Tagged foundation models · show all articles
A model that sees, hears and reads still returns one fluent answer, and fluency hides the fact that the link between that answer and what was actually there breaks in ten distinct, independently documented ways.
Two questions decide how multimodal AI matures by 2035: whether architecture converges on native any-to-any models, and whether perception and generation both cross into open-world reliability. Four scenarios, each with a falsifier.
Image-text systems tokenize a grid and align two vectors. Video is a spacetime volume, audio is a waveform, and a 3D scene is a continuous field — none of them arrives as a grid, and each forces its own discretization scheme before any model can read it.
Four research lineages solved the same problem — joining vision, audio and text into one system — with four different training recipes. Each recipe holds one cost fixed and lets another float, and the documented trade is an engineering choice, not a hierarchy.
Before a single model could read an image and write about it, two research communities spent a decade building separate pieces that had to be joined by hand. This is the record of each join.
Claude carries more defensive machinery than most deployed models — classifiers, citations, constitutional training. Its failures surface at the seams of that machinery, and Anthropic's own records are usually the first place they are documented.
A deployed Claude model is a pretrained prior, a post-training pass partly shaped by written principles, a handful of per-request settings, and a documented evaluation gate — four separable things, not one object, and each changes the answer differently.
Two questions, not one, decide how Anthropic and the Claude line look in 2035: does its safety-training method stay on its current path, and does its scaling policy become everyone's floor or stay its own. Four scenarios follow, each with a falsifier.
Anthropic's own dated record — a 2021 founding, a Constitutional AI paper that preceded its first product, a Responsible Scaling Policy that has since restricted a real model's deployment — is more precise than the branding built on top of it.
Openness in model releases is not a binary and never was. It is a bundle of separately granted permissions over five separable artefacts, and the word on the announcement page rarely tells you which ones you hold.