hapliniste t1_jee3gvr wrote

I tried some things in the web demo and it is really good.

What people haven't realised yet is that Koala (another model they did not publish about for now) is also available in the web demo and it is CRAZY GOOD! It's also really fast because I guess I'm the only one using it right now haha.

I really recommand to try it, it looks like Vicuna is a bit bellow GPT3.5 and Koala a bit above but I did not test it enough to be sure right now.


hapliniste t1_jaebp9r wrote

Alignment will likely be a political issue, not a technological one.

We don't know how an AGI system would work, so we don't know how to solve it yet but it could very well be super simple technologically. A good plan would be to have two versions of the model, and have one be tasked to validate the actions of the second one. This way we could design complex rules that we couldnt code ourself. If the first model think the second model output is not aligned with the value we fed it, it will attribute a low score (or high loss) to the training element of the model (and refuse the output if it is in production).

The problem will be the 200 pages long list of rules that we would need to feed the scoring model, and make it fit most people interests. Also what if it is good for 90% of humanity but totally fuck 10%? That's the questions we will encounter, and that standard democracy might fail to solve best.


hapliniste OP t1_j50pe93 wrote

Also, I think this could help improve the actual "logic" of the model by focusing the small LM on that task while the search part would serve the role of knowledge base.

Another benefit could be the ability to cite its sources.

It really seems like a no brainer to me.


hapliniste t1_ixqd1ip wrote

It worked for me. I did a kangaroo riding a bike. One image was a big failure and the other one came out OK but not better than the 1.5 (but with higher details).

I'll have to see once we have the model in auto's but for now it seems 1.5 with upscaling is still better and give us more power. We'll have to see if it's better when we use upscaling on the 2.0.

Still, the model will abviously be worse for a lot of thing until we get a retrained model (unstable diffusion maybe).