High Signal AI

Signal in the AI noise

[High Signal AI @HighSignal_AI]

Steve Jobs on Failure (1994):

[AI Highlight @AIHighlight]

This is the part nobody saw coming. You don't log into Nitrosend, you just tell it what you want and the email lands in 10,000 inboxes.

One prompt did the writing, the design, and the send. The dashboard is officially extinct.

[Big Brain AI @realBigBrainAI]

Managing Partner and CIO of Atreides Management Gavin Baker on why the entire AI market is pricing in two completely different futures at once:

He argues that the numbers across AI stocks can't all be right at the same time:

"If you look at the valuations for all these AI names, they just they can't all be accurate."

He breaks down the disparities he's seeing across different parts of the market:

"You have memory makers at, you know, three to five times PE. You have Nvidia at a really low PE. You actually have some other accelerator companies at reasonable multiples. And then you have everything else. Everything in power, everything in cooling."

He clarifies what he means by power, noting that utilities and IPs aren't the issue:

"And when I say power, I don't mean utilities. The IPs are actually quite reasonably valued. But power, cooling, even probably some of some of the optical names. These are discounting very different things."

This is the heart of his argument. Different corners of the market are pricing in completely different futures, and only one of them can be right:

"If the multiples on the power cooling optical names are correct, Nvidia memory, they're going up a lot. If the multiples on Nvidia and memory are correct, everything else is probably going to underperform."

@GavinSBaker sums up the situation in a single phrase:

"The AI market is cross-sectionally inefficient right now, which is what I was trying to say."

[High Signal AI @HighSignal_AI]

Sam Altman, CEO of OpenAI, poses a question to physicist David Deutsch about what it would actually take to believe an AI is thinking:

The setup is a discussion of Einstein and general relativity which Altman calls one of the most beautiful things humanity has ever figured out, maybe even number one.

But his point isn't about the physics. It's about the story. As Altman puts it:

"Einstein had a story. We knew what he was working on."

We knew the problems Einstein wrestled with, the questions he chose to chase, and the path he took to get there. That narrative is part of how we recognise genuine understanding.

So @sama builds a hypothetical to test the line between imitation and real reasoning:

"If in a few years GPT-8 figured out quantum gravity and could tell you its story of how it did it and the problems it was thinking about and why it decided to work on that, but it still just looked like a language model output but it really did solve it… would that be enough to convince you?"

In other words: not just the right answer, but the reasoning, the choices, the why this problem. The same things we'd want from any human physicist.

Deutsch's response is short:

"I think it would. Yeah."

And Altman accepts it as the bar: "I agree to that as the test."

The real test for AI might not be whether it can pass as human, but whether it can produce something genuinely new: solving a problem that's eluded us for a century and account for how and why it got there. Output alone isn't enough. The story is what makes it convincing.

[Big Brain Business @BigBrainBizness]

Roy Lee, founder of Cluely, on the unconventional list of employee benefits he offers at his startup:

After building Cluely into a roughly $120 million company in under a year, Roy Lee laid out the perks he offers his team, and the list reveals how he thinks people do their best work.

He starts with pay:

"First, everyone gets paid a minimum of $200,000 USD."

From there, the benefits get more unconventional.

For housing, he gives people a choice. The team can live communally, or opt out:

"If anybody chooses to not live with us communally and wants to get another place, I will give you a $2,500 a month housing stipend to get a place for yourself in New York."

Food and transportation are fully covered, with one quirky condition:

"All food and transportation is comped with no exceptions as long as you are purchasing meat or protein."

Then comes his take on time off, which doubles as a window into what he values:

"I will give unlimited paid time off if you choose to go on a date and you want to leave the workday 10 hours early. I will always allow because I think this is important."

@im_roy_lee extends the same logic to rest.

