SNN - ANN conversion and surrogate gradient methods can both get good results these days, so training has become a lot more comparable to ANNs than it was in the past. I would agree though that there is a disconnect between the hardware and software still which is preventing SNNs from reaching the dream of super low power models.

There has been a lot of progress in the last 2 - 3 years. They're still not quite at the level of ANNs in general but have been gaining ground quickly and do outperform ANNs on some specific tasks -- usually things with a temporal component but low data dimensionality per time-step. Another area with comparable results to ANNs would be object detection.

In a sense, you can communicate between semantic text embeddings and LM models through this method(would operate differently to multi modal embeddings): https://www.lesswrong.com/posts/mkbGjzxD8d8XqKHzA/the-singular-value-decompositions-of-transformer-weight

This method, which is only practical for toy problems really right now, would allow you to use semantic embeddings to find what to look for when doing SVD on an (autoregressive) LM. You could depend this on the input, for example, transforming your embedding into the keys to apply the abduction with in that process, and impacting the generation of logits. I'm not sure this would behave much differently to altering the logit_bias of tokens, but it would be interesting to hear if it was.

I would ideally be able to go in and select a start time and end time for each event within the longer timeseries and assign it a class, like you do for YOLO training labels, but in 1D. I can assemble and label the dataset, but the labeled segments will be extremely variable in length.

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Machine learning algorithms are not even "intelligent" enough to filter out Getty watermarks.

They do not have minds or experiences, any more than zbrush or cinema4D or any other complicated software do.

Furthermore, they do not produce outputs like humans do - the speed and scale are more akin to automated car factories than human tinkers.

Fair use laws were not designed with them in mind.

Artificial general intelligence at this time of human development at this level of hardware, localized entirely within your warehouse?

You have to pay to use the api and it’s completely closed source but resemble.ai works pretty well

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Sounds like you want something like a logical representation of sentences. Reducing sentences to first order logic might be what you're looking for. There's also AMRs (Abstract Meaning Representations). The problem with AMRs is that they need to be built, which is non-trivial for machines and time-consuming for humans.

You can minimize the energy costs by hosting the primary interface on a COBOL mainframe, with eleventeen node-processors.

No it's real human. For some reason it didn't take in my first paragraph. What I was saying was that I own a high value domain related to vaccines and I was also thinking something along the similar lines of what OP posted.

And then the rest of my post was about starting from first principles and asking the simple question what problem does this machine learning website or app solve.

That doesn't help at all. Reading tokens at the byte level does not stop the word "they" or "it" from being vague in the context of a sentence.

It's not just about swapping tokens for other tokens. It's that grammatical structure (of any language) which can convey ambiguous meaning.

I’m able to access it from https://www.wrotescan.com. Are you getting an error message?

There's been some work on getting models to work at the byte level. An example: https://arxiv.org/abs/2105.13626

Is the website down?

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Reads like an ai that needs more training wrote this.

Thank you so much for your reply.

I did take a look at your suggestions. The Sergey Levine course seems really awesome, It is definitely on the list to do. But I'm a little bit conflicted regarding the David Silver course. I have a few follow-up questions, if you don't mind:

I'm currently doing Hugging Face Deep RL course. It is free and at the end I get a certification of completion, not that I care much about the certification, but it is always nice to get a certificate.

Also, isn't the David Silver course a little outdated? It seems that the video lectures were made 7 years ago. I guess the basics don't change, but I was wondering what is the best course to take. I think they are around the same lvl of difficulty. What would you choose?

> you.com

First time hearing about that search engine. I gave it a go, and man is it bad. I don’t understand how they think people will be loyal users of their “AI” search engine when nothing is intelligent about it.

I asked a simple query: “should I wear a jacket tomorrow?”, expecting it to interpret my query as “will it rain/be cold tomorrow” and this was the answer:

> It depends on the weather and the occasion. If it is mild or warm outside, then wearing a jacket may not be necessary. Ultimately, it is up to you to decide what to wear based on the weather, the occasion, and your personal style.

You can follow along CMU’s deep RL course, they post which research papers they go over here: https://cmudeeprl.github.io/703website_f22/lectures/

There's nothing wrong with relevant self promotion, especially if it's high quality material. Obviously bad/irrelevant stuff should be removed, but that's up to the mods discretion.

I personally bookmarked this for later as it's very interesting to me.

No, information is not reduced by just using another code

Looks so dated..