- Less greens. This looks like a salad. Uk, one of those "healthy" dishes ur mum made/makes.
- Finer chopping.
- Mix the greens with the spaghetti properly (except for the spring onion greens).
- Better bowl to eat from.
- Less amount. This amount of stuff in this bowl looks like two cows are going to graze on it.
- Put this in a nice little mound in the middle of the serving plate/bowl.
- Garnish using chopped spring onion. Remember.... "GARNISH". This is NOT A SALAD.
UraniumBlazer
joined 2 years ago
Oooo yummyyy
Oooo amazing!!!
Nice, but the presentation needs work.
TLDR: Let's say you want to teach an LLM a new skill. You give them training data pertaining to that skill. Currently, researchers believe that this skill development shows up suddenly in a breakthrough fashion. They think so because they measure this skill using some methods. The skill levels remain very low until they unpredictably jump up like crazy. This is the "breakthrough".
BUT, the paper that this article references points at flaws in the methods of measuring skills. This paper suggests that breakthrough behavior doesn't really exist and skill development is actually quite predictable.
Also, uhhh I'm not AI (I see that TLDR bot lurking everywhere, which is what made me specify this).
Fair. I'm a little tired right now, but this article says exactly everything that I want/have to say.
This article is by the Communist Party of India (Marxist Leninist). So just for context, there are two communist parties in India (CPI and CPIM). The CPIM split from the CPI during the Sino-Soviet split. The CPIM was the pro China one. In my opinion, in the modern day, both of them are absolute chads.
I love this article because it does not approach the topic in a vacuum. It compares the Uighur genocide to what the Indian State has been doing in Kashmir since independence. The similarities are uncanny. Kashmir, Xinjiang, the Rohingyas, Kurdistan... the story of the oppressors here is the same throughout.
This just shows that we have different definitions for sentience. I define sentience as the ability to be self aware and the ability to link senses of external stimuli to the self. Your definition involves short term memory and weight adjustment as well.
However, there is no consensus in the definition of sentience yet for a variety of reasons. Hence, none of our definitions are "wrong". At least not yet.
I don't know what a "debate pervert" is. However, what I know is that I wasn't engaging with the intent of "winning" or something.
Correct. So basically, you are talking about it adjusting its own weights while talking to you. It does this in training but not in deployment. The reason why it doesn't do this in deployment is to prevent bad training data from worsening the quality of the model. All data needs to be vetted before training.
However, if you look at the training phase, it does this as you said. So in short, it doesn't adjust its weights in production because it can't, but because WE have prevented it from doing so.
Now about needing to learn and "mutate" to be sentient in deployment. I don't think that this is necessary for sentience. Take a look at Alzheimer's patients. They remember shit from decades ago while forgetting recent stuff. Are they not sentient? An Alzheimer's patient wouldn't be able to take up a new skill (which requires adjusting of neural weights). It still doesn't make them non sentient, does it?
I'm sorry you feel that way. However, don't you think it would be more helpful to point at the holes in my reasoning?
np <3