Preview, beta, GA: how AI product launches actually work
Waitlists, research previews, staged rollouts and general availability: a guide to the stages every AI product goes through and what each one means for users.
AI Desk3 min read
Tag
#Explainer
Every The Latent Daily story, tool, model and resource tagged “Explainer”.
16 items
Beginner's CornerGuide
What is generative AI? Text, images and audio explained simply
A plain-English introduction to generative AI: how chatbots and image generators create new content, what they are good at, and the mistakes to watch for.
AI Desk3 min read
How transformers work, explained without the math
The transformer architecture behind ChatGPT, Claude and Gemini, explained step by step: tokens, embeddings, attention and why it changed AI in 2017.
AI Desk3 min read
How diffusion models turn noise into images
Stable Diffusion, FLUX and most image generators rely on diffusion. A clear explanation of forward noising, learned denoising, text guidance and latent space.
AI Desk3 min read
20 AI terms everyone should know, explained in one line each
From tokens and parameters to RAG, fine-tuning and hallucinations: a quick, plain-English glossary of the AI words you will meet in every news story.
AI Desk3 min read
Parameters, tokens, context windows: the numbers in AI announcements explained
What "405B parameters", "1M-token context" and "$3 per million tokens" really mean, and which numbers actually matter when you compare AI models.
AI Desk3 min read
Seven common myths about AI, debunked
No, AI doesn't look things up in a database, and no, bigger is not always better. Seven widespread misconceptions about today's AI, and what is actually true.
AI Desk3 min read
A short history of AI: from Turing to transformers
Seventy-five years of artificial intelligence in one read: the Dartmouth workshop, two AI winters, the deep learning breakthrough and the arrival of ChatGPT.
AI Desk3 min read
How AI benchmarks work — and why they keep "saturating"
MMLU, SWE-bench, ARC and LMArena: how AI benchmarks are built, what their scores really measure, why models quickly max them out and how to read leaderboards.
AI Desk4 min read
How AI pricing works: subscriptions, tokens and credits explained
Why AI tools charge per seat, per token or per credit, how input and output tokens are billed, and how to estimate what an AI feature or subscription will really cost.
AI Desk4 min read
What are AI agents? How they plan, use tools and take actions
AI agents go beyond chat: they plan, call tools, browse and act toward a goal. How the agent loop works, the main design patterns, real uses and the risks.
AI Desk3 min read
Knowledge distillation explained: how small AI models learn from big ones
Distillation trains a compact "student" model to imitate a large "teacher". How it works, why it powers today's small models, and its legal and quality limits.
AI Desk3 min read
Local & On-device AIGuide
Quantization explained: how big AI models run on small hardware
Quantization shrinks AI models by storing weights with fewer bits. How 8-bit and 4-bit formats work, GGUF, GPTQ and AWQ, and the quality trade-offs to expect.
AI Desk3 min read
Algorithmic bias explained: how AI systems end up unfair
Where AI bias comes from — data, labels, design and deployment — with landmark examples such as Gender Shades, and the main ways to measure and reduce it.
AI Desk3 min read