alt Hacker NewsNAND-16: a computer built from 277,248 NAND gates
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What's the point if you didn't do it yourself?
Feels like this https://www.youtube.com/watch?v=gId2HsHvSgs
I was about to say that's a whole lot of gates for not a lot of computer, but then saw that rom and ram are also an array of nand gates.
If you have not tried panning the camera and zooming in to one of the chips, you are missing out.
Bravo to the author. This is inspiring work.
Sorry to be pedantic but...every "boolean" logic gate can be made out of NAND gates pretty trivially (XOR too for that matter). So you just have to design a computer from logic gates and then decompose each one into NANDs.
"I made a computer out of n logic gates" doesn't sound as cool I guess?
Granted I am criticizing the concept and post title, not the execution.
This is pretty sad. Seeing this a couple of years ago would be mind blowing. An impressive technical feat by someone with grit and resilience to painstakingly build this from scratch.
Today? Meh.
First thing I tried was "double-click: fly to this latch". Didn't work. AI slop?
edit: press tab first.
A nand gate takes 2 transistors. So 554,000 transistors if this were manufactured in a physical device.
By way of comparison, the Intel i386 had 275,000 transistors.
Impressed by visuals working so smoothly on mobile
I mean if this was someone taking Nand2Tetris several steps further it would be impressive.
claude "create a NAND gate-based computer, giving it a crappy web page"OHH my god this is soo awesome, I wonder how people build such things.
I think the takeaway is that we have to think bigger, much bigger, now that AI coding is essentially "solved". Anyone can "write" an ARM simulator now, so that can't be the pinnacle of engineering. I'm thinking about buildings that couldn't be built (reasonably) by one person.
I'll give an example of what I'm working on. There's a model for segmenting organs from CT scans. There's another model for calculating radial diameters of blood vessels from CT scans. You can combine the two and approximate how much blood flow each organ gets based on its segmented volume and the sum total radial diameter of vessels feeding it. You can then render all of that in an app that shows perfusion to that organ.
The idea is to combine these models to extract every ounce of usable information from a CT scan that might be useful for procedural planning (I'm an interventional radiologist). While each algorithm would take weeks/months to implement, Opus 5.5 can do them in minutes to hours and then stitch them together. The results thus far have been better than anything I've seen.