5 ms·
If you invent/introduce made up concepts and rules on the spot ("let shmerple be ..."), which can't possibly be found in its training data, then, from my experi
by kgeist 3y ago
If you invent/introduce made up concepts and rules on the spot ("let shmerple be ..."), which can't possibly be found in its training data, then, from my experience, when queried, LLMs are able to correctly reason most of the time... So it's not just Markov chains regurgitating sentences verbatim from their dataset.
Even if this kind of intelligence is just statistics, does it really matter? If it quacks like a duck, it's a duck. Maybe our own brains are nothing more than overrated statistical machines?
The only issue I see with the hype is when people attempt to anthromorphize it.
- throwaway22032 3y agoYeah, it's bizarre. Are we not simply employing statistics when we deduce that yes, if we release our grip, the smartphone will fall to the floor? You wouldn't have to ever see a phone drop in order to know that, and neither would you have to study or know of the terminology of gravity. It comes from the statistical knowledge that all things fall when not blocked.
- 1000thVisitor 3y agoThe key here is abstraction, not statistics. You have seen other items fall and are able to abstract this and then apply it to the phone.
- sharemywin 3y ago1. Rule of probability: The concept of statistics is being used to predict outcomes based on previous observations or experiences, such as the likelihood of an object falling when released. 2. Rule of inherent knowledge: Some understanding or knowledge, like objects falling when not supported, can be known without explicit study or exposure to the specific terminology (e.g., gravity). 3. Rule of generalization: Observations or experiences with one type of object (e.g., a smartphone) can be generalized to other objects or situations, as long as they share similar characteristics (e.g., not being supported). 4. Rule of causality: There is an implied cause-and-effect relationship between an action (releasing the grip) and an outcome (the smartphone falling to the floor). 5. Rule of experiential learning: Knowledge can be gained through direct experiences, even if the specific terms or scientific concepts are not known.
- thom 3y agoWhy would LLMs not learn abstractions when given millions of of concrete examples?
- deleted 3y ago[deleted]
- milchek 3y agoSome great points, and this is where these discussion can get into the freewill vs determinism arena. If you’re more of a determinist, then human brains are basically like organic LLMs and we’re just unique models trained on our own life’s datasets - with other traits/data like preferences and biases also being inherited via genetics, of course.
- chpatrick 3y agoIs it wrong to anthromorphize if it quacks like a human?
- famouswaffles 3y agoNot only is it not wrong, it's actually in our best interests to do so past a certain level of agency, embodiment and unsupervised tool control. If the machine acts like it has emotions, runs forever(this kind of agency is already possible to implement though expensive) and can use tools, then treat it like it doesn't have emotions at your own peril. When the machine can "hit you back" (not necessarily physically of course), you'll learn manners pretty quickly. You can see glimpses of this with bing.
- hammyhavoc 3y ago> You can see glimpses of this with bing. Oh please. The human gives the verbose output meaning by projecting onto it. You're clearly letting your emotions run wild. It's a fucking LLM.
- famouswaffles 3y agoReal word actions and consequences give the words meaning. If you're rude to Bing, the conversation will end. You can keep typing but it won't respond. Searching the web and ending conversations are the only two actions Bing can currently do so what i'm saying is less applicable for now. But humanity is gearing up to give more and more control of more and more tools to increasingly powerful LLMs. Hell Bing is scheduled a bump in tools in the coming weeks. Hate to break it to you but "it's not real [insert property]" is not a shield. Not when you allow the machines to interact with the real world. If your words to [insert LLM] guide responses that perform actions detrimental to you then those actions are no less real or detrimental because you've deluded yourself into thinking "it's not real understanding" is an intelligent argument.
- hammyhavoc 3y agoSo? This is a guardrail added by a Microsoft employee, mate. After their earlier dabblings in AI outputting bigotry and general toxicity, someone in their wisdom saw the sense to try and prevent going down a negative conversation path, hence all the edge lords on Reddit offering prompts to "jailbreak" an LLM and bypass the guardrails, which then get patched by a human being not long after. You're projecting so much meaning onto something that is functioning as designed by throwing a sentiment var into the calculation, just like you can measure "sentiment" with social media analysis tools to get a feel for which way the wind is blowing or which of the millions of tweets at your brand might be worth prioritizing. Do you really believe you've thus offended an LLM? That is delusional.
- version_five 3y ago> Maybe our own brains are nothing more than overrated statistical machines? This is a tired assertion, easily disproved for current llms (read some of Lecun's stuff) and if some variation is going to be claimed, it needs to be an affirmative defence. "Maybe x is true" is a meaningless statement.
- bheadmaster 3y ago> "Maybe x is true" is a meaningless statement. How so? If we don't know what "real intelligence" consists of, how can we know that LLMs can't have "real intelligence"?
- lewhoo 3y agodoes it really matter? If it quacks like a duck, it's a duck I think it absolutely matters if by only quacking we also want to know is it possibly wanting, feeling, experiencing, having an ego etc. You say LLMs are able to reason, but https://youtu.be/QO2BvVq_fWU?t=663 https://youtu.be/QO2BvVq_fWU?t=663 here is a proponent of the more simplistic explanation of how they work. On one hand I saw pretty convincing arguments for it having the ability to reason, on the other hand how do we even conclude anything if we can't really know what's in the training data.
- version_five 3y agoAlso want to add: ELIZA: How do you do. Please tell me your problem. YOU: I'm worried about shmerple ELIZA: Do you believe it is normal to be worried about shmerple ? The fact that it can insert your made up word into patterns has no significance in itself.
- unsupp0rted 3y agoChatGPT answers the way a human might: > I'm sorry to hear that you're worried about someone named "shmerple." Can you please provide me with more information about who shmerple is and why you're worried about them?
- c22 3y agoSorry, but this doesn't sound like any human I've ever spoken to.
- unsupp0rted 3y agoHow would a human, say the receptionist at your dentist's office who doesn't know you at all, respond to something like this? First question would be: is Shmerple a person or a concept, and assume it's a person, since most people don't start conversations about worrying about concepts. Therefore: who is Shmerple and why are you worried about them?
- c22 3y agoSure, your sentence sounded human to me. It's not the content I'm looking at, but the delivery.