Currently working on training language models steered towards certain "states of consciousness".
I have a model trained on publics datasets tied to brainwaves and/eye tracking and text comprehension (have this working well enough to experiment). Now I am training an adapter for various llm architectures to generate text steered to certain neural oscillation patterns (let's call them "states of consciousness" for brevity). I also have a 'rephraser' that rephrases text to elicit these certain states of consciousness. Overall experimenting with creating an suite of tools off my findings with how text relates to the eigenmodes of consciousness. My theory is once I do this I'll be able to do some...interesting things with "AI" agents. lmk if you want to talk about it if you're someone with knowledge in neuroscience/ML. My background is as a Software/ML Engineer so I could use additional thoughts. I do wish I could send a Github/docs which I will soon but this is currently a private project seeking investment for various research/public/private sector applications.
Awesome! I write LLM powered scrapers and stuff all the time and one of the biggest pain points is HTML is full of so much crap that isn't meaningful and overwhelms the context. And being a data science guy idk how to solve this.
awesome that's the same reason why I use it. It's basically a balance between the full html and having the markdown type scrapers that are better for just text. Do you mind if I reach out to you once I set up the Github?
Sooo make your html extremely convoluted, randomized semantics, and a ton of hidden interations (+1 for only using custom web elements). basically make it like youtube. After spending way too much time building browser agents I can assure you this will also defeat Operator as well.
Thank you for the feedback. Personally besides using our API server, we would like to find another way to deploy to anyone who has an issue with this/wants to run everything local (not just the client). Also I think if we had a OSS plug and play version where you could enter in your API keys locally it would help us ship to more devs. Would you be interested in this?
I'm so impressed with the concept of this agent but sorry, I can't have you accessing all my corporate data and systems because I access them via browser.
Perhaps you could create both a Public and Corporate version of the extension, like Copilot does. The Corporate version could have access to all browser data but not share it beyond the bounds of the company.
Thanks! That’s a great point we’ve been discussing how to deal with sensitive data after the launch. I think a corporate/enterprise version makes sense.
Some analysis I've been reading on the implications of DeepSeek says that model optionality is probably here to stay. If so, I think incorporating model choice would be a valuable aspect of this kind of product. Conversely, I agree with parent: I'm not installing this software with that privacy policy in place.
Anything improving reasoning chains of though improves planning. Right now the long term ones Art mentioned like logging in have been around 80% while simpler ones have been higher. Right now our main issue is figuring out how to keep the server up :/ we're getting a little more traffic than expected. However, to bump those success rates up (which we need to) we really really need to fine tune additional models which we're planning out right now.
I have a few ideas around that mostly going down the RL route (with a twist) mixed with some knowledge graph work. We'll give an update when we push that!
We have an API server where we execute all the agent reasoning/planning jobs then we stream the browser commands to the client. We mention this in the how it works section on the website. This is the main reason why we have the 5 bot a day limit is because of this. It's cheap for us to run as of now but if anyone would like us to ship a version where you'd use your own api keys (plug n play) locally let us know!
I have a model trained on publics datasets tied to brainwaves and/eye tracking and text comprehension (have this working well enough to experiment). Now I am training an adapter for various llm architectures to generate text steered to certain neural oscillation patterns (let's call them "states of consciousness" for brevity). I also have a 'rephraser' that rephrases text to elicit these certain states of consciousness. Overall experimenting with creating an suite of tools off my findings with how text relates to the eigenmodes of consciousness. My theory is once I do this I'll be able to do some...interesting things with "AI" agents. lmk if you want to talk about it if you're someone with knowledge in neuroscience/ML. My background is as a Software/ML Engineer so I could use additional thoughts. I do wish I could send a Github/docs which I will soon but this is currently a private project seeking investment for various research/public/private sector applications.