Rather than push people to grind through exhaustion, he built a dedicated space for sleep:

"We have a communal nap area where anybody can take any time out of the day and decide to take a nap whenever they want. I never get any work done when I'm sleepy. And I think it's one of the worst things ever is to try and work while you're fighting the urge to sleep."

Finally, for single employees who want it, he covers Hinge Premium.

His reasoning is pure cost-benefit math: if paying $25 a month even slightly improves your chances of meeting your future partner, he argues, you'd be foolish not to take him up on it.

The throughline across all six benefits is the same:

Remove friction from people's lives so they can focus, and treat their personal happiness as something worth investing in rather than something that competes with the job.

[Pascal @creatorpascal]

https://t.co/ZF7t0JSRe4

[Big Brain Business @BigBrainBizness]

Elon Musk breaks down the "elementary truth" most people forget about what a company really is:

[Big Brain AI @realBigBrainAI]

A Japanese developer just recreated one of Apple Vision Pro's flagship features for less than $10.

[High Signal AI @HighSignal_AI]

In the early 2000s, this "Cyborg Green" laptop shipped with 25-pin parallel, 9-pin serial, dual FireWire, S-Video, and four audio jacks. No dongles. No adapters. Just plug in and go.

[Igor Buinevici @Igor_Buinevici]

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From Yale, Harvard, Wharton, and others.

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Courses are either free or available to audit for free.

Most people never fully commit to improving themselves.

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[Big Brain Business @BigBrainBizness]

Howard Marks, co-founder of Oaktree Capital Management, on why accepting that you'll never time the market perfectly actually sets you free:

Marks explains that certainty is something investors will never have, and that admitting it changes everything.

"You're never going to get it exactly right," he says.

"Sometimes if we're lucky, we know what's going to happen. We never know when."

For @HowardMarksBook, that admission is liberating:

"If you accept that, then it kind of gets you off the hook."

He illustrates the point with a simple example of buying as a stock falls:

"That means you buy today at 9, it goes to 8. You buy more. It goes to 8, you buy at 8, it goes to 7. You buy more."

The mistake, Marks argues, is treating each drop as proof you were wrong:

"You don't say, 'Oh my god, I bought at 9, it went to 8. I must be a moron and I must be wrong.' You understand the nature of this."

To make the case, he points to Warren Buffett's well-known analogy:

"Warren Buffett says I like hamburgers, and when hamburgers go on sale I eat more hamburgers."

The lesson Marks draws is about conviction grounded in sound analysis, not price movement:

"If you did an analysis at 9 and if the analysis was sound and it goes to eight, you should buy more."

What this comes down to is simple:

You can't control timing, so there's no point punishing yourself when the market moves against you in the short term.

Once you accept that uncertainty is built into investing, a falling price stops feeling like a verdict on your judgment. If your original analysis was solid, it's simply a discount.

[Big Brain AI @realBigBrainAI]

Adam Aleksic, a Harvard-trained linguist, on why a single boring word reveals how AI is quietly reshaping human speech:

Aleksic says you can see something strange happening to human language in one small, unremarkable word: delve.

He explains that since ChatGPT came out, the numbers around this word have gone wild:

"Usage of the word 'delve' has spiked a 1,000% since before 2022."

So why does ChatGPT love "delve" so much? According to Adam, the answer is baked into how the model was trained:

"There is a bias in the reinforcement learning process... when the words get trained into the model."

@etymology_nerd lays out two reasons.

The first is about the people doing that training work:

"The reinforcement workers are in Nigeria and Kenya, where they do actually say 'delve' at higher rates — but still not that high."

The second is about the kind of vocabulary the model gravitates toward.

Adam notes that "delve" is a Latin word, and that ChatGPT carries a Latin-based bias, leaning toward dramatic-sounding words rather than the basic connective ones like "the" and "but."

His explanation for why:

"Because these models are trained to sound like they know what they're talking about, they're going to use more of the romance language stuff."

