Deedy Profile picture
Nov 26, 2024 9 tweets 2 min read Read on X
A single fairly unknown Dutch company makes maybe the most expensive and complex non-military device ($200M) that builds on 40 years of Physics and has a monopoly responsible for all AI advancement today.

Here's the story of ASML, the company powering Moore's Law..

1/9 Image
ASML's extreme ultraviolet (EUV) machines are engineering marvels.

They shoot molten tin droplets 50,000x/s with a 25kW laser turning it into plasma as hot as the sun's surface to create 13.5nm UV light —so energetic it's absorbed by air itself.

2/9
Each $200M machine contains mirrors that are the smoothest objects humans have ever created.

They're made with layers of molybdenum/silicon, each just a few atoms thick. If you scaled one to the size of Germany, its largest imperfection would be 1mm high.

3/9
This light goes through the mirrors onto moving 300mm silicon wafers at highway speeds (~1m/s) with precision better than the width of a SINGLE SILICON ATOM (0.2nm).

That's like hitting a target in SF from NYC with the accuracy of a human hair.

4/9
TSMC's 4nm process for NVIDIA H100 needs ~15 EUV layers (+80 DUV layers).

Each layer must align within nanometers. One machine processes ~100 wafers/hr. Cost? About $150K of chips per hour.

Other techniques cannot get the quality + throughput + cost to this level.

5/9
Why monopoly?

The supplier network:
— Zeiss (optics)
— Trumpf (lasers)
— VDL (frames)

40 years of co-development, 40,000 patents, 700+ suppliers. They own 24.9% of Zeiss's semiconductor div.

Replication would take decades + $100B+.

6/9
The complexity is astounding.

Each machine ships in 40 containers and takes 4 months to install. The supply chain spans 700+ companies. 100K+ parts per machine, 40K patents protecting it.

One missing component = global semiconductor disruption.

7/9
Only three companies can run cutting-edge EUV:
— TSMC (that makes GPUs for Nvidia)
— Samsung
— Intel.

ASML machines are the only way to make chips dense enough for modern AI. Each H100 has 80B transistors. The next gen will need >100B.

Impossible without EUV.

8/9
Rich Sutton's "The Bitter Lesson" is that general methods that leverage
computation and Moore's Law are the most effective for advancing AI research.

In the iceberg of AI technology, while LLMs are at the top, ASML is at the murky depths.

It has kept Moore's Law alive.

9/9

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More from @deedydas

Jun 2
The BEST AI report in the world just dropped and I read all 340 pages so you don't have to.

Must-read for frankly, everybody. Here are the top 20 learnings from the report:

ChatGPT has 8x'd growth in 2.5yrs to 800M monthly users.
India at 14% is the #1 largest user base.

1/20 Image
ChatGPT hit 1B searches a day 5.5x quicker than Google.

2/20 Image
3. ChatGPT users spend 3x more time a day on the app than 21mos ago.

3/20 Image
Read 21 tweets
Jun 1
If these 3 Japanese companies you've never heard of went down, all modern digital infrastructure (and every AI breakthrough) would grind to a halt.

Here's the story of JSR, Tokyo Ohka Kogyo (TOK) and Shin-Etsu, the most important companies you've never heard of...

1/7 Image
These 3 control 80% of the global EUV photoresist market.

Photoresists are exotic light-sensitive chemicals that enable the patterning of circuits on silicon wafers when UV or EUV light hits these materials through a mask.

How did they achieve this dominance?

2/7 Image
The chemistry is insanely complex.

They use ~30-50 proprietary compounds and 1000s of patents. It responds to extreme ultraviolet light at 13.5nm wavelengths.
The patterns are smaller than DNA strands and require decades of expertise.

How did they get there?

3/7
Read 7 tweets
May 21
🚨 This was the BEST Google I/O that I can remember.

Google launched over 12 different insane things.

Here is every single one of the launches and the best tweets about them:

1/12
The future of building software.

LLMs are pretty good at generating code, but they're slow. Gemini Diffusion is 10-15x faster than autoregressive models by using diffusion, which used to be for images. This is the 2nd model after Mercury Small to show this.

2/12
Bringing realtime translation with multimodal AI to Google Meet.

No more language barriers ever again.

3/12
Read 12 tweets
May 14
🚨 BigTech jobs have ZERO growth in the last 3yrs.

Google, Microsoft, Apple, Tesla, Meta, Nvidia and Palantir - the biggest tech employers have collectively stagnated headcount, data shows.

This is why CS majors can’t get jobs. Bigtech hypergrowth era is over.

Here's why:

1/4 Image
— They overhired in the pandemic (2020-2022) during zero interest rates
— Revenue growth of several consumer software products peaked in the pandemic but slowed after it was over
— Higher interest rates force CFOs to juice operating margin

2/4
— Cost of capital shot up and many had to place high capex bets in gen AI infra (chips)
— AI productivity gains

Is this the new normal? Does Microsoft having 400k vs 200k people actually 2x the business?

Maybe or maybe not.

3/4
Read 4 tweets
Mar 28
Compilation of 16 USEFUL things people did with GPT 4o native image generation can do (aside from Ghibli images) in the last 48hrs!

They include
— Full video movies / podcasts / ads
— UI design loop
— 3D model gen

Full Lord of the Rings in Ghibli

1/16
Videos in different animation styles

2/16
Read 17 tweets
Mar 15
Google's new AI image editing model is going to kill 99% of Photoshop.

By just describing your image edit in English, you can:
— get passport picture from photo
— make me look like I'm on my way to work
— decorate this house for me
— put these clothes on me
— make a map in a game from these sprites
— animate this sprite
— combine all these faces together
— show this model holding my product
— make me bald / give me hair

You can access Gemini Flash 2.0 experimental on Google AI studio.

This is a 1B+ user product waiting to happen.
1. make me look like I'm on my way to work
Read 11 tweets

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