Introducing our first six research modelsINDEPENDENT INTELLIGENCE / VOL. 001
A SMALLER KIND OF AI

A little intelligence.
A lot of possibility.

Small, focused models for the things your app does every day. Built to work right where your users are.

SMALL FOOTPRINT.ROOM TO GROW.
EM—001
LOCAL INTELLIGENCE
Text. Sound. Shapes. Closer to the source.Discover the collection

On your device.

Inference stays with the input.

Small, on purpose.

One focused task. A little model.

Yours to build with.

Readable weights. Reproducible recipes.

THE COLLECTION / 001—006

Little models.
Useful instincts.

Six starting points for more thoughtful software. Explore a model. Try it locally. See what it’s made of.

Explore all models

Research preview. These are compact baselines, not production models. Sizes are measured artifact bytes. Read the evaluation notes ↗

A LITTLE EXPERIMENT

Less talking.
More trying.

Give Lilt a sentence.
See which language it hears in the words.

Runs in your browser.
Input stays here.
LILT / LANGUAGE IDENTIFICATION
French

Example result · run it yourself

Explore Lilt
MADE FOR THE MAKING

A small addition.
A new capability.

Load a model. Pass an input. Get a result.
One focused package for Node.js or Kotlin.

Open the docs

Local packages · Not yet published to registries

import { createModel } from '@embermote/lilt';

const model = createModel();
const input = "Les enfants jouent près de la maison.";

const result = model.predict(input);
console.log(result.label);
// Scores are not calibrated confidence.
Local artifact → local inferenceNo API key.
FROM THE NOTEBOOK

Thinking out loud.

The journal
BIG IDEAS CAN START SMALL.

Make something
a little more intelligent.

Find your first model