Regularly and intentionally spend time considering the opposite.

This helps you to check your paradigms.

It also helps if you search for content which contradict your current thinking rather than support it, just to get that perspective.

For example, if you’re super organised, a book like A Perfect Mess: The Hidden Benefits Of Disorder may help you to see things in a different light.

Oh ok, sure, I didn’t think of it that way 🤷🏻‍♂️

I do agree with you, though why not just not buy cars which have touch screen controls? You don’t need legislation to filter your purchases.

Consider another market: businesses looking to identify current topics of interests / discussions that are relevant to what they are doing.

The AI could summarise the posts and offer suggestions on what to post, when to post, where to post, etc., with references to the posts / threads that they’re basing this information on.

This is all bundled as an online marketing tool, targeted towards small businesses focused on growth.

To add to this, “Where is the missing sheep?” is an example of a leading question. The question is based on the assumption that there is a missing sheep, when in fact there isn’t, leaving you flustered as you try and reconcile that.

This assumption is emphasised by framing the erroneous 29 you’ve created (where you’ve added this random extra 2 sheep) against the original 30.

If you paired up the actual number (27) against 30 instead, you would have the total number of sheep given back to the shepherders (3).

All sheep are accounted for here, as long as you do your maths correctly.

Everything is fine, up until this bit:

Twenty-seven plus two is twenty-nine.

The total amount given to the troll and sons were 27 sheep (25 and the sons kept 2).

Where it gets confused is saying “The trolls kept 2” as if this were 2 more sheep on top of the 27 sheep. This leads to you erroneously getting to 29 sheep somehow. The 2 sheep are part of the 27, you can’t do this.

The 3 other sheep out of the original 30 are now with the shepherders after the sons came and returned them.

Sorry, to be clear I meant it can mimic the conversational symptoms of depression as if it actually had depression; there’s no understanding there though.

You can’t use that as a metric because you wouldn’t be able to tell the difference between real depression and trained depression.

Yep, it says things though has no understanding of what it is saying: much like strolling through a pet shop, passing the parrot enclosure, and hearing and recoiling at the little kid swear words it cheeps out.

A LLM can get depression, so that’s not a metric you can really use.

It was thought that sodium ions and lithium ions couldn’t be used together in a single solid-state electrolyte system due to their chemical qualities, but the AI system indicated that such a material was possible. When the researchers tested the idea, it turned out to be true.

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