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thoughts on arpgs?
  • Well if you liked PoE I doubt you'll like D4. It's a much simpler game. Sadly my only advice is to try GD and Last Epoch again. I've got hundreds of hours in the former and I just got 10 hours into the latter.

    Last Epoch feels like a more approachable PoE. I thoroughly enjoy how the skills interplay with one another, but I still prefer the itemization in Grim Dawn.

    The only reason I'm not playing GD currently is because I have too many QoL mods installed so my cloud saving doesn't work, but I can cloud save for Last Epoch for my steam deck lmao.

  • [Purchased Bambu A1 mini] Low End FDM for Miniatures, Hobby Parts, and Messing Around?
  • I'm not sure I agree here - I think the resin printer might not be a good entry point, but I'm curious to hear what others think. I've heard resin printers require special ventilation and the photo-resin is carcinogenic. Once dialed in, an FDM can do pretty great for detailed parts. Especially with a smaller nozzle. So I'm not convinced jumping straight into a resin printer is wise.

    I used my Ender 3 for a few years making miniatures, and they came out pretty great. Of course, then I tried switching to a larger nozzle and I still haven't managed to get it running... but that's my fault.

  • World's first bioprocessor uses 16 human brain organoids for ‘a million times less power’ consumption than a digital chip
  • It's a bunch of neurons that speak to a computer with a microelectrode array. So they "speak to" the neurons with electric impulses, and then "listen to" what they have to say. The computer it's connected to uses binary, but the neurons are somewhere in between. Yes, the change in electrical potential is analog, but neurons are typically in their "on" state, recovering from their "on" state, or just chilling out.

    The brain is incredible because of the network of connections between neurons that store information. It'll be interesting to see if a small scale system like this can be used for anything larger scale.

  • World's first bioprocessor uses 16 human brain organoids for ‘a million times less power’ consumption than a digital chip
  • Believe it or not, I studied this in school. There's some niche applications for alternative computers like this. My favorite is the way you can use DNA to solve the traveling salesman problem (https://en.wikipedia.org/wiki/DNA_computing?wprov=sfla1)

    There have been other "bioprocessors" before this one, some of which have used neurons for simple image detection, e.g https://ieeexplore.ieee.org/abstract/document/1396377?casa_token=-gOCNaYaKZIAAAAA:Z0pSQkyDBjv6ITghDSt5YnbvrkA88fAfQV_ISknUF_5XURVI5N995YNaTVLUtacS7cTsOs7o. But this seems to be the first commercial application. Yes, it'll use less energy, but the applications will probably be equally as niche. Artificial neural networks can do most of the important parts (like "learn" and "rememeber") and are less finicky to work with.

  • Do 9-5 jobs still exist in the U.S.?
  • My job is 8:30 - 5 with a 30 minute lunch break. So almost.

    But, we also get 2 days/week at home, and can flex time as required. Tons of international work, so the flexible hours are a godsend when time zones are against us.

    It's a salaried position and depending on your supervisor and stage of your career, you're expected to work 40-45 hours a week. Deadlines and ugly projects tend to increase hours work. I'm very lucky, as my industry can be pretty brutal with sudden ends to projects and unexpected layoffs.

  • After announcing increased prices, Spotify to Pay Songwriters About $150 Million Less Next Year
  • Thanks for the recommendation, I was worried they would be missing some of my artists but they had 99% of my music. Can't wait to ditch Spotify.

    ETA: dear lord the sound quality is so much better. I had no idea what I was missing.

  • Why can't people make ai's by making a neuron sim and then scaling it up with a supercomputer to the point where it has a humans number of neurons and then raise it like a human?
  • We've got some really good theories, though. Neurons make new connections and prune them over time. We know about two types of ion channels within the synapse - AMPA and NMDA. AMPA channels open within the post-synapse neuron when glutamate is released by the pre-synapse neuron. And the AMPA receptor allows sodium ions into the dell, causing it to activate.

    If the post-synapse cell fires for a long enough time, i.e. recieves strong enough input from another cells/enough AMPA receptors open, the NMDA receptor opens and calcium enters the cell. Typically an ion of magnesium keeps it closed. Once opened, it triggers a series of cellular mechanisms that cause the connection between the neurons to get stronger.

    This is how Donald Hebb's theory of learning works. https://en.wikipedia.org/wiki/Hebbian_theory?wprov=sfla1

    Cells that fire together, wire together.

  • Why can't people make ai's by making a neuron sim and then scaling it up with a supercomputer to the point where it has a humans number of neurons and then raise it like a human?
  • Actually, neuron-based machine learning models can handle this. The connections between the fake neurons can be modeled as a "strength", or the probability that activating neuron A leads to activation of neuron B. Advanced learning models just change the strength of these connections. If the probability is zero, that's a "lost" connection.

    Those models don't have physical connections between neurons, but mathematical/programmed connections. Those are easy to change.

  • Why can't people make ai's by making a neuron sim and then scaling it up with a supercomputer to the point where it has a humans number of neurons and then raise it like a human?
  • It's not a terrible idea by any means. It's pretty hard to do, though. Check out the Blue Brain Project. https://en.wikipedia.org/wiki/Blue_Brain_Project?wprov=sfla1

    ETA: not to mention the brain is a heck of a lot more than a collection of neurons. Other commenters pointed out how we just discovered a new kind of brain cell - the brain is filled with so many different types of neurons (e.g. pyramidal, Purkinje, dopamine-based, myelinated, unmyelinated, internet Ron's, etc.). Then there's an entire class of "neuron support" cells called neuralgia. This includes oligodendrocytes (and Schwann cells), microglia, satellite cells, and most importantly, astrocytes. These star-shaped cells can have a huge impact on how neurons communicate by uptaking neurotransmitters and other mechanisms.

    Here's more info: https://en.wikipedia.org/wiki/Tripartite_synapse?wprov=sfla1

  • Why can't people make ai's by making a neuron sim and then scaling it up with a supercomputer to the point where it has a humans number of neurons and then raise it like a human?
  • Heck, we barely know how neurons work. Sure, we've got the important stuff down like action potentials and ion channels, but there's all sorts of stuff we don't fully understand yet. For example, we know the huntingtin protein is critical to neuron growth (maybe for axons?), and we know if the gene has too many mutations it causes Huntington's disease. But we don't know why huntingtin is essential, or how it actually effects neuron growth. We just know that cells die without it, or when it is misformed.

    Now, take that uncertainty and multiply it by the sheer number of genes and proteins we haven't fully figured out and baby, you've got a stew going.

  • InitialsDiceBearhttps://github.com/dicebear/dicebearhttps://creativecommons.org/publicdomain/zero/1.0/„Initials” (https://github.com/dicebear/dicebear) by „DiceBear”, licensed under „CC0 1.0” (https://creativecommons.org/publicdomain/zero/1.0/)NE
    Neuromancer49 @midwest.social
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