Curt Doolittle

Theme: AI

  • SERIOUSLY GPT4 CAN EXPLAIN MY WORK… AND IT”S CORRECT. … FASCINATING –“How d

    SERIOUSLY GPT4 CAN EXPLAIN MY WORK… AND IT”S CORRECT. … FASCINATING

    –“How does philosopher and social scientist curt doolittle define decidabilty?”–

    Curt Doolittle, the philosopher and social scientist who developed the theory of Propertarianism, uses the concept of “operationalism” to define decidability. According to Doolittle, operationalism is the principle that concepts and propositions should be defined in terms of the physical operations that can be used to verify or falsify them.

    In this context, decidability can be understood as the ability to determine whether a proposition or statement is true or false through a physical operation or test. Doolittle emphasizes that operational definitions are essential for achieving clarity and rigor in scientific and philosophical discourse, and that they allow for the development of empirical and testable theories.

    In the context of Propertarianism, decidability is closely related to the concept of “testimonialism,” which is the idea that knowledge can be obtained through testimony and can be verified through empirical tests. Doolittle argues that the ability to verify claims through empirical tests is essential for achieving objective knowledge and for overcoming biases and errors in human reasoning.

    Overall, Doolittle’s theory of operationalism and testimonialism provides a framework for defining decidability in terms of physical operations and empirical tests, which can be used to verify or falsify claims about the world.

    Source date (UTC): 2023-03-31 14:40:51 UTC

    Original post: https://twitter.com/i/web/status/1641812809490083842

  • CHAT GPT-4 EXPLAINS MY WORK BETTER THAN I DO. 😉 –“How does philosopher and soc

    CHAT GPT-4 EXPLAINS MY WORK BETTER THAN I DO. 😉

    –“How does philosopher and social scientist curt doolittle define truth?”–

    Curt Doolittle is a philosopher and social scientist who has developed a theory of truth known as Propertarianism. According to Doolittle, truth can be defined as the degree to which a statement or belief corresponds to reality, where reality is understood as the set of objective, observable, and measurable phenomena.

    Doolittle’s theory of truth is based on the idea that truth is a pragmatic tool that allows humans to cooperate and coordinate effectively in social groups. In his view, truth is essential for social cooperation because it enables people to have a shared understanding of the world and to make accurate predictions about the consequences of their actions.

    Doolittle argues that the degree of truth of a statement or belief can be assessed based on its coherence with other statements or beliefs, its empirical support, and its ability to generate successful predictions about reality. He also emphasizes the importance of using the scientific method to test and verify claims about reality, as well as the need to use clear and precise language to avoid confusion and ambiguity.

    Overall, Doolittle’s theory of truth is grounded in a pragmatic and empirical approach to knowledge, which emphasizes the importance of accuracy, coherence, and empirical evidence in assessing the truth of statements or beliefs.

    Source date (UTC): 2023-03-31 14:37:25 UTC

    Original post: https://twitter.com/i/web/status/1641811942892290049

  • CHAT GPT-4 EXPLAINS MY WORK BETTER THAN I DO. 😉 –“How does philosopher and soc

    CHAT GPT-4 EXPLAINS MY WORK BETTER THAN I DO. 😉

    –“How does philosopher and social scientist curt doolittle define truth?”–

    Curt Doolittle is a philosopher and social scientist who has developed a theory of truth known as Propertarianism. According to Doolittle, truth can be defined as the degree to which a statement or belief corresponds to reality, where reality is understood as the set of objective, observable, and measurable phenomena.

    Doolittle’s theory of truth is based on the idea that truth is a pragmatic tool that allows humans to cooperate and coordinate effectively in social groups. In his view, truth is essential for social cooperation because it enables people to have a shared understanding of the world and to make accurate predictions about the consequences of their actions.

    Doolittle argues that the degree of truth of a statement or belief can be assessed based on its coherence with other statements or beliefs, its empirical support, and its ability to generate successful predictions about reality. He also emphasizes the importance of using the scientific method to test and verify claims about reality, as well as the need to use clear and precise language to avoid confusion and ambiguity.

    Overall, Doolittle’s theory of truth is grounded in a pragmatic and empirical approach to knowledge, which emphasizes the importance of accuracy, coherence, and empirical evidence in assessing the truth of statements or beliefs.

    Source date (UTC): 2023-03-31 14:37:25 UTC

    Original post: https://twitter.com/i/web/status/1641811942720274435

  • THE DISPROPORTIONATE SUCCESS OF LANGUAGE MODELS (reverse engineering turns out t

    THE DISPROPORTIONATE SUCCESS OF LANGUAGE MODELS
    (reverse engineering turns out to work)

    Kind of humorous that in training GPT we are running out of training data. 😉

    We have voice and image as well as text now. we are working on video.

    So I’ve always thought we’d have to start with embodiment and build up to language, but OpenAI uses language models to start with language and work backward – to embodiment (the set of possible physical, cognitive, and emotional changes in state.)

    But it turns out the number of parameters (like dimensions of language) needed is smaller than we thought.

    Similarly, developers are discussing the possible limit of tokens (input data) is limited.

    So, I wonder if we can simple reduce embodiment to a small number of parameters that describe all human possible changes in state, whether physical, or emotional, and possibly logicl.

