AI 101 - SiliconNoon (Page 2)

The Stack

AI 101 — What is CUDA?

CUDA is the software layer that lets ordinary programs run on NVIDIA's graphics chips — and it is the foundation nearly all modern AI is built on. Short for Compute Unified Device Architecture, it first shipped on February 16, 2007, and it turned graphics cards — machines designed to draw video games — into general-purpose computers that any developer could program. Before CUDA, using a graphics chip for serious math meant writing code in the chip's own graphics language, in fragments, with lit

The Frontier

AI 101 — What is overfitting?

Overfitting is when a model learns its training data too well — it gets the examples it has already seen almost perfect, then performs worse on anything new. Since the entire job of a model is to handle cases nobody showed it, overfitting is the most common way an AI system looks brilliant in a demo and disappoints in production. The term shows up in almost every model release, fine-tuning guide and benchmark write-up, and it is rarely explained. The short version: a model is only worth anythin

The Frontier

AI 101 — What is reinforcement learning?

Reinforcement learning is how a machine learns by trial and error: it tries things, notices which attempts earned a reward, and drifts toward the behaviour that earns more of it. There is no answer key involved. In the supervised learning most people picture, someone hands the model millions of labelled examples and it learns to copy them. In reinforcement learning, nobody says what the right move is — the machine acts, gets a number back telling it how well that went, and adjusts. The classic

The Frontier

AI 101 — What is LLM-as-a-judge?

If you read a week of AI news, you'll notice almost nobody grades models by hand any more. When a lab says its new model is better at writing, summarising or handling customers, the number usually came from another AI. An LLM judge is a language model used to grade the work of another model — or of your own AI feature — when no piece of code can decide whether the answer was good. The industry term is LLM-as-a-judge, and the job is simple to state: read a question and an answer, then return a s

The Stack

AI 101 — What is prompt caching?

Prompt caching is a way to make an AI model skip re-reading text it has already read. The provider saves its internal working state for the opening section of your prompt, and the next request that starts with the exact same text picks up from there — cheaper and faster. It sounds like a developer-housekeeping detail. It is now one of the largest line items in how AI gets priced, and one of the most common ways a working product quietly runs up a bill. Why it matters right now On September 2

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AI 101 — What is federated learning?

Federated learning is a way to train one shared AI model across thousands of devices or organisations without ever collecting their data in one place — each participant trains a copy on data it already holds, and only a summary of what that training learned travels back. The name comes from the word "federation": a group of independent members cooperating under one agreed protocol while each keeps its own affairs. The data stays where it lives. The learning moves. Why it matters right now Tw

The Guardrails

AI 101 — What is AI alignment?

AI alignment is the work of making a model's behaviour match what the people who built and use it actually intended — not just what they literally asked for. The one-sentence version hides the hard part. Asking is easy. Intending is not. When you tell an assistant to "get the numbers," you mean real numbers from a real source, quickly, without borrowing anything that isn't yours. Every one of those assumptions is something you never said out loud. Alignment is the discipline of closing that gap

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AI 101 — What is a TPU?

A TPU — Tensor Processing Unit — is a computer chip Google built to do one thing: the enormous matrix multiplications that neural networks run on, done faster and with less electricity than a general-purpose chip can manage. It is the silicon underneath Search, Translate and Gemini, it is what Google rents to other AI companies through its cloud, and in 2026 it became collateral in some of the largest loans the AI buildout has seen. If you have read about a "$22 billion loan" or "a million TPUs"

The Guardrails

AI 101 — What is mechanistic interpretability?

Mechanistic interpretability is the work of reverse-engineering what actually happens inside a neural network — finding the specific internal parts responsible for a specific answer, rather than inferring everything from the model's behaviour. "Mechanistic" is the load-bearing word: the deliverable is a mechanism, a step-by-step account of the computation, not a description of what the model tends to do. Why it matters right now The cheapest way anyone audits a frontier model is by reading it

The Frontier

AI 101 — What is multimodal AI?

Multimodal AI is a model that handles more than one kind of input — text, images, audio, video — inside the same system, rather than one model per sense stitched together. "Modality" is just the academic word for a channel of information. Text is a modality. A photograph is a modality. A voice recording is a modality. Multimodal AI reads more than one of them at once and reasons across them. That last part is the whole trick. You have had software that reads images for years — optical character

The Frontier

AI 101 — AI vs machine learning: what's the difference?

Artificial intelligence is the goal — getting a machine to do things we would call intelligent — and machine learning is the technique the field now overwhelmingly uses to get there: instead of a programmer writing the rules, the system is handed examples and adjusts itself until its answers get better. The two terms get swapped for each other in almost every story you read, including ours. That is mostly harmless, and occasionally it hides the interesting part. When Justin Fanelli, the US Navy

The Guardrails

AI 101 — What is a deepfake?

A deepfake is video, audio, or image content in which AI makes a real, identifiable person appear to say or do something they never did. The name is short for "deep learning" plus "fake," and the second half of the definition is the part that matters: a deepfake is not simply AI-generated media. It is a real person placed in a false situation — your face, your voice, a chief financial officer's on a video call. Why it matters right now. The word has been doing heavy lifting in our coverage all

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