Linux server admin, MySQL/TSQL database admin, Python programmer, Linux gaming enthusiast and a forever GM.

  • 7 Posts
  • 347 Comments
Joined 1 year ago
cake
Cake day: June 8th, 2023

help-circle







  • hay, grass or silage

    All of the above, as well as other feeds such as corn. That percentage includes pastures and growing crops for feed. Here’s a pretty good breakdown.

    Interestingly enough, if someone doesn’t care at all about veganism but wants to reduce agricultural land use, removing beef, lamb and dairy from their diet would be enough to get there (while continuing to eat chicken, fish, etc).

    sweeping, emotional appeals

    I don’t think my comment was very emotionally charged.

    Surely, there are stronger arguments against eating meat than that

    The power of an argument is determined by the reader. There’s compelling reasons in terms of zoonotic diseases and rampant antibiotic use, there’s other reasons from a moral point of view, there’s others in terms of environment (like this argument), there’s others in terms of human health, etc. Which one is convincing to which person depends entirely on what that person cares about.











  • So, first of all, thank you for the cogent attempt at responding. We may disagree, but I sincerely respect the effort you put into the comment.

    The specific part that I thought seemed like a pretty big claim was that human brains are “simply” more complex neural networks and that the outputs are based strictly on training data.

    Is it not well established that animals learn and use reward circuitry like the role of dopamine in neuromodulation?

    While true, this is way too reductive to be a one to one comparison with LLMs. Humans have genetic instinct and body-mind connection that isn’t cleanly mappable onto a neural network. For example, biologists are only just now scraping the surface of the link between the brain and the gut microbiome, which plays a much larger role on cognition than previously thought.

    Another example where the brain = neural network model breaks down is the fact that the two hemispheres are much more separated than previously thought. So much so that some neuroscientists are saying that each person has, in effect, 2 different brains with 2 different personalities that communicate via the corpus callosum.

    There’s many more examples I could bring up, but my core point is that the analogy of neural network = brain is just that, a simplistic analogy, on the same level as thinking about gravity only as “the force that pushes you downwards”.

    To say that we fully understand the brain, to the point where we can even make a model of a mosquito’s brain (220,000 neurons), I think is mistaken. I’m not saying we’ll never understand the brain enough to attempt such a thing, I’m just saying that drawing a casual equivalence between mammalian brains and neural networks is woefully inadequate.