Scientists used to think so-called “slow slip events” were “theoretically impossible.” Now these subtle tectonic shifts could be the key to predicting future earthquakes.
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.
the greatest power of machine learning algorithms is the source of its greatest drawback. they are essentially heuristic models of something, constructed in a way that they are much cheaper to execute than a traditional algorithmic approach. this cheapness results in error, which for a lot of applications is fine because you can refine/check the result with more accurate tools, but it also means you can never just trust it like you can with more traditional tools. this problem is baked into the technology so theres no amount of scale that will make it go away, as we’ve seen time and again with LLMs. failing to understand this is the mistake most people make when it comes to “AI”, and results in all kinds of bad decision making. but in the hands of people who understand the limitations, machine learning can truly be a game changing technology. not chatbots though those are fucking stupid and i hope they go away when the bubble bursts.
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.
the greatest power of machine learning algorithms is the source of its greatest drawback. they are essentially heuristic models of something, constructed in a way that they are much cheaper to execute than a traditional algorithmic approach. this cheapness results in error, which for a lot of applications is fine because you can refine/check the result with more accurate tools, but it also means you can never just trust it like you can with more traditional tools. this problem is baked into the technology so theres no amount of scale that will make it go away, as we’ve seen time and again with LLMs. failing to understand this is the mistake most people make when it comes to “AI”, and results in all kinds of bad decision making. but in the hands of people who understand the limitations, machine learning can truly be a game changing technology. not chatbots though those are fucking stupid and i hope they go away when the bubble bursts.