| ▲ | anon-3988 2 hours ago |
| You are forgetting that they are now going to use AI to summarize it back. |
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| ▲ | kombookcha an hour ago | parent | next [-] |
| This is one of my major concerns about people trying to use these tools for 'efficiency'. The only plausible value in somebody writing a huge report and somebody else reading it is information transfer. LLM's are notoriously bad at this. The noise to signal ratio is unacceptably high, and you will be worse off reading the summary than if you skimmed the first and last pages. In fact, you will be worse off than if you did nothing at all. Using AI to output noise and learn nothing at breakneck speeds is worse than simply looking out the window, because you now have a false sense of security about your understanding of the material. Relatedly, I think people get the sense that 'getting better at prompting' is purely a one-way issue of training the robot to give better outputs. But you are also training yourself to only ask the sorts of questions that it can answer well. Those questions that it will no longer occur to you to ask (not just of the robot, but of yourself) might be the most pertinent ones! |
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| ▲ | notahacker 16 minutes ago | parent | next [-] | | Yep. The other way it can have net no impact is if it saves thousand of hours of report drafting and reading but misses the one salient fact buried in the observations that could actually save the company money. Whilst completely nailing the fluff. | |
| ▲ | birdsongs an hour ago | parent | prev | next [-] | | > LLM's are notoriously bad at this. The noise to signal ratio is unacceptably high I could go either way on the future of this, but if you take the argument that we're still early days, this may not hold. They're notoriously bad at this so far. We could still be in the PC DOS 3.X era in this timeline. Wait until we hit the Windows 3.1, or 95 equivalent. Personally, I have seen shocking improvements in the past 3 months with the latest models. | | |
| ▲ | kombookcha 16 minutes ago | parent | next [-] | | Personally I strongly doubt it. Since the nature of LLM's does not allow them semantic content or context, I believe it is inherently a tool unsuited for this task. As far as I can tell, it's a limitation of the technology itself, not of the amount of power behind it. Either way, being able to generate or compress loads of text very quickly with no understanding of the contents simply is not the bottleneck of information transfer between human beings. | |
| ▲ | mcny an hour ago | parent | prev [-] | | I would like to see the day when the context size is in gigabytes or tens of billions of tokens, not RAG or whatever, actual context. |
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| ▲ | kykeonaut an hour ago | parent | prev [-] | | > Those questions that it will no longer occur to you to ask (not just of the robot, but of yourself) might be the most pertinent ones! That is true, but then again also with google. You could see why some people want to go back to the "read the book" era where you didn't have google to query anything and had to make the real questions. |
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| ▲ | prmoustache an hour ago | parent | prev | next [-] |
| This reminds me of that "telephone" kids game. https://en.wikipedia.org/wiki/Telephone_game |
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| ▲ | SpaceNoodled an hour ago | parent | prev [-] |
| So what we now have is a very expensive and energy-intensive method for inflating data in a lossy manner. Incredible. |
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