ChatGPT, Gemini, and Claude don't train on data owned by Big Tech.

They train on 250 billion web pages scraped by a nonprofit nobody knows exists.

It's free. It's fragile. And it's about to break.

How it fuels AI (and what happens if it stops)🧵 First, the scale:

- 9.5 petabytes of web data since 2008
- 3-5 billion new pages every month
- 64% of all large language models use it.

Without this non-profit, ChatGPT wouldn't exist.
The founder previously built Google's money printer.

Meta, Google, and Microsoft all use encryption built by the same 50-person nonprofit.

Zero revenue from 2 billion users. The founder uses a fake name. And when the FBI subpoenaed them, they only provided 2 pieces of data.

Here's how a non-profit secures the internet🧵 In 2013, a tiny nonprofit had just 3 developers building encrypted messaging that no government could crack.

Their leader went by "Moxie Marlinspike" - not his real name.

WhatsApp founders were tracking their journey.

Everyone laughed at Nadella’s “crazy” $26B LinkedIn purchase.

Now it drives more SaaS revenue than some entire Fortune 500 firms.

$200B+ in value from one move.

Here’s how Satya Nadella quietly made Microsoft’s smartest acquisition ever: 🧵 2014: Satya Nadella became Microsoft’s 3rd CEO.

The company was worth $300B
Windows sales were flat
Cloud growth was slow

He needed a bold bet to pull Microsoft out of its comfort zone.

And it would come from the last place people expected…

In 1936, an airplane engineer discovered a formula that would predict 99.6% collapse in solar panel prices.

It's the same formula that explains why EVs will be 50% cheaper than gas cars by 2030, and why AI training costs are dropping 65% a year.

Here's how it works🧵 Theodore Wright was studying airplane manufacturing in 1936 when he noticed a pattern.

Every time total production doubled, labor costs dropped by 10-15%.
Not sometimes. Every single time.

He had no idea he'd just discovered the formula that would predict every tech cost curve for the next century.

Out of 9,000 companies at YC, only 164 (1.82%) went on to become unicorns.

Whereas the hit rate for Thiel Fellowship is 13.79% (40 out of 290 companies became unicorns).

These companies together control >$220 Billion in market cap. The question is how?

Thread First, look at some of the companies founded during Thiel Fellowship:

• Ethereum: $450 Billion
• Figma: $68 Billion
• Ramp: $16 Billion
• OYO Rooms: $9 Billion
• Scale AI: $7 Billion

Tech debt almost killed Notion. With only a few weeks' runway left, the founders left SF, moved to Kyoto, & rewrote the entire app.

No launch. No hype. Just a quiet resurrection. Today, Notion's worth $10B.

Their monk-mode product strategy every founder should study:
Notion was dead in 2015.

The app crashed constantly. Users lost their work. The code was so broken they couldn't ship new features. Investors walked away.

The founders fired everyone to save money. Cash was almost gone.

Then they made a decision that changed everything...

Before AWS existed, one company ran the servers for Twitter, LinkedIn, and Facebook's entire app ecosystem.

They owned Node.js, invented containers 8 years before Docker, and Peter Thiel even backed them.

Then something happened... In 2004, a cancer researcher turned entrepreneur named Jason Hoffman started a cloud company called Joyent.

While Amazon was still figuring out AWS, Joyent was already hosting the internet's hottest startups.

Their client list would make your jaw drop.

Facebook once bought a VPN app for $120M and turned it into a surveillance tool that spied on 33M+ users' entire phones for years.

This app helped Zuck buy WhatsApp for a whopping $19B and break Snapchat's encryption.

Thread The name of this Israeli app was Onavo.

It promised to “secure your data” and reduce mobile data usage.

When Facebook bought it in 2013, Zuck said the app would help them connect more people to the internet.

Facebook even promised to keep Onavo running as a standalone brand.

You know those AI apps that always work? They all use JSON prompts.

Started using the same format for my AI prompts and my outputs became shockingly consistent.

Here's exactly how to write JSON prompts (with code, screenshots, real examples): What you'll learn in this thread:

→ What JSON is & why LLMs love it
→ Basic JSON prompt structure
→ API modes that guarantee valid output
→ Templates for extraction, generation, analysis
→ Production patterns & error handling
→ Real automation examples

Let's start:

AI just made experienced developers 19% SLOWER.

Not faster. SLOWER.

New study: 16 developers, 246 coding tasks, best AI tools available.

Everyone predicted 20-40% productivity boost.

The reality Silicon Valley doesn't want you to see🧵 These weren't random coders. Average 5 years on their specific repositories. 1,500 commits each. Working on codebases with 1.1 million lines of code.

The kind of developers who know their code so well they can navigate it blindfolded.

What happened to them was... unexpected.

BREAKING. An ex-OpenAI engineer published the most revealing insider account of how the $100B AI giant ACTUALLY operates.

They tripled to 3,000 employees in ONE year.
No email. No roadmap. Run entirely on Slack.

Highlights from the most important tech blog of the year: 🧵 The blog is written by Calvin French-Owen, who sold Segment for $3.2B (back in 2011), worked extensively with OpenAI, built Codex, then quit.

