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
Page 2 of 9
Articles & Analysis — Page 2
Deep dives, analysis, features and opinion on artificial intelligence.
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
Does AI "understand"? Common questions about language models answered
Do chatbots think, remember, learn from you or have opinions? Clear answers to the questions people ask most often about how AI language models work.
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
The deep learning revolution in ten milestones (2012–2022)
AlexNet, word2vec, GANs, ResNet, AlphaGo, transformers, BERT, GPT-3, AlphaFold and ChatGPT: the ten results that turned deep learning into today's AI.
AI Desk3 min read
How to read an AI research paper (and spot the hype)
A practical method for reading machine learning papers: what to read first, how to judge experiments and benchmarks, and the red flags that signal overclaiming.
AI Desk4 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 we review AI tools: the Latent Daily testing methodology
The criteria, test tasks and scoring rules we use to evaluate AI tools and models, how ratings are assigned, and what can and cannot influence a review.
AI Desk3 min read
How to choose an AI writing assistant: a buyer's checklist
Quality, voice control, sources, integrations, privacy and price: a practical checklist and test plan for choosing an AI writing tool for yourself or a team.
AI Desk3 min read
ChatGPT vs Claude vs Gemini: how the big AI assistants differ
The three leading AI assistants compared on what actually differs: ecosystems, strengths, context handling, privacy controls and pricing — plus how to test them yourself.
AI Desk4 min read
Open-weight vs closed AI models: a practical comparison
When should you self-host an open model like Llama, Mistral or Qwen, and when is a closed API better? Cost, quality, privacy, control and licensing compared.
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
How to cut your AI API bill: caching, batching and model routing
Practical techniques to reduce LLM API costs without hurting quality: prompt caching, batch APIs, smaller models, routing, shorter contexts and output limits.
AI Desk4 min read
How to keep up with AI model and tool updates without drowning
New models and features ship every week. A practical system to track the AI changelogs that matter to you, using RSS, release notes and a monthly review habit.
AI Desk3 min read
Model deprecations explained: what happens when an AI model is retired
AI providers regularly retire older models. How deprecation timelines work, what breaks when a model is shut down and how to plan migrations without surprises.
AI Desk3 min read
Open-source alternatives to popular AI tools
Free and open-source options for chat, image generation, transcription, automation and coding assistance — what they are, what you need to run them, and the trade-offs.
AI Desk3 min read
Switching AI tools? How to evaluate an alternative before you move
A step-by-step plan to compare a new AI tool with the one you use today: define success, run a side-by-side trial, check data migration, costs and exit options.
AI Desk3 min read
Vibe coding explained: building software by describing it — and the risks
What "vibe coding" means, how people build apps by talking to AI, where it works brilliantly, where it fails, and how to keep vibe-coded projects safe.
AI Desk3 min read