• gnuplusmatt@aussie.zone
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    1 year ago

    So we go back to the future and we stop Biff from stealing the time machine!

    We can’t, because if we travel into the future from this point in time…it will be the future of this reality…in which Biff is corrupt and powerful and married to your mother, and in which this has happened to me!

    No. Our only chance to repair the present is in the past at the point where the time line skewed into this tangent!

  • TrontheTechie@infosec.pub
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    1 year ago

    George Jetson had an 17 minute work day with 2 hours a week and could afford a house, a hover car, a robot maid, enough money for his wife to spend the day shopping on top of household needs, enough extra to take care of a dog, and STILL enough leftover to allow elroy to be involved in extracurricular activities and to take the family on a vacation to the moon.

    I worked two jobs at 50-60 hours a week and could only afford to rent a 1 bed apartment with almost nothing left over.

    I wish I had came of age in that period of post war optimism that inspired that cartoon.

    Edit: the Jetson’s takes place in the year 2062, we still have ~38 years or so to ensure our children can achieve that

    • Restaldt@lemmy.world
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      1 year ago

      And then you consider the flintstones crossover episode and realize that we are right on track for that reality

      Its just us peasants will be living on the surface in flintstone world

  • Squiglet@lemmy.world
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    1 year ago

    Yeah shouldn’t it have been the other way? AI for robots to take out the trash and cook and clean, and we’d be free for art and writing?

  • Maladius@lemmy.world
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    1 year ago

    What’s the hold up on my trash taking/dishes doing robot? Is object recognition still too slow? I heard there’d been strides with fuzzy logic there. Is power storage still a limiting factor?

    • howrar@lemmy.ca
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      1 year ago

      Object recognition is good enough for this kind of task now IMO. The problem is with controlling physical hardware, which is a problem typically handled by reinforcement learning. This is a difficult problem for current techniques mainly because of its sequential nature (i.e. what you need to do now depends on the state you’re in, which depends on what you did a second ago). Being sequential means you can’t easily take advantage of GPUs for parallelizing a huge amount of work like you can for image generation where you produce the entire thing at once.