Late At night, I dream of embeddings, matrix multiplication, and implementations of theory of mind. Sometimes I even dream of red-hot sewage-cooled GPUs that reveal hidden assembly code routines on the heat sink

My passion for machine learning is such that my tinnitus has been replaced by server fan noise and CMOS beeps. My internal monologue is implemented in type-hinted Python.

You caught me! When I'm not busy fixing toilets and unclogging drains, I'm secretly moonlighting as a machine learning engineer —-Why, you ask?

To strike revenge into the hearts of all those politicians and uppity techies who told me and my fun-loving, abstraction-hating hooligans that we simply needed to "learn to code"

Well Now I’m re writing everything in cobol, just to flex. Like I’m rewriting South America in Cobol, we out here stunting hard.

while the techies are sipping their pumpkin mochas while dreaming about the elegant workflow (slack flow) of incorporating 4th monitor. day after Day passes along as they hack away at 50 WPM in emoji-drenched Slack groups making backslash API calls to build a bear.

Well bro: I'm donning my steel-toed boots and a Cat5e copper-reinforced belt and showing them what a real day's work looks like, I ain’t got no slack, not even in my sewage stained Dickies workplace pants.

I’m passionate about the low level math of AGI and also about eliminating midwit AI doomer vibes throughout less wrong blog and HN. I will bring aligned AGI to the people. —— You will never again have to read another lesswrong blog post along the lines of “moores law, matrix multiplication and the panic attack I had after realizing even GPT-2 is already better than me at backhanded displays of intelligence via Reddit arguments”.

With every leaky faucet I fix, I'm secretly honing my skills and plotting my revenge. I’m keeping mya pipes ah pressured!!!.

Now, let me show you my COBOL skills:/

IDENTIFICATION DIVISION.

PROGRAM-ID. NEURAL-NETWORK.

DATA DIVISION.

WORKING-STORAGE SECTION.

01 INPUT-NEURONS PIC 99 VALUE 784.

01 HIDDEN-NEURONS PIC 99 VALUE 15.

01 OUTPUT-NEURONS PIC 99 VALUE 10.

01 INPUTS OCCURS 0 TO 783 TIMES DEPENDING ON INPUT-NEURONS PIC 9(3)V9(2).

01 HIDDEN OCCURS 0 TO 14 TIMES DEPENDING ON HIDDEN-NEURONS PIC 9(3)V9(2).

01 OUTPUT OCCURS 0 TO 9 TIMES DEPENDING ON OUTPUT-NEURONS PIC 9(3)V9(2).

01 WEIGHT1 OCCURS INPUT-NEURONS DEPENDING ON HIDDEN-NEURONS PIC 9(3)V9(2).

01 BIAS1 OCCURS HIDDEN-NEURONS PIC 9(3)V9(2).

//)(

JK