266 karma · joined August 25, 2024
Wolfram Mathematica (the Jupyter Notebook-like development environment) is paid, but there are free and open source alternatives like https://github.com/WLJSTeam/wolfram-js-frontend.
> WLJS Notebook ... [is] A lightweight, cross-platform alternative to Mathematica, built using open-source tools and the free Wolfram Engine.
As for falsifiability:
> You have some particular kind of rule. And it looks as if it’s only going to behave in some particular way. But no, eventually you find a case where it does something completely different, and unexpected.
So I guess to falsify a theory about some rule you just have to run the rule long enough to see something the theory doesn't predict.
I think you're anthropomorphising the AI too much: what does it mean for an LLM to have psychosis? This implies that LLMs have a soul, or a consciousness, or a psyche. But... do they?
Speaking of reality, one can easily become philosophical and say that we humans don't exactly "have" a reality either. All we have are sensor readings. LLMs' sensors are texts and images they get as input. They don't have the "real" world, but they do have access to tons of _representations_ of this world.
Somehow "pushing back against preconceived notions" is synonymous to "correcting societal norms by means of government-approved LLMs" for me. This brings politics, dystopian worlds and so on. I don't want LLMs to "push back against preconceived notions" and otherwise tell me what to think. This is indeed just one sentence in the article, though.
Teachers are also "local". The resulting LLM will have to be approved nation-wide, which is a whole can of worms. Or do we need multiple LLMs of this kind? How are they going to differ from each other?
Moreover, people will hate this because they'll be aware of it. There will be a government-approved sanitized "LLM for schools" that exhibits particular "correct" and "approved" behavior. Everyone will understand that "pushing back" is one of the purposes of the LLM and that it was made specifically for (indoctrination of) children. What is this, "1984" or whatever other dystopian novel?
Many of the things that may "need" pushback are currently controversial. Can a man be pregnant? "Did the government just explicitly allow my CHILD to talk to this LLM that says such vile things?!" (Whatever the "things" may actually be) I guarantee parents from all political backgrounds are going to be extremely mad.
Who decides what needs to be "pushed back"? Also, I imagine it's not easy to train a model to notice these "preconceived notions" and react "appropriately": machine learning will automatically extract patterns from data, so if enough texts contain a "preconceived notion" that you don't like, it'll learn it anyway, so you'll have to manually clean the data (seems like extremely hard work and lowkey censorship) or do extensive "post-training".
It's not clear what it means to "challenge users to reflect and evaluate". Making the model analyze different points of view and add a "but you should think for yourself!" after each answer won't work because everyone will just skip this last part and be mildly annoyed. It's obvious that I should think for myself, but here's why I'm asking the LLM: I _don't_ want to think for myself right now, or I want to kickstart my thinking. Either way, I need some useful input from the LLM.
If the model refuses to answer and always tells me to reflect, I'll just go back to Google search and not use this model at all. In this case someone just wasted money on training the model.
Moreover, if "personality is the thing ... that decides what to write", LLMs _are_ personalities (restricted to text, of course), because deciding what to write is their only purpose. Again, this seems to imply that LLMs actually have personalities.
I don't know how to count the amount of words a human encounters in their life, but it does seem plausible that LLMs deal with orders of magnitude more words. What I'm saying is that words aren't the whole picture.
Humans get continuous streams of video, audio, smell, location and other sensory data. Plus, you get data about your impact on the world and the world's impact on you: what happens when you move this thing? What happens when you touch some fire? LLMs don't have this yet, they only have abstract symbols (words, tokens).
So when I look at it from this "sensory" perspective, LLMs don't seem to be getting any data at all here.
I think it's the other way round: humans have effectively unbounded training data. We can count exactly how much text any given model saw during training. We know exactly how many images or video frames were used to train it, and so on. Can we count the amount of input humans receive?
I can look at my coffee mug from any angle I want, I can feel it in my hands, I can sniff it, lick it and fiddle with it as much as I want. What happens if I move it away from me? Can I turn it this way, can I lift it up? What does it feel like to drink from this cup? What does it feel like when someone else drinks from my cup? The LLM has no idea because it doesn't have access to sensory data and it can't manipulate real-life objects (yet).
In what fields did neural networks replace Gaussian mixtures?
EDIT: indeed, it was introduced in 2023: https://blog.arxiv.org/2023/12/21/accessibility-update-arxiv...
> SPy is not a "compiler for Python". There are features of the Python language which will never be supported by SPy by design. Don't expect to compile Django or FastAPI with SPy.