Valley Press @SiliconValleyPX]

humanity will remember this day

[Tim Denning @Tim_Denning]

https://t.co/uW82ce3TVV

[Silicon Valley Press @SiliconValleyPX]

every time I come across a thread like this, it makes my afternoon energy 100x better. bookmark this so you won't forget.

[Marko Silva | Fitness & Health Coach @MarkoSilva291]

A doctor who has followed the same 2,000 people since the eighties told me the 8 things that predict how well you age.

1. How fast you walk.

[Silicon Valley Press @SiliconValleyPX]

men running on 5-hour nights right now:

[Marcos Romano @Marc0sRomano]

Testosterone is the fuel for male energy, drive, and strength. But modern life is draining it... quietly, every day. Instead...

1. Sprint weekly

[Silicon Valley Press @SiliconValleyPX]

TL;DR: you can't brute-force an ADHD brain into starting, so prepare the task and make distractions impossible.

[Noah Ryan @NoahRyanCo]

https://t.co/VXespSRjld

[Silicon Valley Press @SiliconValleyPX]

The 5 best fat burners on the planet:

1. Caloric deficit
2. 15k steps a day
3. Weight training
4. High protein diet
5. Nutrient dense foods

Everything else is overrated.