Curt Doolittle

Theme: AI

  • (NLI Team) Interesting. Running sections through ChatGPT4 and it’s able to under

    (NLI Team)
    Interesting. Running sections through ChatGPT4 and it’s able to understand.

    PROMPT:
    Please explain the following passage:

    Variables:
    |Behavior|: Sensation > Perception > Valuation > Prediction, Reaction > Action > Cooperation > Competition > Survival(persistence).
    |Evolutionary Computation|: Conflict, Stress, Disequilbrium > Accumulation(physical) > Acquisition(life) > Cooperation(Sentient Life) > Evolutionary Consequence(ecology, selection, evolution).
    |Scale of Evolutionary Computation|: Individual > Others > Norms > Institutions > Civilizations
    |Means of Persistence|: Genetic(Genes, SNPs) > Epigenetic(Expression) > Neurological(Memory) > Habits(Responses) > Norms (others habits) > Traditions(Intergenerational) > Institutions(procedural) > Metaphysical presumptions

    ChatGPT’s Response
    This passage appears to be outlining a model or framework for understanding behavior and evolution from a computational perspective. Here’s a general interpretation of the main ideas:

    1. Behavior: The author suggests a sequence or process for behavior, starting with sensation (receiving information from the environment), followed by perception (interpreting this information), valuation (assigning value or importance to this information), prediction and reaction (anticipating and responding to future events based on this information), and finally action, cooperation, competition, and survival. This sequence seems to describe how organisms interact with their environment and with each other.

    2. Evolutionary Computation: The author proposes a model for evolution as a form of computation or problem-solving process. This process begins with conflict, stress, or disequilibrium, which leads to accumulation (in physical systems), acquisition (in living systems), and cooperation (in sentient or conscious systems). The outcome of this process is evolutionary change, which affects the ecology of the system and leads to natural selection and further evolution.

    3. Scale of Evolutionary Computation: The author suggests that this process of evolutionary computation can occur at different scales, from the individual to civilizations. This could be interpreted as a way of understanding how evolution operates at different levels of biological and social organization.

    4. Means of Persistence: The author outlines different mechanisms by which traits or behaviors can persist over time, from genetic and epigenetic factors (which affect the expression of genes), to neurological factors (such as memory), habits, norms, traditions, institutions, and metaphysical presumptions (presumably deeply held beliefs or assumptions).

    This passage seems to be an attempt to integrate concepts from various fields, including biology, psychology, sociology, and computer science, to create a comprehensive model of behavior and evolution.

    Some of the terms and ideas presented are complex and may not align with mainstream scientific understanding. The author also seems to use some terms in non-standard ways, which can make the passage difficult to understand.

    Source date (UTC): 2023-06-25 17:34:52 UTC

    Original post: https://twitter.com/i/web/status/1673021959049715716

  • ? I don’t. I do care about the evolution of the underlying technology as it appr

    ? I don’t. I do care about the evolution of the underlying technology as it approaches the ability to produce real time rendering including believable actors.

    Source date (UTC): 2023-06-22 00:07:57 UTC

    Original post: https://twitter.com/i/web/status/1671671328334655489

    Reply addressees: @sommatic @Rainmaker1973

    Replying to: https://twitter.com/i/web/status/1671670657770201091

  • (NLI Team) Just a reminder. Do not take the bait. The best negative reinforcemen

    (NLI Team)
    Just a reminder.
    Do not take the bait.
    The best negative reinforcement is ignoring.
    The algorithm reinforces cross-network comments.
    Share what’s smart. Ignore whats trolling.
    Don’t feed the nitwits and midwits.
    Mute is sufficient. Blocks are effective.
    Thanks. 😉

    Source date (UTC): 2023-06-21 21:24:48 UTC

    Original post: https://twitter.com/i/web/status/1671630268359139335

  • I shouldn’t respond because the algorithm then tries to connect our networks, wh

    I shouldn’t respond because the algorithm then tries to connect our networks, which just increases the number of nitwits and midwits I have to deal with.

    But in this case, I’ll just explain that you’re accusing me of playing for another team, with different morals, for emotional reasons, using feminine shaming, because that’s what you do.

    But the only team I play for is the referees, the judiciary, and the truth, whether your team or any other team likes it or not. You just can’t bear it. And I don’t want, care about, respect your shallow ignorant opinions any more than I do that of children. 😉

    -hugs.

    Reply addressees: @PaulHHenry @deesemonster @ModelYManiac @snopes @Starlink

    Source date (UTC): 2023-06-21 21:06:58 UTC

    Original post: https://twitter.com/i/web/status/1671625780856512513

    Replying to: https://twitter.com/i/web/status/1671624593742905344

  • AI TOLD YOU SO: “TRANSFORMERS’ PERFORMANCE WILL RAPIDLY DECAY WITH INCREASED TAS

    AI TOLD YOU SO: “TRANSFORMERS’ PERFORMANCE WILL RAPIDLY DECAY WITH INCREASED TASK COMPLEXITY.”

