Raw LLM Responses
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I am of the opinion that if many people have self-driving cars, that most of the…
ytc_UghasmfeH…
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Welcome to my world. It is a scary thing to deal with. We are dealing with this …
rdc_dcwmoli
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I strive to become a great artist. I want a career that involves art. Another pr…
ytc_UgyA0LjQO…
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Little does the Ai CEO realizes that he is contributing to the extinction of the…
ytc_UgxMGQuLt…
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Human level A.I takes a LOT of time, effort and money etc. There will be tons of…
ytc_UgybEkuIa…
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stupid people don't understand that consciousness is everywhere, my cat is absol…
ytc_UgwngMfFM…
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Nicholas Perez - check out this blog post that we published today that goes into…
ytr_Ugi75uTYK…
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The Oppenheimer of AI now recognises his great gift is nothing of the kind even …
ytc_Ugzv61OQX…
Comment
Regarding the ending, so how can a machine where none of the subparts are actual thinking, get 80% success rate suddenly on normal white collar tasks in many industries? It seems like there is a missing reasoning leap there. 😂 I can only conclude that this machine will work continuously for 4 hours of deep work, but the result will be only mildly useful to a company. Also in real life, I get 1 good result out of 2-4 deep work sessions 3-8 hours), but the other sessions taught me where I was wrong and is important to the process. How will success be evaluated then? Also I have not seen 80% success rate anywhere if that means the result/product fully did what you asked and it can be deployed to production. Usually the 80% means it finished (stopped running), but it may not have passes all the tests, may have totally skipped some requirements, and usually have glaring problems that make it unusable in production. I would welcome a 2nd video with detailed example of how LLM or any other deep-learning & machine-learning model combo can replace x% of white collar jobs in the near future. Even if you believe it will take 10-20 years instead of 1.5-2 years, I would like to hear your thoughts. Thanks. 🎉
youtube
AI Jobs
2026-03-02T18:5…
Coding Result
| Dimension | Value |
|---|---|
| Responsibility | none |
| Reasoning | consequentialist |
| Policy | none |
| Emotion | indifference |
| Coded at | 2026-04-27T06:24:53.388235 |
Raw LLM Response
[
{"id":"ytc_UgxbGiQ7f_q2DjcgcRZ4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_UgxVB3Dzq5wcpq-EZXZ4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"regulate","emotion":"outrage"},
{"id":"ytc_UgxTm_v3cmB-qGxh4zd4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"none","emotion":"fear"},
{"id":"ytc_UgwGCjVsAHTnB2EaMTl4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"resignation"},
{"id":"ytc_Ugxw8FlQK3bXijZ48zZ4AaABAg","responsibility":"none","reasoning":"unclear","policy":"none","emotion":"mixed"},
{"id":"ytc_UgzjRXSMiV6Xr-kL9eB4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},
{"id":"ytc_UgzUqzaWjpxXy3Yp6hh4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"fear"},
{"id":"ytc_UgwmGF6dhGjM9vhARUV4AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"resignation"},
{"id":"ytc_UgyiTW_WGqdmj3Lo4N54AaABAg","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"outrage"},
{"id":"ytc_UgylflwkIbC1qc8YX8B4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"liability","emotion":"fear"}
]