So ChatGPT keeps producing "delve." But here's the part Adam flags as genuinely unsettling:

The influence doesn't stay inside the machine. There's now evidence that, in just the past few years, humans have started using "delve" more often in their own spontaneous, spoken conversation.

As the interviewer Chris Williamson summed it up: "So the creature that programmed the AI is being programmed by the AI."

Adam's reply captures the entire phenomenon in five words:

"Its reality is influencing our reality."

[High Signal AI @HighSignal_AI]

Jesse, the founder and CEO of Rabbit, on why the device in your pocket is broken and the new kind of AI he built to replace it:

Rabbit's mission, @jesselyu says, is "to create the simplest computer, something so intuitive that you don't need to learn how to use it."

The thing he's trying to fix isn't the smartphone's hardware. It's what's inside:

"The problem with these devices, however, is not the hardware form factor. It's what's inside the app-based operating system."

He describes the daily friction we've all stopped noticing. Fumbling through pages and folders to find the right app, then clicking endless buttons. As he puts it: "Add to the cart, go to the next page, check the boxes, and jumping back and forth, and so on."

Then comes his sharpest line. The smartphone was supposed to be intuitive, but with hundreds of apps that don't work together, it isn't anymore. And worse:

"Our smartphones has become the best device to kill time instead of saving them."

Jesse walks through why earlier attempts failed. A decade ago, Siri, Cortana, and Alexa "often either don't know what you're talking about or fail to accomplish the tasks we ask for." Modern LLMs solved the understanding problem. Chatbots proved natural language is the path forward but they hit a different wall:

"Where these assistants struggle is still getting things done."

His example: ask ChatGPT's Expedia plug-in to book a ticket, and "it can suggest options but ultimately cannot assist you in completing the booking process from start to finish."

The breakthrough came from a simple insight about what every app on iOS, Android, or desktop has in common: an interface.

"At a philosophical level, if we can make an AI trigger actions on any kind of interface just like a human would, we will solve the problem."

That became the Large Action Model (LAM). Jesse draws the distinction cleanly:

"The large language model understands what you say, but the large action model get things done."

Or, as he sums it up: "We use LAM to bring AI from words to action."

He packed the LAM into an operating system, rabbit OS, and then into a standalone device built in collaboration with Teenage Engineering: the Rabbit R1.

[Justin Mecham @thejustinmecham]

I think a lot of us are tired.
Not lazy. Not ungrateful.
Just tired of building a life where
our best ideas keep getting pushed
to someday.

But someday is expensive.

Life is too short to only build
someone else’s dream.

At some point, you have to ask:

What am I building that still belongs to me?

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[Big Brain Business @BigBrainBizness]

What if you could look young forever without needles? On Shark Tank, the founder of Face Yoga with Koko says you can.

[Big Brain AI @realBigBrainAI]

In universities, Claude won't just hand students the answer. It flips the question back: "What did you find confusing about the essay?"

[High Signal AI @HighSignal_AI]

The recipe for a viral AI edit: take one instantly recognizable thing, then remix it everywhere. Here, it's Tom Cruise running, except he never stops:

[Big Brain Business @BigBrainBizness]

Apple co-founder Steve Wozniak reveals how he and Steve Jobs bootstrapped Apple with almost nothing:

[Big Brain AI @realBigBrainAI]

12 parallel agents fixed 3,528 TypeScript errors in half an hour, which cost a full 5-hour credit window on Claude Code.

[High Signal AI @HighSignal_AI]

'Neural Network' by Kim Seonghyun mirrors how the human brain processes information running live inference so you can watch a trained model take an input and produce an output. One of the cleanest examples of turning something buried in code into something physical and understandable

[Patrick Sullivan Jr. @realPatrickJr]

Low magnesium is linked to bone loss, insulin resistance, poor sleep, and a 54% higher risk of sudden cardiac death.

The standard test only reads 1% of your supply, so most deficiencies never get caught.

And the form on most shelves absorbs at 4%.

What to take instead: