76
Scientists Used AI to Find Hidden Earthquake Signals Along the San Andreas Fault (gizmodo.com)
submitted 4 months ago by to c/technology@lemmy.world
12 comments fedilink hide all child comments

all 14 comments

sorted by: hot top controversial new old
[–] 50 points 4 months ago (6 children)

before anyone immediately smashes "downvote" and comes here arms raised, "AI" includes ML, as in models specifically trained for this, and models have been around for 20+ years. AI != LLMs

  • permalink
  • fedilink
  • source
  • hideshow 6 child comments
    •
  • [–] 9 points 4 months ago* (2 children)

    One of the insanely powerful uses of AI is just parsing large amounts of data and looking for patterns. However it still requires human oversight and may overlook patterns also. I think this is the problem with AI in general: The vast majority of people can't be trusted to verify the results. Scientists are extremely thorough in general so that's probably fine.

    I had a family member arguing with me about a particular piece of law that I happened to be very familiar with. They are actually an attorney. And they flaunted that as if it made them right. The problem is they didn't even actually review the law, they just typed it into chat GPT. So they were breaking the law based on advice from a chat bot.

  • permalink
  • fedilink
  • source
  • parent
  • hideshow 2 child comments
    •
  • [+] 4 points 4 months ago (2 children)
    [deleted]
  • permalink
  • fedilink
  • source
  • parent
  • hideshow 2 child comments
    •
  • [–] 2 points 3 months ago (1 child)

    I disagree with your assessment. Modern machine learning methods will result in a far more complex algorithm than any human could device on their own. It will be "cheap" to execute, but only because of the vast amount of data it's been trained on. That's the strength. The raw number of calculations it can do per second means it can sift through more data in a day than a human could in its lifetime.

    The biggest danger is hidden local minimums that can potentially distort new results and findings. But that's not unique to machine learning. And you can let the AI grade its result with how certain it is. Automatically flag any result that falls below a certain threshold. And again, this is where the danger of local minimum come in. Because it can raise the certainty of results when maybe it shouldn't be so certain. Though you will find out quickly when results are false with high certainty. Then you go back and you keep working at it.

    As of this particular topic of earthquakes. There are no traditional tools of accurately predicting them. We've never been able to do it before. Now they think this might be able to. So we will just have to wait and see if its predictions are accurate or not.

  • permalink
  • fedilink
  • source
  • parent
  • hideshow 1 child comment
    •
    • load more comments (-1 replies)
    • load more comments (-1 replies)
  • [–] 7 points 4 months ago (2 children)

    Also, LLMs doesn’t equal generalist trained chatbots.

  • permalink
  • fedilink
  • source
  • parent
  • hideshow 2 child comments
    •
    • [–] 31 points 4 months ago (1 child)

    As usual, the term AI is used for Machine Learning. Nothing to do with the Techbros large scale language model dead end. Sad that a success like this could be misconstrued to be a Techbro success.

  • permalink
  • fedilink
  • source
  • hideshow 1 child comment
    •
  • [–] 8 points 4 months ago*

    They‘re based on the same principle and are therefore both AI or based on machine learning. The actual misconception comes from LLMs being treated as AI when they‘re just a product of machine learning. Both things are based on the same principles of pattern recognition and training data, though.

    The difference here is that scientist use machine learning for something useful while tech bros use it to make word salad generators.

  • permalink
  • fedilink
  • source
  • parent
    • [–] 16 points 4 months ago

    I hate that everyone just calls everything "AI" now. At this point, this term has basically lost its whole meaning. But I guess writing "Scientists Used Machine Learning to Find ..." is not as attention grabbing. Though "Machine Learning" is also a very broad term

  • permalink
  • fedilink
  • source
    •
    [–] -2 points 3 months ago (1 child)

    "Fuck AI... Already did that... the sensors must of improved. There will always be some word salad to explain away the skepticism but AI has yet to turn a profit. If it ain’t making dollars then it ain’t makin cents. We just got a lot of suckers but eventualy they will dry up." - Put that in the history books

  • permalink
  • fedilink
  • source
  • hideshow 1 child comment
    •
    • 3 comments in c/Aii@programming.dev view that post
    [–] 2 points 3 months ago

    That's exactly the kind of AI application I'd like to see more of.

  • permalink
  • fedilink
  • source
    •
    [–] 1 point 4 months ago (1 child)

    Hidden or hallucinated?

  • permalink
  • fedilink
  • source
  • hideshow 1 child comment
    •
    • 2 comments in c/artificial_intel@lemmy.ml view that post
    [–] 3 points 4 months ago (1 child)

    Factually incorrect. This phenomenon has been studied extensively over the last 2 or 3 decades by researchers and scientists in the PNW.

    Here's Nick Zentner talking about the clockwise rotation (and occasional counter rotation) of Washington and Oregon as part of a larger continental story

    https://youtu.be/r9recENBhiU?is=Kjp4pIVvF83NETOB

    Note this video was posted back in 2013.

  • permalink
  • fedilink
  • source
  • hideshow 1 child comment
    •