4 ms·

So it like just does the pure unicode or...I don't want to embarass myself by further explicating unassissted llol

• Drakim 3y ago
  Well, it's just float values while it's being transformed from node to node but ultimately those floats are exchanged for tokens. Tokens as kinda like letters except certain common combinations are clumped together based on how frequently they are used in human language. So "I" and "a" are likely tokens even though they are just one letter, while hamster is most likely two tokens of "ham" and "ster". I think it's just done for efficiency, since it reduces amount of variations by a great deal not having to have a separate value for every single letter. The amount of nodes that needs to interact with the value for "dog" is a lot smaller than the amount of nodes that needs to interact with the value for "d", thus the neutral network can be a lot more effective. But those tokens are translated to unicode before it's printed out to humans as the end result.
  • Obscurity4340 3y ago
    Who DISCOVERED discovered this approach?
    • Drakim 3y ago
      No idea, you'll have to google up the history, but this approach has been toyed around with for ages. Neutral networks are absolutely not new, you can find tons of youtubes of people making small creatures that use neural networks to find food in a simulated environment. The revolution, from what I understand, comes from new techniques to very quickly grade good/bad behavior so you don't need a human to mark every result as good or bad as it's being trained.