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Not directly related but still kind of, I've more or less settled on Gemini lately and often use it "for fun", not to do the task but see if it could do it better than me and or in novel or efficient way. NotebookLM and Canvas work nicely and it felt easy to use.

I've been absurdly surprised at how good it is at things, and how bad it is at others, and notably that the thing it seems the worst at are the easy picking parts.

Let me give an exemple; I was checking with it the payslip of my employees for the last few months, various wires related to their salaries and the various taxes, and my social declaration papers for labor taxes (which in France are very numerous and complex to follow).I had found a discrepency in a couple of declaration that ultimately led to a few dozen euros losts over some back and forth. Figuring it out by myself took me a while, and was not fun; I had the right accounting total and almost everything was okay, and ultimately it was a case of a credit being applied while an unrelated malus was also applied, both to some employees but not others, and the collision meant a pain to find.

Providing all the papers to gemini and asking it to check if everything was fine, it found me a bazillion "weird things", all mostly correct but worth checking, but not the real problem.

Giving it the same papers, telling him the problem I had and where to look without being sure, it found it for me with decent details, making me confident that next time I can use it not to solve it, but to be put on the right track much much faster than without gemini.

Giving it the same papers, the problem but also the solution I had but asking it to give me more details, again provided great result and actually helped me clarified which lines collided in which order, again not a replacement but a great add on. Definitely felt like the price I'm paying for it is worth it.

But here is the funny part : in all of those great analysis, it kept trying to tally me totals, and there was always one wrong. We're not talking impressive stuff here, but quite literal case of here is a 2 column 5 rows table of data, and here is the total, and the total is wrong, and I needed to ask it like 3 or 4 times in a row to fix its total until it agreed / found its issue (which was, literally).

Despite being a bit amused (and intrigued) at the "show thinking" detail of that, where I saw it do the same calculation in half a dozen different way to try and find how I came up with my number, it really showed to me how weirdly different from us those thing work (or "think", some would say).

It it's not thinking but just emergent behavior for text assimilation, which it's supposed to be, then it figuring it something like that in such details and clarity was impressive in a way I can't quite grasp. But if it's not that but a genuine thought process of some sort, how could he miss so many time the simplest thing beside being told.

I don't really have a point here, other than I used to know where I sat on "are the models thinking or not" and the waters have really been murkied for me lately.

There have been lots of talk about these things replacing employees or not, and I don't see how they could, but I also don't see how an employee without one could compete with one helped by one as an assistant; "throw ideas at me" or "here is the result I already know but help me figure out why". That's where they shine very brightly for me.



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