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Education

AI explainers, primers, and practical guides. Concepts made clear for curious readers who want to understand the technology, not just keep up with the news cycle.

Diagram contrasting total parameters with active parameters in a mixture-of-experts AI model.

What is mixture-of-experts? The architecture behind cheaper trillion-parameter AI

Mixture-of-experts is how a 671-billion-parameter model can cost less per token than a 70-billion-parameter one. A plain-English guide to MoE, active vs total parameters, routers and experts, and why open-weights frontier labs picked the architecture first.

Three families of AI evals shown as comparison cards: capability, safety, and production.

What are AI evals? The work that decides whether a model ships

Evals are how labs decide a model is ready to ship — and how buyers decide which model to buy. A plain-English guide to capability, safety, and production evals, the LLM-as-a-judge pattern, and what changed in 2026.

An editorial infographic showing generated examples moving through seed, generate, filter, evaluate, and train stages.

What is synthetic data? The training material AI is starting to make for itself

Synthetic data is generated training material. It can teach models faster, protect privacy, and also cause model collapse when used badly. Here is the practical version.

The official Nightshade illustration of AI training data poisoning: a model trained on subtly modified images learns to associate words with wrong concepts.

What is dataset poisoning? The supply-chain risk inside every model

Dataset poisoning happens when AI training data is deliberately contaminated. Here's what the research proves, what may be happening in practice, and what remains uncertain.

Close-up macro photograph of an HBM2 DRAM die on a Radeon RX Vega 64 GPU — the actual silicon that stores the bytes a model has to load and reload during inference.

What is HBM memory, and why does AI need so much of it?

HBM is the high-bandwidth memory glued to every modern AI accelerator — and the single component most likely to be the bottleneck the next time someone says 'we need more GPUs.'

The official Model Context Protocol simple diagram: AI applications acting as MCP hosts connect through MCP clients to local and remote MCP servers, with each server exposing tools, resources

What is MCP? The protocol that lets AI agents use your tools

MCP is Anthropic's open standard for connecting AI assistants to external data and tools. Here's what it does, what it leaves to implementers, and what it changes for developers.

Contrastive language-image pretraining diagram (CLIP): image encoder and text encoder trained jointly so matching pairs cluster in a shared embedding space.

What 'multimodal' really means in consumer AI apps

Every AI assistant launch carries the word 'multimodal.' Here's what it actually changes about the experience, where it works well, and where it still embarrasses itself.