KingRandomGuy

@KingRandomGuy@lemmy.world

• ⁨Comment⁩ on ⁨Pokemon Legends Z-A's visuals aren't "great" say former Nintendo marketing leads, but hope Switch 2 could allow Game Freak to "go back to the drawing board"⁩ ⁨⁨2⁩ ⁨weeks⁩ ago⁩:

  IIRC BOTW was built on MonolithSoft’s engine (the devs behind Xenoblade) so in fairness, those games are more-so the same exception rather than the rule. That said, even without the comparison, GameFreak clearly did not properly optimize the Pokemon games on switch, with stuff like loading the whole map’s ocean at any given time.

• ⁨Comment⁩ on ⁨The science is divided⁩ ⁨⁨5⁩ ⁨weeks⁩ ago⁩:

  Yep this is the exact issue. This problem comes up frequently in a first discrete math or formal mathematics course in universities, as an example of how subtle mistakes can arise in induction.

• ⁨Comment⁩ on ⁨The science is divided⁩ ⁨⁨5⁩ ⁨weeks⁩ ago⁩:

  Exactly, the assumption (known as the inductive hypothesis) is completely fine by itself and doesn’t represent circular reasoning. The issue in the “proof” actually arises from the logic coming after this, in which they assume that they can form two differeny overlapping sets by removing a different horse from the total set of horses, which fails if n=2 (as then they each have a distinct element).

• ⁨Comment⁩ on ⁨Nintendo sues a streamer for streaming ten games before their release⁩ ⁨⁨4⁩ ⁨months⁩ ago⁩:

  Sony v Connectix is the actual case that set the precedent for emulation, not Bleem. The Bleem case decided whether or not the use of screenshots of copyrighted games to advertise their emulator was legal. I believe it just deferred to the Connectix case for the legality of the emulator.

• ⁨Comment⁩ on ⁨Nobel Prize 2024⁩ ⁨⁨5⁩ ⁨months⁩ ago⁩:

  I work in an ML-adjacent field (CV) and I thought I’d add that AI and ML aren’t quite the same thing. You can have non-learning based methods that fall under the field of AI - for instance, tree search methods can be pretty effective algorithms to define an agent for relatively simple games like checkers, and they don’t require any learning whatsoever.

  Normally, we say Deep Learning (the subfield of ML that relates to deep neural networks, including LLMs) is a subset of Machine Learning, which in turn is a subset of AI.

  Like others have mentioned, AI is just a poorly defined term unfortunately, largely because intelligence isn’t a well defined term either. In my undergrad we defined an AI system as a programmed system that has the capacity to do tasks that are considered to require intelligence. Obviously, this definition gets flaky since not everyone agrees on what tasks would be considered to require intelligence. This also has the problem where when the field solves a problem, people (including those in the field) tend to think “well, if we could solve it, surely it couldn’t have really required intelligence” and then move the goal posts. We’ve seen that already with games like Chess and Go, as well as CV tasks like image recognition and object detection at super-human accuracy.