    If that’s true then the ‘working backward from language’ might get us to AGI. And that’s … well, at least unexpected by me.

    Cheers

    Source date (UTC): 2023-03-31 14:36:10 UTC

    Original post: https://twitter.com/i/web/status/1641811631381311490

  • THE DISPROPORTIONATE SUCCESS OF LANGUAGE MODELS (reverse engineering turns out t

    THE DISPROPORTIONATE SUCCESS OF LANGUAGE MODELS
    (reverse engineering turns out to work)

    Kind of humorous that in training GPT we are running out of training data. 😉

    We have voice and image as well as text now. we are working on video.

    So I’ve always thought we’d have to start with embodiment and build up to language, but OpenAI uses language models to start with language and work backward – to embodiment (the set of possible physical, cognitive, and emotional changes in state.)

    But it turns out the number of parameters (like dimensions of language) needed is smaller than we thought.

    Similarly, developers are discussing the possible limit of tokens (input data) is limited.

    So, I wonder if we can simple reduce embodiment to a small number of parameters that describe all human possible changes in state, whether physical, or emotional, and possibly logicl.

    If that’s true then the ‘working backward from language’ might get us to AGI. And that’s … well, at least unexpected by me.

    Cheers

    Source date (UTC): 2023-03-31 14:36:10 UTC

    Original post: https://twitter.com/i/web/status/1641811631205130243

  • Nothing to be scared of that I can see. This is the point in every tech where pe

    Nothing to be scared of that I can see.
    This is the point in every tech where people have ridiculously exaggerated fantasies of the future that are eventually neutralized by reality. I mean, if you go back to the beginning of the web era, the movies for example are ridiculous.
    Again, as far as I know we are seeing a improvement in man-machine interface. Until the thing is smarter than a doorstop, that’s all we’re going to see.
    It SHOULD have the same effect on our work as the smartphone, the internet, client-server, and desktop computers had. It will result in our work changing and some displacement, and some re-education. But it’s increasingly easy to understand machines because we keep improving the user interface and keep expanding the data we have access to.

    Source date (UTC): 2023-03-30 18:37:24 UTC

    Original post: https://twitter.com/i/web/status/1641509951905357839

    Replying to: https://twitter.com/i/web/status/1641508792054718464

  • Nothing to be scared of that I can see. This is the point in every tech where pe

    Nothing to be scared of that I can see.
    This is the point in every tech where people have ridiculously exaggerated fantasies of the future that are eventually neutralized by reality. I mean, if you go back to the beginning of the web era, the movies for example are ridiculous.
    Again, as far as I know we are seeing a improvement in man-machine interface. Until the thing is smarter than a doorstop, that’s all we’re going to see.
    It SHOULD have the same effect on our work as the smartphone, the internet, client-server, and desktop computers had. It will result in our work changing and some displacement, and some re-education. But it’s increasingly easy to understand machines because we keep improving the user interface and keep expanding the data we have access to.

    Reply addressees: @Getouttheway7

    Source date (UTC): 2023-03-30 18:37:24 UTC

    Original post: https://twitter.com/i/web/status/1641509951787917314

    Replying to: https://twitter.com/i/web/status/1641508792054718464

  • I’ve never, in my life, seen any tech release, spread and advance as vast as the

    I’ve never, in my life, seen any tech release, spread and advance as vast as the langauge models. This is insane(ly good).

    Source date (UTC): 2023-03-30 17:50:08 UTC

    Original post: https://twitter.com/i/web/status/1641498052836876296

  • Smart. Primary outstanding problem is similar to this model, which is that 2048

    Smart.
    Primary outstanding problem is similar to this model, which is that 2048 tokens is far too few. And the task queue serves the wayfinding by recursion question. And competition between found routes.
    Insight
    There is a most parsimonious constructive logic of first principles (laws) of all existence. In my work I’ve discovered that that set of laws is far smaller than we’d imagined.
    So there is a delta between our existing sum of knowledge and the FRAME we use for each discipline’s knowledge, and the most parsimonious versino of that knowledge, and the need for explanatory power to bridge the two (which is what gpt at least, appears to do reasonably well).

    Source date (UTC): 2023-03-30 14:02:49 UTC

    Original post: https://twitter.com/i/web/status/1641440847228190721

    Replying to: https://twitter.com/i/web/status/1641227655134560256

  • Smart. Primary outstanding problem is similar to this model, which is that 2048

    Smart.
    Primary outstanding problem is similar to this model, which is that 2048 tokens is far too few. And the task queue serves the wayfinding by recursion question. And competition between found routes.
    Insight
    There is a most parsimonious constructive logic of first principles (laws) of all existence. In my work I’ve discovered that that set of laws is far smaller than we’d imagined.
    So there is a delta between our existing sum of knowledge and the FRAME we use for each discipline’s knowledge, and the most parsimonious versino of that knowledge, and the need for explanatory power to bridge the two (which is what gpt at least, appears to do reasonably well).

    Reply addressees: @jgreenhall

    Source date (UTC): 2023-03-30 14:02:49 UTC

    Original post: https://twitter.com/i/web/status/1641440847110750210

    Replying to: https://twitter.com/i/web/status/1641227655134560256