Obviously I’m using AI here as a shorthand for (all) LLMs, like the author of the article. The term AI is, on its own, so broad and meaningless, as to be entirely useless without a proper context to scope it.
No LLM (corporate or not) can be a reliable source of information due to the architectural limitations of LLMs.
Then you don’t actually understand what LLMs are, and you’re using the term as a short-hand to mean chat bots. I’m not trying to be rude, but you need to understand that is just a fact, if you think LLMs can only be chat-bots, and can only be corporate, and can only be trained unethically.
Would it surprise you to know that quite a lot of genuine advances have been made by using LLMs that don’t speak any language you’d recognize? Evo 1 and Evo 2 for example “Speak” genome sequences. There are other models that have been used to improve weather modeling, and animal behaviour analysis.
You’re right that AI is a very broad term, but so is LLM. The problem is that ignorant people see “AI” and automatically assume it’s bad because of the connotation with Chat-Bots.
if you think LLMs can only be chat-bots, and can only be corporate, and can only be trained unethically
Don’t put words in my mouth.
1 and Evo 2 for example “Speak” genome sequences. There are other models that have been used to improve weather modeling, and animal behaviour analysis.
Evo 1 and 2 are deep learning models (I think Genomic Language Models would be the correct term), but not Large Language Models. I’m willing to bet neither are the “other” models you’re mentioning. They’re unlikely to be trained on vast amounts of human text for purposes of natural language interaction.
Besides, none of those “other models” are in any way applicable to either the OP or the critique of using LLMs as a source of information.
This is my point. They are LLMs. That is not an opinion or a debatable point. They are categorically, definitionally, LLMs. You don’t understand what LLMs are, because LLMs ARE deep learning models, and instead of taking the time to actually learn about the technology you’re responding to my corrections with hostility.
You and I are on the same side. Chat-bots ARE harmful. But putting that label on a technology as a whole is purely tribe-based fear that is already causing the spread of unfounded fear and misinformation.
And the claim wasn’t “Don’t use AI as a source of information,” which I agree with. It was “Don’t use any AI,” which you clarified to mean LLMs. So this is very much pertinent.
You don’t understand what LLMs are, because LLMs ARE deep learning models, and instead of taking the time to actually learn about the technology you’re responding to my corrections with hostility.
You’re claiming that I don’t understand technology while seemingly claiming that because LLMs are a type of deep learning, then all deep learning models are LLMs.
Evo was trained on genomic sequences, not human text. Per Wikipedia:
A large language model (LLM) is an AI model (typically a neural network) trained on a vast amount of text for natural language processing tasks, especially language generation.
Genomic sequences are not natural language. Ergo, “definitionally” Evo 2 is not an LLM.
I did not say all deep learning algorithms are LLMs, I said all LLMs are deep learning algorithms. It’s a nested hierarchy, that relationship only runs one way.
Yes. Evo was trained on text strings of genomic data. That’s what I was trying to say was the misunderstanding. LLMs do not require language as you and I would recognize it. If you think that calling them “Large Language Models,” is misleading, I kinda agree, but then we can start arguing semantics about why scientists name anything the way they do. Dark matter isn’t actually dark, and probably isn’t matter. Dark energy isn’t dark. There was no explosion during the big bang.
If you’re using colloquial word usage and demanding scientific advances follow your expectations, you’re going to have a bad time.
But let’s just say for the sake of argument that you’re 100% correct, and that Evo is not an LLM. Rather, it’s something extremely close, save for a few differences.
People are already angry at the researchers for “Using AI to develop super-bugs,” or saying the genuinely universal “AI has no uses!” And earnestly failing to differentiate between the shit-bot that makes deep-fakes, and the AI designed to identify cancers.
That is why I absolutely reject your disrespectful framing that by defending a technology, and NOT it’s worst uses, I’m somehow opposite to “care(ing) for humanity.”
The actual technology behind Evo and ChatGPT is structurally the same. The methods of training a model on genomic data or weather patterns is indistinguishable from training it on stolen media. The difference is the uses, and targets.
