The Machine I Never Saw
Two weeks on an HP ZGX Fury I never saw: the big machine that lost, the favorite idea that lost too, and the one rule that let me be reckless.
For two weeks in September I worked on an HP ZGX Fury, a desk-side machine built for serious AI work, and I never once saw it.
HP lent me time on it through its Lighthouse evaluation program. It never came near my desk. To me it was an IP address at the far end of an SSH session, a blinking cursor that could hold a trillion-parameter model in its memory and serve it.
I wrote two long technical papers about what happened there, full of tables and receipts. This is the other version, for people who will never open a CUDA file and should not have to.
The big machine lost
On my last morning with it, I ran the same job on two computers: the Fury, and the workstation under my own desk. The Fury is the far bigger machine. My workstation won.
That is the moment you either blame the hardware or go look in the mirror. I put five timestamps into my code, the dumbest instrument there is. The GPU was barely involved. Most of the time went to my own software building thousands of little text records, then throwing nearly all of them away. The expensive machine was waiting on me.
By the end of that day the same job ran in under a millisecond. The hardware never changed. The lesson was the oldest one in engineering: measure before you guess, because your guess is usually about someone else’s fault.
My favorite idea lost too
Before I touched the machine, I wrote down what I expected to happen. Every prediction, with a date on it, before the first run. Scientists call this pre-registration. I call it taking away my own escape hatches.
My favorite prediction was a clever caching idea, the kind you fall in love with in the shower. It edged out the simplest approach by a hair and lost clearly to another one. The gap I predicted never showed up.
What surprised me is that it did not sting much. Because the bet was written down first, there was nothing to argue about. I could not quietly move the goalposts, so I did not waste a week trying. The idea lost, and I got the week back.
The rule that let me be reckless
The simulation work ran on one rule: the answer is not allowed to change. Not close enough. The same bytes, every time, checked by a machine.
That sounds like a constraint. It was the opposite. With a check like that waiting at the end, I could rip out the core of the engine at four in the afternoon and try something strange. If I broke anything, the check went red within seconds. It did go red once, and I fixed it before a single number left the building.
Most people think rules slow you down. The right rule tells you instantly when you are wrong, and that is exactly what lets you go fast.
What I am taking home
The trillion-parameter model ran on one box. That was the headline I wanted, and it held. But the things I will remember are smaller: the big machine losing to a desktop because of my own code, my best idea losing to a better one, and one unbreakable rule that made a reckless day feel safe.
If you build things, the two technical papers have every number, the scripts, and a list of what I got wrong:
If you do not build things, here is the short version. Write down your bet before you start. Measure before you blame. And find the one rule that tells you, right away, when you are wrong.
HP provided two weeks of remote access to an HP ZGX Fury at no cost through its Lighthouse evaluation program. The opinions here are my own.