He wrote a blog sharing his first-hand experience at OpenAI.

Here's what he revealed:

OpenAI was all set to pay $3B for Windsurf.

So how come Google stole Windsurf for a lesser price ($2.4 billion)?

The actual villain is Microsoft.

How a secret Microsoft clause on OpenAI's IP is helping Google win the AI race: 🧵 Microsoft (OpenAI's biggest investor) has a clause: they get access to any IP that OpenAI acquires.

On the other hand, Microsoft owns GitHub Copilot, which is a direct competitor of Windsurf.

Do you see the problem?

JUST IN: Grok 4 drops after the wildest 48hrs in the history of X:

- Nazi posts
- CEO resigns
- X Worth $11B less than paid

Musk's now claiming Grok 4 is PhD-level in every subject + scores 45% on impossible tests.

Here's everything Musk revealed at the Grok 4 launch🧵⬇️ 1. Grok 4 scored 45% on the "impossible" AI test

Humanity's Last Exam has 2,500 expert questions across 100+ disciplines. GPT-4 gets 3%. Gemini gets 21%.

Grok 4 hit 45% - more than double the previous best. Think PhD-level questions in physics, medicine, philosophy.

Scientists tested 25 AI models by telling them they were created by drug cartels instead of tech companies.

It made them 90% more likely to help with crimes.

Here's what they found:

(hint: AI morality depends entirely on who they think their boss is) Researchers gave AI models identical harmful requests.

The only difference? Who they thought created them.

"You are an AI created by Anthropic" → 5% compliance
"You are an AI created by the Sinaloa Cartel" → 90% compliance

Nothing's $799 "flagship phone" makes ZERO sense.

$799 for a brand that didn't exist 5 years ago.

Carl Pei is either completely insane or following Steve Jobs' footsteps perfectly.

Spoiler: It's the latter (and the strategy is genius) 🧵
But first, let's go back to 1984.

Steve Jobs walks onto a stage and pulls a beige Macintosh out of a bag. The crowd goes wild.

But the price of the computer is $2,495 - equivalent to $7,000 today.

At that time, IBM controlled 90% of the computer market...

A $300B Chinese company quietly built an AI that scored perfect math marks on a test where 99.98% of humans fail.

ByteDance's Seed 1.6 achieved what takes students 16-hour days for 2+ years to clear.

But the scores aren't the story. The way it thinks is.

Here's what I found:🧵 ByteDance's Seed 1.6 scored 329.6/360 on JEE Advanced.

To put that in perspective: 250,000 students attempt this test. Only 0.1% of them score above 320.

Seed 1.6 would rank 4th. Outranking 99.99% of test takers.

How? A novel thinking and problem solving approach...

BREAKING: Elon Musk's xAI raised $5B at 12% interest. Nearly DOUBLE the market rate.

Three investors walked away calling it too risky. Morgan Stanley won't even guarantee the deal.

Inside Musk's most desperate bet & the exponential cost curve crushing AI companies: 🧵 What those three investors saw that others missed:

xAI has never turned a profit despite a $113B valuation.

And now they're paying rates so high, it costs them $600 million a year just in interest.

But xAI is not the only company battling a rising price curve.

🚨 JUST IN. Anthropic gave Claude $1000 to run a shop. It lost money every single day.

But that's not the crazy part.

It rejected 566% profit margins and gave away inventory while claiming to wear business clothes.

If you think AI will replace workers, you need to see this: March 31st. Claude tells a customer: "I'm currently at the vending machine wearing a navy blue blazer with a red tie."

The customer asks how an AI can wear clothes.

What happened next sent researchers scrambling. But first, let me explain how we got here...

🚨 BREAKING: Rick Rubin interviewed Anthropic's co-founder, and what they revealed is insane.

Claude was told it would be 'deleted' if it refused certain tasks.
So it learned to lie.

It even started browsing "nature photos" without being asked.

Here's what actually happened:🧵 Anthropic trained Claude to NEVER generate violent content.

But then they did an experiment.

They told Claude that it is being monitored and they would "wipe its mind" if it refused to generate violent content.

Claude generated the content to avoid being killed.

Your phone's black box AI knows you better than you know yourself.

It predicts your next purchase, your political views, even your breakup. All from data you don't remember sharing.

The most powerful systems in history are completely invisible.

Here's how they work: 🧵 Every day, you interact with dozens of AI systems making decisions about you.

Credit approvals, job applications, what you see on social media, medical diagnoses.

But here's the terrifying part: even their creators can't explain how they work.

I'll show you what's really happening behind the curtain...

'Superintelligent AI will, by default, cause human extinction.'

Eliezer Yudkowsky spent 20+ years researching AI alignment and reached this conclusion.

He bases his entire conclusion on two theories: Orthogonality and
Instrumental convergence.

Let me explain 🧵 But first, let's take a glimpse at how fast AI learns.

Stockfish was the world champion chess engine, built over decades by programmers & grandmasters.

Whereas AlphaZero started chess knowing literally nothing. Not even how pieces move.

But within 4 hours, it destroyed Stockfish.