⭕ PREDICTION

Outputs probability scores for every possible next word. Temperature controls randomness: low = predictable, high = creative.

6 steps and Billions of parameters
That's what runs every time you hit "send".

⭕ FEED-FORWARD

Each token processes through neural layers independently. Non-linear functions capture complex patterns beyond word relationships.

⭕ NORMALIZATION

Keeps data stable flowing through layers. Residual connections prevent information loss across deep networks.

⭕ EMBEDDING

Those token numbers become vectors in high-dimensional space.Similar words sit close together

⭕ ATTENTION

The model figures out which words matter most for context. Every word can "talk" to every other word

That’s the point.
FOMO is engineered.

Dropout founders go viral.
Teen millionaires trend.
You're seeing the top 1% on loop.

Don’t quit College
Don’t ignore AI.
Do both.

Learn AI. Build while you study.
Waiting is the only thing you can’t afford.

“you need more parameters to get smarter AI.”

🔺MLM – masked language models
guess the missing words, understand both sides.

🔺LAM – large action models
think and do—code, automate, execute.

🔺SAM – segment anything models
pixel-perfect vision understanding.

every model has its lane.
pick right, perform better

🔺LCM – large concept models
see the meaning, not just the words.

🔺VLM – vision-language models
mix image + text for smarter perception.

🔺SLM – small language models
tiny, fast, edge-ready.

🔺MOE – mixture of experts
only the needed experts wake up per task.

→ Automatic retries -
Recovers from failures without losing progress

→ Checkpoints -
Picks up where it left off instead of restarting

It's the control plane that makes agents actually work in production:

→ Stateful execution -
Remembers context across every step

→ Graph-based flow -
Handles branching logic, not just linear chains