It should be noted that e.g. DeepL which is a very good AI translation service isn’t an LLM but rather falls into the category of “Neural machine translation”. So this would still be fine
Edit: I leaned it’s an LLM now, my knowledge is outdated.
To be fair, LLMs do really good translations, but as with everything you use them for, you need to be familiar with the subject so you catch their mistakes.
I’m thinking beginner level so the LLM can support instead of replacing you while you get better.
LLMs do not do translations, they approximate something similar to the original statement in another language. They are very accurate when given a common piece to translate, but wildly accurate when given a sentence which is highly improbable.
If it makes more mistakes than humans and therefor requires humans to check all of their work, and it’s been shown to not be very cost-effective, then what’s the point? Better to just not use the AI at all.
LLM stands for “large language model” in other words, it is a big neural machine. Saying they don’t use LLMs is like saying the ocean isn’t blue, it’s azure.
LLMs work by increasing scale, number of separate neural networks, to increase accuracy when improvement from training hits a wall. Which is very problematic because it means power consumption becomes exponential. I think most people won’t have a problem with neural networks, but certainly do have a problem with LLMs.
It should be noted that e.g. DeepL which is a very good AI translation service isn’t an LLM but rather falls into the category of “Neural machine translation”. So this would still be fine
Edit: I leaned it’s an LLM now, my knowledge is outdated.
DeepL uses plenty of LLMs internally and recently laid of around 1000 employees to “shift to AI”.
To be fair, LLMs do really good translations, but as with everything you use them for, you need to be familiar with the subject so you catch their mistakes.
I’m thinking beginner level so the LLM can support instead of replacing you while you get better.
LLMs do not do translations, they approximate something similar to the original statement in another language. They are very accurate when given a common piece to translate, but wildly accurate when given a sentence which is highly improbable.
If it makes more mistakes than humans and therefor requires humans to check all of their work, and it’s been shown to not be very cost-effective, then what’s the point? Better to just not use the AI at all.
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LLM stands for “large language model” in other words, it is a big neural machine. Saying they don’t use LLMs is like saying the ocean isn’t blue, it’s azure.
An LLM is a type of artificial neural network, but not every ANN is an LLM. So its a lot more like saying that not every red thing is a firetruck.
That is an extremely simple concept that even toddlers can understand.
I’m having trouble passing your comment. Are you saying I’m more stupid than a toddler, or that the marketers are?
LLMs work by increasing scale, number of separate neural networks, to increase accuracy when improvement from training hits a wall. Which is very problematic because it means power consumption becomes exponential. I think most people won’t have a problem with neural networks, but certainly do have a problem with LLMs.
Machine learning, neutral networks, AI, in general it’s very useful when trained at a specific task. LLMs are most certainly where things went wrong.