You know that eventually (probably already) the developers of AI are going to be using AI to enhance ... maybe even direct ... the AI coding of the future, right?

Apparently you don't.

Dave   AB7E



On 9/29/2025 2:47 PM, Karl W Hubbard wrote:
Stalin: What matters is who counts the votes.

AI: What matters is who writes the programs.




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On Monday, September 29, 2025, 2:24 PM, David Gilbert via Elecraft <[email protected]> wrote:


    As others have said, AI today merely replies based upon the data
    it was
    trained on, aided by a very fast and very broad real time online
    search
    capability.  That search capability is one reason I use ChatGPT
    ... its
    replies are faster and broader than Google, for me at least.

    Sometimes when I ask ChaGPT a question it gives me an inaccurate
    response and I need to correct it to get the proper result.  ChatGPT
    remembers that (for me) and (usually) doesn't make the same mistake
    again if I ask it a related question, but  AI currently doesn't
    aggregate what it learns from multiple users. In other words, the
    feedback it gets from its interactions with one batch of users is not
    used to "teach" it how to more accurately respond to a similar
    question
    from other users.  At least part of that limitation is per the
    decision
    of the developers, such as for user privacy concerns.

    However ... that is not necessarily how it will be in the future.
    Humans
    learn from others, not just their own perceptions and observations of
    the world around them ... i.e., the raw "data".  AI could do the same
    ... and then who knows what we will get.  So I asked ChatGPT this
    question:

    "How long do you think it will be before AI is able to aggregate
    what it
    learns from a broad spectrum of interactions with multiple users?"  I
    got the response below.  It's a cut&paste so hopefully it makes it
    through the reflector.

    Dave   AB7E

    p.s.  The comment about "drift" is a real issue I hadn't considered.
    Pretty interesting.


          *Technically:* we’re already there (in a limited way)

    OpenAI, Google, Anthropic, etc., already do something like this
    today —
    but not by letting the model itself remember. Instead:

      *

        They *collect and anonymize* user interactions.

      *

        Those logs feed into *future training runs or fine-tunes* of
    the model.

      *

        The new model you get months later has improved capabilities based
        on /aggregate/ patterns — but not on any specific identifiable
        conversation.

    So in effect, “learning from a broad spectrum of interactions”
    already
    happens; it’s just *offline* and at periodic update intervals, not
    continuous and in real time.

    ------------------------------------------------------------------------


          *What isn’t here yet:* true “online lifelong learning”

    That would mean the model you’re chatting with today is directly
    shaped
    by everyone’s conversations from yesterday. That’s technically harder
    (you risk drift, bias, privacy leaks), and it’s a regulatory
    minefield.

    To do it safely you’d need:

      *

        Very robust anonymization and filtering.

      *

        Real-time evaluation for harmful or biased shifts.

      *

        Clear user consent and opt-out mechanisms.

    ------------------------------------------------------------------------


          *Timeline guess (if done responsibly):*

      *

        *Within 2–4 years*: Large commercial AIs may begin limited, opt-in
        “online fine-tuning” where they adapt weekly or monthly using
        anonymized data.

      *

        *5–8 years*: We’ll probably see truly “continuously learning”
    public
        models, but with heavy privacy layers and regulatory oversight.

      *

        *Beyond that*: Personal AIs that combine global learning with your
        private, encrypted data for hyper-personalized experiences,
    without
        leaking your details to others.

    ------------------------------------------------------------------------

    So the short version:

      *

        The /aggregate learning/ you’re imagining already happens
    today, but
        in batches and offline.

      *

        Real-time, ongoing learning from everyone at once is coming — but
        probably in a *measured, opt-in* way over the next decade, not
    as a
        sudden flip.



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