A new category of intelligence.
Learning that begins where training ends.
AI models learn before they are released, and then stay as they are. ACI learns, plans, simulates, decides and acts after: at runtime, from your work, for as long as it runs. That makes it a category of its own.
Where training ends, ACI begins.
A model’s learning ends when it is released. ACI’s begins on its first day at work, and goes on for as long as it runs.
Step 1 of 5: Training
A model learns the world in one long training run, before anyone uses it.
It builds on what came before.
Each result adds to what ACI knows, without disturbing what came before. A new rule applies from the next decision, and everything else it learned stays as it was.
Step 1 of 4: The new and the old
It is intelligence, so it generalises.
In MS Duplex, ACI learns the pattern behind a result, so it handles a case it has never seen, tells a look-alike apart, and acquires skills it tests before use. In MS Reflex, a lesson from one example carries to the cases like it.
Step 1 of 3: New words
In MS Duplex, the same request in new words: ACI knows it, and answers.
It learns your work, and what it learns is yours.
A model knows what the world wrote down. ACI knows what your work has shown it, and keeps each lesson on record. In MS Duplex, it goes wherever you work. In MS Reflex, it stays on your machines, under your control.
Step 1 of 3: An example
In MS Reflex, your operator shows the rover a new gate once, and ACI learns it on the spot.
Put intelligence that keeps learning to work.
Start with MS Duplex in the assistant you already use, or plan an MS Reflex pilot on your machines. Either way, what it learns is yours.