    They’re dumb. Really dumb. Anyone who has worked on language, especially search engine indexing, and the means by which LLMs tokenize and function, would recognize that these are… https://twitter.com/y0b1byte/status/1671148393194831872

    Source date (UTC): 2023-06-20 22:55:14 UTC

    Original post: https://twitter.com/i/web/status/1671290640045318144

  • Fewer Coders or More Code? 😉 AI code generation is the obvious mainstream direc

    Fewer Coders or More Code? 😉
    AI code generation is the obvious mainstream direction in the industry, and it’s so obvious because so much code is boilerplate transformation of data from one source to another with minor application of rules and manipulations. I mean, there are only so many language models, only so many data sources, only so many design patterns, and only so many code problems. And that’s why coding gets boring over the lifetime of your career. You rewrite the same nonsense with differen syntax over and over.
    Seriously. I just can’t figure out if half the coders are going to disappear or the volume of software is going to double. 😉

    Source date (UTC): 2023-06-20 21:29:54 UTC

    Original post: https://twitter.com/i/web/status/1671269164609069059

  • Sigh, Anthropic’s Claude fails the truth test. 🙁

    Sigh,
    Anthropic’s Claude fails the truth test. 🙁 https://t.co/dxdbrmOGbF

    Source date (UTC): 2023-06-20 14:19:22 UTC

    Original post: https://twitter.com/i/web/status/1671160818791243777

  • Joscha Bach @Plinz With The Right Answer – and some additional insights: Joscha

    Joscha Bach @Plinz With The Right Answer – and some additional insights:

    Joscha says we need:
    1) Individual (Personal) AI’s.
    2) That don’t lie.

    But…
    3) Joscha argues that there is no universal commensurability and therefore decidability in manners, ethics, and morals – but my work and our organization have demonstrated that’s not true – at least, that all conflicts over demonstrated interests are universally decidable independent of opinion. In-group moral bias may be an arbitrary evolutionary artifact. But cross-group (cross-individual) moral violations of substance are universally decidable. Leaving the only question open one of manners (signals).

    However…
    4) That, however, does not impact the choice of what’s preferable for you and good for you and yours at the scale of your agency.
    5) We know that the fundamental problem as ability and knowledge decrease is auto-associative prediction and the difficulty in compensating for ignorance, error, bias, wishful thinking, and self-and-other deception. Yet Personal AI’s can increase universal commensurability and increase cooperation by advising us on falsehoods, manners, and irreciprocities, and alternative solutions thus limiting much of the cooperative (if not productive) challenges of cooperation, whether interpersonal, social, economic, political, or strategic.

    Therefore…
    6) So Joscha’s point is more to be reduced to the importance of individual AI’s and the risk of corporate or government (or religious) AI’s that can be chartered with irreciprocities and malincentives, which only personal AI’s can defend us from.
    7) And that we can’t regulate what we don’t yet understand ( I think we can by prohibiting ai’s from lying and irreciprocities (criminal, ethical, and moral), and by limiting military AI’s to carrying out specific orders.)

    Cheers

    Curt Doolittle
    The Natural Law Institute
    The Science of Cooperation

    Source date (UTC): 2023-06-19 20:31:11 UTC

    Original post: https://twitter.com/i/web/status/1670892000617308161

  • The current LLMs that will run on a phone are relatively simple. But then, so is

    The current LLMs that will run on a phone are relatively simple. But then, so is the hardware on our phones. Even so, it’s clear we’ll be able to use locally running AIs in androids, robots, vehicles, military vehicles, missiles, planes, and satellites, faster than we’d assumed.

    Our LLMs are dumb as a rock. But we haven’t hit anything near the low-level limit of the tech yet. But as someone who has worked on these questions to one degree or another for decades, we still have three (hard) layers of problems to solve. While we’re seeing some simple evolution of wayfinding and recursion, we still don’t have episodic memory, prediction, and judgment (morality) – and those are pretty hard problems.

    Basically, we’d thought we’d need to build AI bottom up, but instead, we’re building it top down as a child learns from observing, listening, and identifying patterns. And it turns out that while we have less control over it, it’s working far better than any of us ever imagined.

    Source date (UTC): 2023-06-19 19:30:23 UTC

    Original post: https://twitter.com/i/web/status/1670876702606491650

  • He’s active. They produce videos. I follow their discussion groups. I have learn

    He’s active. They produce videos. I follow their discussion groups. I have learned more from Hawkins’ group than all others combined. Primarily because he is working at what we would consider the micro-column level not the neuron or neural network level. And that’s how the brain…

    Source date (UTC): 2023-06-18 16:36:24 UTC

    Original post: https://twitter.com/i/web/status/1670470528233078784

    Reply addressees: @PavlosProkopeas @mezaoptimizer

    Replying to: https://twitter.com/i/web/status/1670413129598074880