In JSON, it supports data types, and helps the same data to be nested directly:

{
"id": 1,
"name": "Alice",
"orders": ["Laptop", "Mouse"]
}

That’s why APIs prefer JSON, it naturally handles relationships like customers → orders or users → addresses.

To simulate relationships, you split data into files and connect them with IDs.

customers.csv
1,Alice
2,Bob

orders.csv
101,1,Laptop
102,1,Mouse
103,2,Keyboard

Alice’s orders are linked because they share customer_id = 1

Analogy:

Think of training an AI like teaching a student:

🏫 Training: You teach the student how to solve math problems (e.g., recognize cats in pictures).

✍️ Inference: The student is now tested with new questions — they apply what they learned to give you answers (e.g., “Yes, that’s a cat”).

✅ PS5 GPU: ~10 TFLOPs 🎮
✅ NVIDIA RTX 4090: ~82 TFLOPs 🎨🖥️
✅ Frontier Supercomputer: ~1.1 ExaFLOPs (1,100,000 TFLOPs) 🌌🚀

Analogy: If a 1 TFLOP CPU was a worker doing 1 billion calculations per second, a 1 ExaFLOP supercomputer would be a city of 1 million workers doing the same.

Cores are groups of transistors working together to process data. Think of each core as a worker in a factory handling tasks.

Threads are instructions that a core can handle at once. A single core can switch between multiple threads, like a worker multitasking between two tasks.

🔴 More Memory Needed 💾 – Programs/files take up more space since every number/character gets bigger.

⚖️ Faster or Slower? ⏩⏳ – Could speed up large number processing but also increase memory/bandwidth use.

Would it be worth the change? 🤔

🧠 Why the gap?
Hardware limitations – Motherboards and CPUs physically can’t fit/address that much RAM.
OS constraints – Operating systems often restrict RAM usage based on version/edition.
Cost – RAM is expensive and not typically installed beyond practical need.

Windows 10/11 Pro: up to 2 TB RAM
macOS (Apple Silicon): currently supports up to 192 GB RAM
Linux (with proper kernel and configs): can support hundreds of TBs, depending on the architecture.

Practical Limits (as of now):
Most consumer operating systems cap it around 128 GB to 2 TB. High-end servers and data centers may support 4 TB to 6 TB or more.

So, while cores are made up of transistors, they are more like units of computation (workers) that utilize those transistors to perform tasks. A higher number of cores means the processor can handle more tasks at once!