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@null@piefed.au

• ⁨Comment⁩ on ⁨Argentina wants to monitor social media with AI to ‘predict future crimes’⁩ ⁨⁨22⁩ ⁨hours⁩ ago⁩:

  I feel like people are somehow stupider.

  In Australia in the 80s there was very strong opposition to the introduction of tax file numbers, similar to a social security number I guess - merely a unique identifier for tax paying citizens. It was considered an over reach by the government, and an unnecessary way to track and monitor citizens.

  Now 45 years later those same people who were resistant to this type of identifier, like my parents, are nodding along with the conservatives who are trying to implement AI surveillance everywhere saying how necessary it is to protect us all from evil crime doers.

• ⁨Comment⁩ on ⁨Do LLM modelers maintain a list of manual corrections fed by humans?⁩ ⁨⁨1⁩ ⁨day⁩ ago⁩:

  I don't know the answer and I don't know anything about how LLMs are tuned but I think the answer is probably partially yes.

  My supposition is:

  Instead of providing manual answers to specific questions, you modify the bot's approach to answering different types of questions.

  For example, if you ask "what color are bananas" the bot answers this by looking for discussions about the color of different fruits and selects the word that seems to be provided most often.

  Alternatively, if you ask "what is two plus two", when the bot parses the question it recognises that it's a math question, so instead of looking for text discussions of math, it converts it to an equation and returns the solution.

  Previously, I guess bots were answering the "how many r's" question in the text based kind of way, and the fix made the bot interpret it in a more mechanical / mathematic kind of way.

  It's a pretty salient demonstration of a bot's inability to reason. They're good at making sentences, but they can only emulate reasoning.