Translation. Only works for unified technical texts. The older non-LLM translation is still better for any general text and human translation for any fiction is a must. Case in point: try to translate Severance TV show transcript to another language. The show makes a heavy use of “Innie/Outie” language that does not exist in modern English. LLM fail to translate that - human translator would be able to find a proper pair of words in the target language.
Triaging issues for support. This one is a double-edged sword. Sure you can triage issues faster with LLM, but other people can also write issues faster with their LLMs. And they are winning more. Overall, LLM is a net negative on your triage cost as a business because while you can process each one faster than before, you are also getting way higher volume of those.
Grammar. It fails in that. I asked LLM about “fascia treatment” but of course I misspelled “fascia”. The “PhD-level” LLM failed to recognize the typo and gave me a long answer about different kinds of “facial treatment” even though for any human the mistake would’ve been obvious. Meaning, it only corrects grammar properly when the words it is working on are simple and trivial.
Starting points for deeper research. So was the web search. No improvement there. Exactly on-par with the tech from two decades ago.
Recipes. Oh, you stumbled upon one of my pet peeves! Recipes are generally in the gutter on the textual Internet now. Somehow a wrong recipe got into LLM training for a few things and now those mistakes are multiplied all over the Internet! You would not know the mistakes if you did not not cook/bake the thing previously. The recipe database was one of the early use cases for the personal computers back in 1990s and it is one of the first ones to fall prey to “innovation”. The recipes online are so bad, that you need an LLM to distill it back to manageable instructions. So, LLM in your example are great at solving the problem they created in the first place! You would not need LLM to get cooking instructions out of 1990s database. But early text generation AIs polluted this section of the Internet so much, that you need the next generation AI to unfuck it. Tech being great at solving the problem it created in the first place is not so great if you think about it.
You’re bringing up edge cases for #1, and it should be replacing google translate and basic human translation, eg allowing people to understand posts online or communicate textually with people with whom they don’t share a common language. Using it for anything high stakes or legal documents is asking for trouble though.
For 2, it’s not for AIs finding issues, it’s for people wanting to book a flight, or seek compensation for a delayed flight, or find out what meals will be served on their flight. Some people prefer to use text or voice communication over a UI, and this makes it easier to provide.
For 3, grammar and spelling are different. I said it wasn’t useful for spellcheck, but even then if you give it the right context it may or may not catch it. I was referring more to word order and punctuation positioning.
For 4, yeah for me it’s on par in terms of results, but much much faster, especially when asking followup questions or specifying constraints. A lot of people aren’t search engine powerusers though, so will find it significantly easier, faster and better than conventional search than having to manage tabs or keep track of what you’ve seen without just scrolling back up in the conversation.
For 5, recipes have been in the gutter for a decade or more now, SEO came before LLMs, but yeah, you’ve actually caught on to an obvious #6 I missed here of text summarisation…
What I’m getting overall though is that you’re not considering how tech-savvy the average person is, which absolutely makes them seem less useful as the more tech savvy you are, both the more you’re aware of their weaknesses and the less you benefit from the speedup by simplification they bring. This does make ai’s shortcomings more dangerous, but as it matures one would hope that it becomes common knowledge.
Translation. Only works for unified technical texts. The older non-LLM translation is still better for any general text and human translation for any fiction is a must. Case in point: try to translate Severance TV show transcript to another language. The show makes a heavy use of “Innie/Outie” language that does not exist in modern English. LLM fail to translate that - human translator would be able to find a proper pair of words in the target language.
Triaging issues for support. This one is a double-edged sword. Sure you can triage issues faster with LLM, but other people can also write issues faster with their LLMs. And they are winning more. Overall, LLM is a net negative on your triage cost as a business because while you can process each one faster than before, you are also getting way higher volume of those.
Grammar. It fails in that. I asked LLM about “fascia treatment” but of course I misspelled “fascia”. The “PhD-level” LLM failed to recognize the typo and gave me a long answer about different kinds of “facial treatment” even though for any human the mistake would’ve been obvious. Meaning, it only corrects grammar properly when the words it is working on are simple and trivial.
Starting points for deeper research. So was the web search. No improvement there. Exactly on-par with the tech from two decades ago.
Recipes. Oh, you stumbled upon one of my pet peeves! Recipes are generally in the gutter on the textual Internet now. Somehow a wrong recipe got into LLM training for a few things and now those mistakes are multiplied all over the Internet! You would not know the mistakes if you did not not cook/bake the thing previously. The recipe database was one of the early use cases for the personal computers back in 1990s and it is one of the first ones to fall prey to “innovation”. The recipes online are so bad, that you need an LLM to distill it back to manageable instructions. So, LLM in your example are great at solving the problem they created in the first place! You would not need LLM to get cooking instructions out of 1990s database. But early text generation AIs polluted this section of the Internet so much, that you need the next generation AI to unfuck it. Tech being great at solving the problem it created in the first place is not so great if you think about it.
You’re bringing up edge cases for #1, and it should be replacing google translate and basic human translation, eg allowing people to understand posts online or communicate textually with people with whom they don’t share a common language. Using it for anything high stakes or legal documents is asking for trouble though.
For 2, it’s not for AIs finding issues, it’s for people wanting to book a flight, or seek compensation for a delayed flight, or find out what meals will be served on their flight. Some people prefer to use text or voice communication over a UI, and this makes it easier to provide.
For 3, grammar and spelling are different. I said it wasn’t useful for spellcheck, but even then if you give it the right context it may or may not catch it. I was referring more to word order and punctuation positioning.
For 4, yeah for me it’s on par in terms of results, but much much faster, especially when asking followup questions or specifying constraints. A lot of people aren’t search engine powerusers though, so will find it significantly easier, faster and better than conventional search than having to manage tabs or keep track of what you’ve seen without just scrolling back up in the conversation.
For 5, recipes have been in the gutter for a decade or more now, SEO came before LLMs, but yeah, you’ve actually caught on to an obvious #6 I missed here of text summarisation…
What I’m getting overall though is that you’re not considering how tech-savvy the average person is, which absolutely makes them seem less useful as the more tech savvy you are, both the more you’re aware of their weaknesses and the less you benefit from the speedup by simplification they bring. This does make ai’s shortcomings more dangerous, but as it matures one would hope that it becomes common knowledge.