CPU, RAM, Storage, Motherboard, and why AI needs ALL the GPUs.

How your message travels through switches, routers, and undersea cables to reach ChatGPT.

Type a number and see it in binary — or type binary and see the decimal:

- [RapidTables Binary Converter](https://www.rapidtables.com/convert/number/decimal-to-binary.html) — quick conversion both ways

- [CS Unplugged Binary Cards](https://www.csfieldguide.org.nz/en/interactives/binary-cards/) — the dot card activity from class, but online

- [Firia Labs Network Simulator](https://netsim.erinn.io/) — build a virtual network with switches and routers

- [Subnet Game](https://www.subnetting.net/) — test your networking knowledge (extension challenge)

A modern Intel Core i9 processor. The silver square is the heat spreader — underneath are billions of transistors smaller than a virus.

DDR memory sticks. These plug into the slots on the motherboard. The gold pins are the electrical contacts. More sticks = more "desk space" for your apps.

**SSD (Solid State Drive)** — No moving parts. Data stored on memory chips. Fast, silent, expensive.

The NVIDIA RTX 5060 Ti — a modern gaming graphics card. Those two black circles are fans that cool the chip during heavy work. AI companies buy millions of these (or the more powerful server versions).

Everything plugs into this board. You can see the CPU socket, RAM slots, PCIe slots (for the GPU), and hundreds of tiny traces carrying data between components.

Modern CPUs use 3-nanometre transistors. A human hair is about 80,000 nanometres wide. You could fit roughly 26,000 transistors across a single hair. The Apple M4 chip has 28 billion of them.

Because transistors are switches — they're either ON (1) or OFF (0). It's easier to build reliable hardware with two states than ten. Everything else (text, images, video, AI) is built on top of these two states.

About 200,000 km/s — roughly two-thirds the speed of light. A message from Melbourne to London (17,000 km) takes about 85 milliseconds through undersea cables. That's faster than you can blink.

Thousands of server racks, each holding dozens of computers. Google has over 30 data centres worldwide. A single data centre can use as much electricity as a small city. Most of that power goes to cooling — the chips generate enormous heat.

AI training needs thousands of GPUs running together for weeks or months. Companies like OpenAI, Google, and Meta are buying every GPU they can get. NVIDIA's revenue tripled because of AI demand. The same chip architecture (CUDA cores) that makes games look good also makes AI calculations fast.

|--------|---------|

| `00001101` | 13 |

| `01010101` | 85 |

| `11000011` | 195 |

| `10000001` | 129 |

|---------|--------|

| 25 | `00011001` |

| 100 | `01100100` |

| 42 | `00101010` |

| 200 | `11001000` |

**Check your working:** For each 1 in the binary number, add up the place value. For decimal to binary, find the biggest power of 2 that fits, subtract, repeat.

---

Wondering what your child is learning? Here's a quick summary:

- Students are exploring **how computers work** — opening old laptops, identifying components, understanding what each part does

- They're learning **binary** — the number system computers use (just 0s and 1s)

- They're building **networks** — connecting devices with real cables and switches

- Everything connects to **AI** — helping students understand that AI runs on the same hardware they're studying

This aligns with the [Victorian Curriculum: Digital Technologies](https://victoriancurriculum.vcaa.vic.edu.au/technologies/digital-technologies/introduction/rationale-and-aims) for Years 7-8.

---