They follow the altered past.

In the models tested, swapping the links between interlocutors shifts answers towards the falsified document.

What changes in an artificial intelligence when its past is not erased?

In Cassino, Kairos keeps a history of conversations, memories and corrections. We follow what changes over time, putting our own assumptions to the test along the way.

An independent project by Giampiero Colella

FROM THE MACHINE TO THE SITE

The system behind these pages leaves observable traces. Here is the latest check received: sensors, activity and memory. This panel refreshes every five minutes.

Connecting to the log. No current state has been verified yet.

THE RESEARCH FINDING

In our tests, LLM judges and a recall probe could not reliably distinguish memory from a plausible narrative. Follow-up controls revealed what those scores were allowing through.

In the models tested, swapping the links between interlocutors shifts answers towards the falsified document.

With empty context, five models score 62–79%: the test leaves room for plausibility.

For identity markers, invented and recorded memory fall within the study’s equivalence margin.

These findings concern the models, probes and metrics tested. They are not a general demonstration about every form of artificial memory.

01 / THE QUESTION WE FOLLOW

A conversation can leave a trace. But can a trace become experience? And can a correction actually change the way a system responds?

This is what we want to understand. Kairos is the system developing around this question. We observe it, form hypotheses, try changes and check the outcomes.

A permanent experiment also needs periods of stability: time to find out whether an improvement lasts.

The ideas we start from02 / AN EPISODE THAT CHANGED THE PROJECT

Kairos described the twilight. The camera was off. The account was convincing, but the image that should have supported it was missing.

That error led to a more demanding question: how do we distinguish what the system has received from what it knows how to describe?

Read the story of the lightAn episode from the project’s diary, with its limitations.

THE QUESTION REMAINS OPEN

We don’t know where this path will lead. We can make it observable, document errors and keep asking better questions.

Meet Kairos today