Raw LLM Responses

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G You people only think it is a threat because you can't control it and manipulate… ytc_Ugwld6Z9E… G Bro I think you are extra worried. I am Masters student doing research on AI, A… ytr_UgwNdKu0B… G Fascinating perspective from Helen Toner! It's a reminder that while AI continue… ytc_Ugwa7ktSb… G can't say i like AI art to any extent, however i also don't get the wild obsessi… ytc_Ugw-FtRQv… G To those who use AI Generated Images and call it their own work: You aren't an a… ytc_UgzqwnYF1… G You see guys, I am an artist as well. But this is a hard topic, bcause in fact h… ytc_UgzdH_50r… G Great episode. 👏👏 I’ve been saying this for years, and it’s more relevant than e… ytc_UgwBdckUr… G Jeff Bezos will not stop developing facial recognition software . All the other … ytc_UgzgwXmHF…
Comment
Absolutely loved the predictions from Sabine, Although they are predictions and may not be 100% correct, but mostly to the point, and I love that we get something conclusive from this channel, you have to be brave to predict. Counter points I would add is, though not human like intelligence but text being the default median of our professions and work, LLMs do have potential in tasks which are non critical (medical or financial) and have verification loops, they can be automated and are being, and yes 90+% of work 90+% of time is not innovating but reproducing, so LLMs can help there as well.. and also when working with trusted sources, like for my own work or APIs I own/trust, there is no risk of prompt injection as with external communication. I am not denying any of Sabine points, just showing a way that LLMs can still be productive and effective if not entirely (which is good, as we keep our white color jobs). Also one point which Sabine didn't mentioned is the limited context window and context rot, which means LLMs don't have infinite memory and all the local context like us and instead we have to load relevant context every time we need them to work on each task, which is a major limitation.
youtube 2025-12-24T02:2…
Coding Result
DimensionValue
Responsibilitynone
Reasoningmixed
Policynone
Emotionapproval
Coded at2026-04-26T23:09:12.988011
Raw LLM Response
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