AI/ML Engineer · AI@IllinoisTech

Kaung Myat Naing

In the age of AI,if you can imagine it, you can build it.

Currently building:

Step through

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01 / The introduction

Mandalay Palace

02 / WHERE IT BEGAN

A small beginning. A big world.

I grew up in Mandalay, Myanmar, with a curiosity bigger than the world I knew.

At 17, I left home to discover what was possible. I didn't know exactly where that journey would lead, but I knew I wanted to build something meaningful.

EVERY JOURNEY BEGINS SOMEWHERE.

Mandalay
21.96° N / 96.09° E

Board

03 / BETWEEN TWO HOMES

Somewhere between fear and possibility.

I boarded a plane with two suitcases, a thousand questions, and a dream bigger than I could explain.

I was leaving everything I knew, chasing a future I hadn't figured out yet.

MANDALAY → CHICAGO

ONE FLIGHT. A WHOLE NEW CHAPTER.

Look out

Step inside

04 / THE NEXT CHAPTER

A new city. A bigger dream.

I arrived in Chicago chasing possibilities. What I found was a place to turn curiosity into something real.

From writing my first lines of code to building AI systems, every step has brought me closer to the future I want to create.

FAR FROM HOME. CLOSER TO MY DREAMS.

Chicago
41.88° N / 87.63° W

05 / AFTER HOURS

Life beyond the code.

Games to play. Movies to watch. Songs on repeat. Food to try. And a hundred little ideas waiting to be built.

I guess I'm just someone who loves exploring, whether it's a new place, a new flavor, or a new possibility.

WELCOME TO MY LITTLE CORNER OF THE WORLD.

> type in

import torch

# Ask. Build. Test. Repeat.
model.train()
for inputs, targets in loader:
    optimizer.zero_grad()
    predictions = model(inputs)
    loss = criterion(predictions, targets)
    loss.backward()
    optimizer.step()

import torch

# Ask. Build. Test. Repeat.
model.train()
for inputs, targets in loader:
    optimizer.zero_grad()
    predictions = model(inputs)
    loss = criterion(predictions, targets)
    loss.backward()
    optimizer.step()

06 / WHY AI

A dream that never left.

As a kid, I watched sci-fi movies and imagined a world where intelligent machines weren't just fiction. I dreamed of having my own JARVIS, a companion that could understand me, think alongside me, and help turn ideas into reality.

I never thought I'd actually get the chance to help build something like it.

But the more I explore AI, the more I realize how much is still possible. What excites me most isn't how far we've come, but how much remains undiscovered.

That's why I'm here. To explore the frontiers of intelligence, contribute to AGI, and help make the future I once imagined real.

I DON'T WANT TO JUST IMAGINE THE FUTURE. I WANT TO BUILD IT.

nick@chicago / build

import torch

# Ask. Build. Test. Repeat.
model.train()
for inputs, targets in loader:
    optimizer.zero_grad()
    predictions = model(inputs)
    loss = criterion(predictions, targets)
    loss.backward()
    optimizer.step()

query, retrieve, reason, build, evaluate, iterate

> keep goingClick, or keep scrolling

07 / Change the lens

From city lights
to lines of code.

Somewhere along the way,

the city lights turned into code.

build.log Illustrative log

TypeError: Cannot read properties of undefined (reading 'grad')
    at step (train.py:18)
CUDA out of memory. Tried to allocate 512 MiB
loss: nan
Segmentation fault
retrying...
build passed

> enter