const ai = new Model();
await model.train(data);
import torch
def forward(self, x):
npm run deploy
git push origin main
loss.backward()
SELECT * FROM neurons
docker build -t ai .
export default App;
fn main() -> Result<>
pipe = pipeline('text')
kubectl apply -f pod.yml
console.log('hello AI')
{ }
</>
Py
TS
JS
=>
AI
Go
Rs
C#
++
λ
∑
#!
>>
SQL
function predict(input) {
return model.run(input);
}
class NeuralNet:
def __init__(self):
self.layers = []
const config = {
epochs: 100,
lr: 0.001,
};
impl Transformer {
fn attention(&self)
-> Tensor { }
}
{ }
</>
( )=>
One Man Crew
Exploring the frontier of AI

Build. Train. Deploy.

Deep dives into AI, large language models, and intelligent systems. From neural architectures to production ML pipelines — one engineer's journey through the age of AI.

ai-workstation — ~/one-man-crew
GPU: Active
Explore Latest Research
Latest from the lab

Recent Explorations

Deep dives into AI systems, neural architectures, and the engineering behind intelligent software.

Powered by neural networks & caffeine. One Man Crew DevLog © 2026