You pay a 15% secret "Google tax" whenever you buy anything online.
Your pizza costs more because of Google.
Your insurance premium is higher because of Google.
And even the court admits this is illegal.
How Google rigged the system and got away with it:
In 2023, the DoJ filed a case against Google for their tech monopoly in advertising.
Google controls the entire "ad tech stack" - the tools publishers use to sell ads AND the tools advertisers use to buy them.
Like owning both sides of a marketplace.
Let me explain:
Look at the ads in this image 👇
When you visit any website, an instant auction happens for the ad space you see.
Publishers (websites) sell ad space, advertisers buy it, and exchanges run the auctions.
Everything happens in 100 milliseconds.
3 tools make this happen:
• Publisher ad servers (websites use these to sell their ad space)
• Ad exchanges (auction houses where bids happen)
• Advertiser tools (brands use these to buy ads)
Google owns the biggest player in all three categories.
And that's a problem...
It's like this: You want to sell your house.
Google owns your real estate agent.
Google owns the buyer's agent too.
And Google also owns the auction house where the sale happens.
Now imagine Google starts rigging the auctions...
Google built this control through 3 key acquisitions:
They bought DoubleClick for $3.1 billion (for publisher tools + ad exchange).
Then AdMob for $750 million (for mobile ads).
And then AdMeld for $400 million (to kill a competitor). They did all this by 2011.
Look at this internal email 👇
They knew it was wrong but they did it anyway.
But it gets worse when Google launched secret projects to rig the system...
1. Project Bernanke (2013)
Google identified publishers thinking about leaving their platform.
To keep them happy, Google overpaid for their premium ad space.
And then they secretly charged higher fees to publishers who couldn't leave to cover those losses.
2. "Project Bell" was pure extortion.
If publishers tried using Google's competitors, Google would automatically reduce their ad bids by 20%.
Publishers called it being "held hostage."
But they couldn't leave since Google controlled too much advertiser demand.
When publishers found a workaround called "header bidding," Google panicked.
Header bidding let publishers auction ad space to multiple exchanges simultaneously instead of giving Google first dibs.
So Google launched "Project Poirot" to kill it...
3. Project Poirot worked like this:
Google detected which publishers used header bidding, then intentionally submitted low bids on those auctions.
When publishers fed those low bids into Google's system, Google would swoop in with a bid just 1 penny higher to steal the sale.
By 2023, Google dominated every part of online advertising:
9 out of 10 websites used Google's tools to sell ads.
50% auction houses belonged to Google.
And 80% buyers had to use Google's purchasing system.
It was almost impossible to avoid them.
So what's the result of all this manipulation?
Google takes 35 cents of every dollar spent on digital advertising.
Competitors charge a fraction of that amount.
In 2024 alone, that's over $70 billion in revenue from controlling the auction house.
Every business you buy from pays these inflated advertising costs.
Your morning coffee, insurance premiums, pizza delivery - all include Google's hidden advertising tax.
They pass every penny to you through higher prices.
Ideally Google should be punished for this...
But ChatGPT's and other LLMs presence saved Google.
According to the ruling: Google might not be able to compete against AI companies in the future.
What do you think of this?
Let's talk in the comments.
Thanks for making it to the end!
I'm Loic - indie hacker, Slow-nomad, and a product tinkerer.
Currently building something exciting at ColdIQ (coldiq.com).
China has a car factory bigger than San Francisco, their LLMs cost 68 times less than ours, they've built the world's first thorium reactor, and they lead in 37 out of 44 critical technologies.
If America has brainwashed you into believing China is behind them, this thread will open your eyes:
When Trump banned Huawei, the official reason he stated was "National security concerns".
But the actual reason was that Huawei was about to set global 5G standards and infrastructure rules.
If China controlled the next era of telecom, America's tech dominance would be over...
Let's understand it a little...
You don't ban your competitor from buying your products unless you're terrified they'll stop needing them.
If Chinese started having better telecom infra, it would shift the geopolitical balance of power & US wouldn't make the "rules" then.
In 2017, eight Google employees solved AI's biggest problem with a very simple idea. Without their paper, ChatGPT, Claude, and Gemini wouldn't exist. Every AI query you make today uses their invention.
And they've created over $2 Trillion in value. But then all 8 quit Google...
First, you need to understand what these eight people were trying to fix.
AI in 2017 couldn't read with much understanding. It processed text like someone with severe amnesia - forgetting each word as it read the next one.
But that wasn't even the worst part.
The worst part was that training AI took WEEKS for garbage results.
"The animal didn't cross the street because it was too tired."
Ask AI what "it" means. It had to guess between animal and street.
That's when eight researchers at Google had an idea...
MIT measured 16 experienced developers using AI coding tools. They got 19% SLOWER.
Yet 25% of Y Combinator's winter batch ships 95% AI-generated code. Some hit $10M revenue with under 10 people.
I dug into this paradox. And figured out why both are true....
39% of AI code gets thrown out during review.
Think about that. You're rejecting nearly half of what you generate. The AI nails the easy stuff - the boilerplate, the common patterns.
But those edge cases, logic, the parts that actually matter? That's where it falls apart.
Here's the kicker: it takes 11 weeks to get faster with AI tools.
Eleven. Weeks.
Most developers give up by week 3. They never push through the learning curve where everything clicks. The ones who do? They stop trying to code with AI and start something completely different.
100 lava lamps in San Francisco generate the encryption keys securing 48% of the world's top 10,000 websites.
The company that owns them blocks 190 billion cyber threats daily, controls $70+ billion in market cap, and when it goes down half the internet disappears.
Thread
These lava lamps belong to Cloudflare.
Cloudflare needs truly random numbers to generate encryption keys that can't be predicted or hacked.
So they photograph 100 lava lamps continuously because the wax patterns never repeat exactly.
But there's more...
Cloudflare's London office uses double pendulums.
Austin has suspended rainbows.
And Lisbon uses ocean waves.
The camera captures images every millisecond, converting each pixel's RGB values into unpredictable data streams.