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.
But let’s just say for the sake of argument that you’re 100% correct, and that Evo is not an LLM.
Why only assume? I cited Wikipedia. You cited nothing.
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.”
There you go putting words in my mouth again.
The actual technology behind Evo and ChatGPT is structurally the same.
…Except that it isn’t. It’s not a Generative Pre-Trained Transformer. It uses a Transformer-like architecture. You cannot use Evo’s architecture to make a chatbot. It’s a GLM.
The methods of training a model on genomic data or weather patterns is indistinguishable from training it on stolen media.
Go ahead and train a StripedHyena2 model to be a chatbot, then. I’m sure that will work great.
For someone who’s such a stickler for making 100% correct and unambiguous statements, you’re sure keen on asserting equality where there is merely similarity.
Nobody is claiming these technologies don’t share some (or even a lot of) DNA. Being upset that people correctly use the definition of LLMs as outlined by Wikipedia, where even Evo’s own Github page doesn’t claim it’s an LLM, is just derailing the conversation away from people’s righteous objections.
Nobody is campaigning against using non-chatbot AI for science.
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.
Why only assume? I cited Wikipedia. You cited nothing.
There you go putting words in my mouth again.
…Except that it isn’t. It’s not a Generative Pre-Trained Transformer. It uses a Transformer-like architecture. You cannot use Evo’s architecture to make a chatbot. It’s a GLM.
Go ahead and train a StripedHyena2 model to be a chatbot, then. I’m sure that will work great.
For someone who’s such a stickler for making 100% correct and unambiguous statements, you’re sure keen on asserting equality where there is merely similarity.
Nobody is claiming these technologies don’t share some (or even a lot of) DNA. Being upset that people correctly use the definition of LLMs as outlined by Wikipedia, where even Evo’s own Github page doesn’t claim it’s an LLM, is just derailing the conversation away from people’s righteous objections.
Nobody is campaigning against using non-chatbot AI for science.
Read the room. Pay more attention to the context.