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Joined 1 year ago
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Cake day: June 4th, 2023

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  • Maybe chickpeas are expensive where you live, or maybe you miscalculated. Either way, take a look at my numbers for comparison.

    We can get a 3.63kg bag of chickpeas here for $7.49 (CAD). Assuming you fulfill all your Calorie and protein needs from chickpeas alone (2500 Calories and 150g protein per day), it comes out to about $600/year. That’s $1.64/day. In order to be $10/day, you’d have to pay 6x as much for your chickpeas, so that same 3.63kg bag would have to cost $45.50.


  • More variety in your diet is likely to always be superior to less. That goes for both kids and adults. The trouble with younger kids is that deficiencies can impact their development and have more severe long term consequences, and they’re also less capable of seeking out foods to fill that gap.










  • Is this an issue of executive dysfunction? Putting the cart back is such a trivial task that I have a hard time attributing it to laziness. It doesn’t sound like you’re doing it on purpose to be a dick either. Do you find that you sometimes can’t do other things that should also be trivially simple? Like getting up off the couch to grab something two feet away, or deciding that lunch is too complicated because you need to put it in the microwave? My partner and I have both gone through this for most of our lives and it really sucks, but it doesn’t have to be that way.



  • Before I started adblocking, I’d get “relevant” ads in that I can understand how someone of my age/gender might like it, but they’re never things I’d purchase myself. I just want a mostly empty home with as little visual stimulation as possible, and buying more stuff doesn’t help with that.

    So yeah, I’m definitely saying “ads don’t work for me”, but it’s probably only because these companies refuse to make ads targeted to people like me.


  • howrar@lemmy.catoAI@lemmy.mlDo I understand LLMs?
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    2 months ago

    mathematically “correct” sounding output

    It’s hard to say because that’s a rather ambiguous way of describing it (“correct” could mean anything), but it is a valid way of describing its mechanisms.

    “Correct” in the context of LLMs would be a token that is likely to follow the preceding sequence of tokens. In fact, it computes a probability for every possible token, then takes a random sample according to that distribution* to choose the next token, and it repeats that until some termination condition. This is what we call maximum likelihood estimation (MLE) in machine learning (ML). We’re learning a distribution that makes the training data as likely as possible. MLE is indeed the basis of a lot of ML, but not all.

    *Oversimplification.