4 ms·

I'm calling it now, these models will just grow and grow, their responses are reflexive probabilistic responses. HN will scream its not a AI since it doesn't un

I'm calling it now, these models will just grow and grow, their responses are reflexive probabilistic responses. HN will scream its not a AI since it doesn't understand the world, then we will discover that human beings are just reflexive probabilistic machines. And the dumber reflexivity (which is what the models have (or rather dumber humans have)) are not logically incorrect, they just arent complex enough to hold all the information, but still very good at spitting out what is there. A deep understanding of human intelligence I believe will reveal that this is the case, and humanity will be cracked open

tetris11 4y ago
After reading the Google Lamda transcripts, and genuinely believing the AI there to be sentient, I question how people judge the sentience of others
- zaptrem 4y ago
  Lambda and these language models are not currently capable maintaining an internal train of thought that isn't expressed as token context. It has no memory of the world other than what we tell it to have. It can only "think" as long as it takes to infer a token. I think these big language models might get closer to something we would all call sentience once they can refer directly to their weights' previous activations for context instead of just tokens.
  - naasking 4y ago
    > Lambda and these language models are not currently capable maintaining an internal train of thought that isn't expressed as token context. Why would that necessarily be insufficient for sentience? Sentience is just about the ability to "feel". Whatever "feeling" is, mechanistically, it will be some process that accepts some information and produces some output for these "feelings". It's not obvious that any kind of "memory" has to be part of the input to that process. For all we know, the transformer model is producing feelings as it computes, ie. that the next generated word is selected because it "feels right", where "feels right" simply means it's the most statistically likely word to follow the current token. Can you prove that this isn't basically what that gut feeling is for people? We don't actually know what "feelings" are fundamentally, so most of the people dismissing LaMDA's sentience don't really understand the can of worms they just stepped in.
    - cscurmudgeon 4y ago
      The burden of evidence is on proving "feelings" existing in these models rather than proving "feelings" NOT existing in these models.
      - naasking 4y ago
        The burden of proof is on anyone making firm claims, whether they are claiming these models do or do not have feelings.
        cscurmudgeon 4y ago
        No one was making claims till the guy from Google made the first claim.
    - visarga 4y ago
      > We don't actually know what "feelings" are fundamentally I bet feelings are value functions - they estimate the expected future reward from a given state. As we move from self-supervised to RL, AIs will get feelings. But they are always task dependent, the system of values is built around goals and past experience, it's not something that can be separated from the specifics of the case. Humans come preloaded with reward signals that guide the development of feelings. We got our goals in-built - to survive, to thrive, to self replicate, and then all the sub-goals necessary to achieve the main directives - to move around and manipulate objects, to be social, to obtain food, etc.
      - naasking 4y ago
        A plausible abstract description, but what are the specific properties of value function that create the feeling? We need that mechanistic understanding to avoid creating feelings when we don't want a sentient system. More than likely this will make the system less effective at certain tasks as well, but the ethics around this are unclear and can only be discussed once that mechanistic understanding becomes clear.
  - woojoo666 4y ago
    Was it sentient during training though?
visarga 4y ago
I am sure humans are just reflexive probabilistic machines but we have one major advantage - we are embodied in a complex environment, both physical and social. The environment allows simple reflexive inferences to align to real outcomes / grounds the model. Maybe we need to build an android baby and raise it as part of human society to get similar benefits for AI. As it stands, AI has no "skin in the game" so to speak, it doesn't optimize rewards and has nothing to lose. Predicting the next word has its limits, a model can't design and try new experiments like human agents, a static training dataset is dead while the world is alive. Even AlphaGo was limited while doing imitation learning, but surpassed humans training from scratch by accessing a Go environment (table + opponent). The environment is the real teacher.
woojoo666 4y ago
In case you haven't seen it yet, there's a popular article that echoes the same idea called The Scaling Hypothesis [1] [1]: https://news.ycombinator.com/item?id=31564033 https://news.ycombinator.com/item?id=31564033

tetris11 4y ago

After reading the Google Lamda transcripts, and genuinely believing the AI there to be sentient, I question how people judge the sentience of others

zaptrem 4y ago
Lambda and these language models are not currently capable maintaining an internal train of thought that isn't expressed as token context. It has no memory of the world other than what we tell it to have. It can only "think" as long as it takes to infer a token. I think these big language models might get closer to something we would all call sentience once they can refer directly to their weights' previous activations for context instead of just tokens.
- naasking 4y ago
  > Lambda and these language models are not currently capable maintaining an internal train of thought that isn't expressed as token context. Why would that necessarily be insufficient for sentience? Sentience is just about the ability to "feel". Whatever "feeling" is, mechanistically, it will be some process that accepts some information and produces some output for these "feelings". It's not obvious that any kind of "memory" has to be part of the input to that process. For all we know, the transformer model is producing feelings as it computes, ie. that the next generated word is selected because it "feels right", where "feels right" simply means it's the most statistically likely word to follow the current token. Can you prove that this isn't basically what that gut feeling is for people? We don't actually know what "feelings" are fundamentally, so most of the people dismissing LaMDA's sentience don't really understand the can of worms they just stepped in.
  - cscurmudgeon 4y ago
    The burden of evidence is on proving "feelings" existing in these models rather than proving "feelings" NOT existing in these models.
    - naasking 4y ago
      The burden of proof is on anyone making firm claims, whether they are claiming these models do or do not have feelings.
      - cscurmudgeon 4y ago
        No one was making claims till the guy from Google made the first claim.
  - visarga 4y ago
    > We don't actually know what "feelings" are fundamentally I bet feelings are value functions - they estimate the expected future reward from a given state. As we move from self-supervised to RL, AIs will get feelings. But they are always task dependent, the system of values is built around goals and past experience, it's not something that can be separated from the specifics of the case. Humans come preloaded with reward signals that guide the development of feelings. We got our goals in-built - to survive, to thrive, to self replicate, and then all the sub-goals necessary to achieve the main directives - to move around and manipulate objects, to be social, to obtain food, etc.
    - naasking 4y ago
      A plausible abstract description, but what are the specific properties of value function that create the feeling? We need that mechanistic understanding to avoid creating feelings when we don't want a sentient system. More than likely this will make the system less effective at certain tasks as well, but the ethics around this are unclear and can only be discussed once that mechanistic understanding becomes clear.
- woojoo666 4y ago
  Was it sentient during training though?

visarga 4y ago

I am sure humans are just reflexive probabilistic machines but we have one major advantage - we are embodied in a complex environment, both physical and social. The environment allows simple reflexive inferences to align to real outcomes / grounds the model. Maybe we need to build an android baby and raise it as part of human society to get similar benefits for AI. As it stands, AI has no "skin in the game" so to speak, it doesn't optimize rewards and has nothing to lose. Predicting the next word has its limits, a model can't design and try new experiments like human agents, a static training dataset is dead while the world is alive. Even AlphaGo was limited while doing imitation learning, but surpassed humans training from scratch by accessing a Go environment (table + opponent). The environment is the real teacher.

woojoo666 4y ago

In case you haven't seen it yet, there's a popular article that echoes the same idea called The Scaling Hypothesis [1] [1]: https://news.ycombinator.com/item?id=31564033 https://news.ycombinator.com/item?id=31564033