DEV Community: Jasim Alam

𝗛𝗼𝘄 𝗗𝗼𝗲𝘀 𝗔𝗜 𝗕𝗲𝗰𝗮𝗺𝗲 𝗦𝗼 𝗚𝗼𝗼𝗱?

Jasim Alam — Mon, 21 Jul 2025 06:09:58 +0000

How LLM like ChatGPT reads between the lines like a mind reader?

Picture this: “𝘛𝘩𝘦 𝘤𝘢𝘵 𝘴𝘢𝘵 𝘰𝘯 𝘵𝘩𝘦 𝘮𝘢𝘵 𝘣𝘦𝘤𝘢𝘶𝘴𝘦 𝘪𝘵 𝘸𝘢𝘴 𝘵𝘪𝘳𝘦𝘥.”

You instantly know “it” = the cat.

But for a machine? That’s pure magic.

Meet attention — the breakthrough that gave AI its superpower of understanding context.

𝗛𝗲𝗿𝗲’𝘀 𝗵𝗼𝘄 𝘁𝗵𝗲 𝗺𝗮𝗴𝗶𝗰 𝘄𝗼𝗿𝗸𝘀:

Think of AI like a detective examining evidence. For every word, it asks:

“𝘞𝘩𝘪𝘤𝘩 𝘤𝘭𝘶𝘦𝘴 𝘪𝘯 𝘵𝘩𝘪𝘴 𝘴𝘦𝘯𝘵𝘦𝘯𝘤𝘦 𝘩𝘦𝘭𝘱 𝘮𝘦 𝘤𝘳𝘢𝘤𝘬 𝘵𝘩𝘦 𝘤𝘢𝘴𝘦?”

The model becomes a master multitasker, simultaneously:

Querying: “What am I trying to solve right now?”
️ Keying: “What secrets does each word hold?”
Valuing: “Which insights should I actually use?”

Result? The AI gives “cat” a spotlight while “mat” fades to background lighting when decoding “it.”

𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗰𝗵𝗮𝗻𝗴𝗲𝘀 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴:

This isn’t just clever programming — it’s a cognitive revolution. AI can now:

Jump across entire documents to connect ideas
Understand sarcasm and tone
Translate languages while preserving meaning
Write code that actually makes sense
Hold conversations that feel genuinely human

𝗧𝗵𝗲 𝗺𝗶𝗻𝗱-𝗯𝗹𝗼𝘄𝗶𝗻𝗴 𝗽𝗮𝗿𝘁?

This breakthrough came from a single 2017 paper: “Attention Is All You Need”

Total transformation of how machines understand us.

This attention breakthrough now powers everything from ChatGPT, Google Translate to the entire modern AI ecosystem.

Note: Originally Published On Medium

Auto Rotation of PM2 log

Jasim Alam — Mon, 21 Jul 2025 06:05:55 +0000

PM2 by default stdout to log directory, default ($HOME/.pm2/logs). Over time this can be huge unless rotated.

Below process uses npm module to handle the rotation.

Install the pm2-logrotate module

$ pm2 install pm2-logrotate
[PM2][Module] Installing NPM pm2-logrotate module
[PM2][Module] Calling [NPM] to install pm2-logrotate …
[PM2][Module] Module downloaded
[PM2][WARN] Applications pm2-logrotate not running, starting…
[PM2] App [pm2-logrotate] launched (1 instances)

Set max size of the log

$ pm2 set pm2-logrotate:max_size 50M
[PM2] Module pm2-logrotate restarted
[PM2] Setting changed
Module: pm2-logrotate
$ pm2 set pm2-logrotate:max_size 50M
$ pm2 set pm2-logrotate:retain 20
$ pm2 set pm2-logrotate:compress true
$ pm2 set pm2-logrotate:dateFormat YYYY-MM-DD_HH-mm-ss
$ pm2 set pm2-logrotate:workerInterval 30
$ pm2 set pm2-logrotate:rotateInterval 0 0 * * *
$ pm2 set pm2-logrotate:rotateModule true

set log rotation interval in cron format.

$ pm2 set pm2-logrotate:rotateInterval '0 0 * * *'
[PM2] Module pm2-logrotate restarted
[PM2] Setting changed
Module: pm2-logrotate
$ pm2 set pm2-logrotate:max_size 50M
$ pm2 set pm2-logrotate:retain 20
$ pm2 set pm2-logrotate:compress true
$ pm2 set pm2-logrotate:dateFormat YYYY-MM-DD_HH-mm-ss
$ pm2 set pm2-logrotate:workerInterval 30
$ pm2 set pm2-logrotate:rotateInterval 0 0 * * *
$ pm2 set pm2-logrotate:rotateModule true

change the retention time

$ pm2 set pm2-logrotate:retain 10
[PM2] Module pm2-logrotate restarted
[PM2] Setting changed
Module: pm2-logrotate
$ pm2 set pm2-logrotate:max_size 50M
$ pm2 set pm2-logrotate:retain 10
$ pm2 set pm2-logrotate:compress true
$ pm2 set pm2-logrotate:dateFormat YYYY-MM-DD_HH-mm-ss
$ pm2 set pm2-logrotate:workerInterval 30
$ pm2 set pm2-logrotate:rotateInterval 0 0 * * *
$ pm2 set pm2-logrotate:rotateModule true

Note: Originally published on Medium

Types of Machine Learning - Explained Simply

Jasim Alam — Mon, 21 Jul 2025 05:54:34 +0000

Supervised Learning : Learning with a teacher

Imagine a student learning from past exams.
The machine gets both the questions and the correct answers.
Over time, it learns the pattern.

Real-Life Examples:

Spam Email Detection
House Price Prediction
Disease Diagnosis
Stock Market Forecasting
Weather Predictions

Example:

You show a computer 1000 labeled images:

Later, it can say, “That’s a cat!” when shown a new image.

Unsupervised Learning : Learning without a teacher

Like a child sorting toys by shape or color without knowing their names.

The machine explores data without labels and discovers hidden patterns.

Real-Life Examples:

Customer Segmentation for targeted ads
Market Basket Analysis (product recommendations)
Fraud and Anomaly Detection

Example:

Give it 1000 fruit pictures — no names. It might group them like:

Round and red fruits
Long and yellow fruits
Small and purple fruits

It doesn’t know the fruit names but it finds structure.

Reinforcement Learning : Learning by doing

Like training a pet with rewards and corrections.

The machine (called an agent) tries different actions, gets rewards or penalties, and learns what works best over time.

Real-Life Examples:

Self-driving Cars
Game AI (Chess, Go, video games)
Robotics and Automation
Stock Trading Bots

Example:

A robot tries to walk.
Falls result in no reward.
Moves forward result in a reward.
It learns to stay balanced and move smart.