Comment by ninjahawk1

Good point, another example would be for when I was training my own small LM a while back, the target was about 170M parameters and was trained on 2B tokens worth of movie subtitles.

The run stalled mid-step around 80M parameters, Orb notified me that it stalled, asked if I wanted to resume at the last checkpoint and kill the stalled version. I simply press “yes” and continue doing whatever I was doing.

For non-technical users and non-antisocial people, remembering things you forgot so you don’t let people down. You told your sister you’d send her some pictures two hours ago but it can see you’re scrolling on reddit and the photos are on your desktop, so it assumes you forgot and reminds you.

The idea was that the biggest issue with the usefulness of an agent is that it has too little context about who I am, it needs more data. So I run all of my data through a smart router, then the local database, then the LLM reviews it and uses reasoning on what’s been collected.