384
Microsoft confirms an AI worm is propagating through Copilot and other MS apps | CSO Online (www.csoonline.com)
submitted 2 months ago by to c/technology@lemmy.world
76 comments fedilink hide all child comments
you are viewing a single comment's thread
view the rest of the comments
[–] 35 points 2 months ago (5 children)

if the instruction is messy fuzzy human language to a system that was not coded instruction by instruction but got generated and trained then there never is a way to differentiate instructions from data if i'm not mistaken

  • permalink
  • fedilink
  • source
  • parent
  • hideshow 5 child comments
    •
  • [–] 1 point 2 months ago (3 children)

    We know that some humans can be trained to do that just fine. Humans are natural neuronal networks. That implies, neuronal networks can in principle do it. We just don't have any human-capability artificial neuronal networks yet.
    LLMs might never get there. But humans aren't LLMs. If we ever manage to properly model a human brain, that probably will be able to do that task with human-level accuracy (which actually is pretty good if you only look at professionals of the filed).
    Hopefully, it doesn't actually need a human brain for the task - because modeling that might still be a century off.

  • permalink
  • fedilink
  • source
  • parent
  • hideshow 3 child comments
    •
  • [–] 6 points 2 months ago (2 children)

    A human brain model would never get us to a super computer, which is their intended goal.

    Our brains have about one exaflop of processing. The NVidia B300 has 15 petaflops of processing. Corresponding to 0.015 exa, you'd need 66 of the strongest GPUs on the market to match the processing power of one human brain.

    That's before considering context, current estimations would put the human brain at 2.5 petabytes of storage. The former B300 has 288 gigabytes of VRAM. Corresponding to 0.000288 of one human brain, the earlier expectation of 66 landing flat at 0.019 the storage of a human brain.

    Can arguments be made not all brain capacity is at VRAM at all times? Most likely. But context windows is the primary bottleneck, not compute

    Our brains are absolute monsters, we'd gain more from understanding how we can have this powerful of a machine on so little space. The bigger breakthrough would be brainbased processing of software, but I've not heard of anyone going that route - Probably because it's not feasible

  • permalink
  • fedilink
  • source
  • parent
  • hideshow 2 child comments
    •
  • [–] 2 points 2 months ago

    Human brains are also considerably more efficient than an artificial neural network. Most modern ones only replicate the function of a human brain and its neurons in the most basic of aspects.

    Things like encoding data itself in how the signal is transmitted are still pretty uncommon in artificial neural networks, for example.

    We'd probably need somewhere close to several times the size and computing power of a human brain to even start coming close with current technology, assuming that it is possible to begin with.

  • permalink
  • fedilink
  • source
  • parent
  • [–] 1 point 2 months ago

    Just a hundred years ago, we had one floating point operation per second in mechanical calculators. We got roughly 100 TFlops (fp16; probably much more accurate than human brain neurons) in a high-end gaming GPU now. That's 14 orders of magnitudes in a hundred years. I guess, 4 more orders of magnitude in another hundred years should be possible. We don't even have fusion power yet. A lot changes when power becomes a practically unlimited resource.

  • permalink
  • fedilink
  • source
  • parent