Obviously I’m using AI here as a shorthand for (all) LLMs, like the author of the article. The term AI is, on its own, so broad and meaningless, as to be entirely useless without a proper context to scope it.
No LLM (corporate or not) can be a reliable source of information due to the architectural limitations of LLMs.
Then you don’t actually understand what LLMs are, and you’re using the term as a short-hand to mean chat bots. I’m not trying to be rude, but you need to understand that is just a fact, if you think LLMs can only be chat-bots, and can only be corporate, and can only be trained unethically.
Would it surprise you to know that quite a lot of genuine advances have been made by using LLMs that don’t speak any language you’d recognize? Evo 1 and Evo 2 for example “Speak” genome sequences. There are other models that have been used to improve weather modeling, and animal behaviour analysis.
You’re right that AI is a very broad term, but so is LLM. The problem is that ignorant people see “AI” and automatically assume it’s bad because of the connotation with Chat-Bots.
Don’t put words in my mouth.
Evo 1 and 2 are deep learning models (I think Genomic Language Models would be the correct term), but not Large Language Models. I’m willing to bet neither are the “other” models you’re mentioning. They’re unlikely to be trained on vast amounts of human text for purposes of natural language interaction.
Besides, none of those “other models” are in any way applicable to either the OP or the critique of using LLMs as a source of information.
This is my point. They are LLMs. That is not an opinion or a debatable point. They are categorically, definitionally, LLMs. You don’t understand what LLMs are, because LLMs ARE deep learning models, and instead of taking the time to actually learn about the technology you’re responding to my corrections with hostility.
You and I are on the same side. Chat-bots ARE harmful. But putting that label on a technology as a whole is purely tribe-based fear that is already causing the spread of unfounded fear and misinformation.
And the claim wasn’t “Don’t use AI as a source of information,” which I agree with. It was “Don’t use any AI,” which you clarified to mean LLMs. So this is very much pertinent.
You’re claiming that I don’t understand technology while seemingly claiming that because LLMs are a type of deep learning, then all deep learning models are LLMs.
Evo was trained on genomic sequences, not human text. Per Wikipedia:
Genomic sequences are not natural language. Ergo, “definitionally” Evo 2 is not an LLM.
While its StripedHyena2 architecture is very similar to LLMs, it does not use the same Generative Pretrained Transformer architecture associated with LLMs (per: https://docs.nvidia.com/bionemo-recipes/2.6.3/interactives/illustrated-evo2/index.html ).
My hate of LLMs is certainly not misinformed. It’s only tribe-based in that I care for humanity.
I did not say all deep learning algorithms are LLMs, I said all LLMs are deep learning algorithms. It’s a nested hierarchy, that relationship only runs one way.
Yes. Evo was trained on text strings of genomic data. That’s what I was trying to say was the misunderstanding. LLMs do not require language as you and I would recognize it. If you think that calling them “Large Language Models,” is misleading, I kinda agree, but then we can start arguing semantics about why scientists name anything the way they do. Dark matter isn’t actually dark, and probably isn’t matter. Dark energy isn’t dark. There was no explosion during the big bang.
If you’re using colloquial word usage and demanding scientific advances follow your expectations, you’re going to have a bad time.
But let’s just say for the sake of argument that you’re 100% correct, and that Evo is not an LLM. Rather, it’s something extremely close, save for a few differences.
People are already angry at the researchers for “Using AI to develop super-bugs,” or saying the genuinely universal “AI has no uses!” And earnestly failing to differentiate between the shit-bot that makes deep-fakes, and the AI designed to identify cancers.
That is why I absolutely reject your disrespectful framing that by defending a technology, and NOT it’s worst uses, I’m somehow opposite to “care(ing) for humanity.”
The actual technology behind Evo and ChatGPT is structurally the same. The methods of training a model on genomic data or weather patterns is indistinguishable from training it on stolen media. The difference is the uses, and targets.