Have you posted actual technical details to share and get feedback? As a long time member of this sub I would be interested, and I don’t think I’m alone here.

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semantic synthesis, I know that it has made a lots progress with those text-to-image diffusion models, but what I notice is that not much work is invested in semantic generation, especially video generation, or maybe I have just missed something.

Lol sure.

could you test it again LRA please?

>plus the approach is fundamentally wrong.

What do you mean by that?

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Very little of it is.

I feel like for that it’s better to follow researchers on Twitter. Like @_akhaliq is a good start, or @karpathy

My thought was similar. One of the predominant philosophical understandings of consciousness is that it's an emergent trait of organisms.

Just like language models show spelling as an emergent property. Just like vision transformers show spacial awareness as an emergent property.

Isaac Asimov went "It's easier to make the child brain than the adult brain." Well, have we done that?

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Got it. Thanks for the information.

In terms of probabilities yeah that's right.

In the actual code, it's most common to do a softmax over the output vocabulary. In practice that means the model computes the probability of every possible next output (whether word or subword) and then we sort it, take the argmax, or the top K depending on the problem.

I think about generating one word at a time as a key part of the way we're searching through the space of probable sentences, because we can't afford to brute-force search.

There's way more to computer vision than what you listed.

Long form video understanding is still incredibly limited. Compared to the current SOTA capabilities of LLM to understand very long text and the various advancements in text summarization, video understanding seems to have an incredibly long ways to go.

Our current models can understand relatively very simple actions (sitting/standing/dancing) however compared to text, we want to reach a level where we can understand entire scenes in a movie or maybe even an entire movie, although that's more of a fantasy currently. Not to mention all the 3D input (instead of a projection 2D image) which adds extra complexity.

I agree with the sentiment. But, you do understand what you have just done, right?

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Pray tell, how do you know if an AI is sentient or conscious?

Not everything that involves chatgpt belongs in this sub.

there is no "useful vs unuseful", you either want it or do not want it. the usefulness is something you define which is subset of the things you want. however the model will just suggest you stuff that may or may not be practical to you, but you want it. you may find them pseudo-useful or useful at the moment or....

case is, it will sell

That book actually looks amazing. Nice visualizations, code in Julia to implement the algorithms and the exercises have solutions at the end. To top this off, its available for free to download.

I am impressed, thank you so much for the suggestion!

What are the smaller academically focused ML subs

There should be an active "beginning and easy questions megathread" instead of the sub just being uninviting. The about says to go to "r/learn machine learning" which was just a dead end for me.

For example, I am here because of chatgpt. So quit reading now if you don't like newbs. But I have over 20 years of programming esperience, I just never tried machine learning before. -I have watched videos about it and read, that's it. But I'm interested in it -now.

In a month of hobby time, I now have a working prototype of a novel llm architecture that can learn and write at blistering speed; and accurately rewrite Wikipedia articles, create new poetry, etc with as little as 7mb of model size while staying coherent. I am allowing in to grow to 8.5 billion parameters sometimes and can still run it on a potato device, -quickly. I am working on ways to simultaneously increase accuracy and long term memory and abstraction capability while lowering the amount of resources it needs. And it's working.

And this sub is too snobby to allow beginner questions, so instead of my project getting any sort of help, momentum or publicity or open sourcing, or guidance, -or I don't know, me becoming part of the community here, I'm just keeping it in dark corner to die or get the ADHD hyperfocus once a month; even if yeah it might be worthless, -but it could potentially open up one other person's input and be a game changer, because none of the approaches I'm taking come up in papers or Google searches, and they are efficient and they work.

But no noob questions. So I run to Google and other places to learn, and I don't post here. this community won't grow and get cross specialization with the attitude it has, it's very off putting.

Makes sense. To expand on the number of possible iterations wouldn't it be something akin to a collapsing wave function? Like trying to iterate through all possible responses would be impossible, but the list of probable responses shrinks as the context expands.

For example if I just input "knock" there are too many possible sentences to search, but if I input "knock knock". The most likely response is "who's there?" A simple example sure, but you get the point yea?

Yeah, I mean people with mental ilness (e.g. schizophrenia), people with debilitatingly low intelligence and similar cases. Who knows how they would interact with seeminingly intelligent LMs.