Simply explained: How does GPT work?

Certainly, Midjourney's "creativity" is different from human creativity. But it is producing results that we marvel at. It's creative not because it's doing the exact same philosophical thing humans do, but because it can produce the same effect.

And I think many situations are like that. We can always say that human creativity/reasoning/x will always be different from artificial reasoning. But even today, GPT's statistical model replicates many aspects of human reasoning virtually. Is that really an illusion (implying its fake and potentially useless), or is it just a different way of achieving a similar result?

Plus, different models will excel at different thing. GPT's model will excel at synthesizing answers from far more information than a single human will ever be able to know. Does it really matter if it's not identical to human reasoning on a philosophical or biological level, if it can do things humans can't do?

At the end of the day, some of these discussions feel like bike shedding about what words like "reasoning" mean philosophically. But what will ultimately matter is how well these models perform at real world tasks, and what impact that will have on humanity. It doesn't really matter if it's virtualized reasoning or "real" human reasoning at that point.

I guess ... this is what confuses me. GPT -- at least, the core functionality of GPT-based products as presented to the end user -- can't just be a language model, can it? There must be vanishingly view examples from its training text that start as "Write a Limerick", followed immediately by some limerick -- most such poems do not appear in that context at all! If it were just "generating some text that's likely to come after that in the training set", you'd probably see some continuations that look more like advice for writing Limericks.

And the training text definitely doesn't have stuff like, "As a language model, I can't provide opinions on religion" that coincides precisely with the things OpenAI doesn't want its current product version to output.

Now, you might say, "okay okay sure, they reach in and tweak it to have special logic for cases like that, but it's mostly Just A Language Model". But I don't quite buy that either -- there must be something outside the language model that is doing significant work in e.g. connecting commands with "text that is following those commands", and that seems like non-trivial work in itself, not reasonably classified as a language model.[2]

If my point isn't clear, here is the analogous point in a different context: often someone will build an AND gate out of pneumatic tubes and say, "look, I made a pneumatic computer, isn't that so trippy? This is what a computer is doing, just with electronics instead! Golly gee, it's so impressive what compressed air is [what LLMs are] capable of!"

Well, no. That thing might count as an ALU[1] (a very limited one), but if you want to get the core, impressive functionality of the things-we-call-computers, you have to include a bunch of other, nontrivial, orthogonal functionality, like a) the ability read and execute a lot of such instructions, and b) to read/write from some persistent state (memory), and c) have that state reliably interact with external systems. Logic gates (d) are just one piece of that!

It seems GPT-based software is likewise solving other major problems, with LLMs just one piece, just like logic gates are just one piece of what a computer is doing.

Now, if we lived in a world where a), b), and c) were well-solved problems to point of triviality, but d) were a frustratingly difficult problem that people tried and failed at for years, then I would feel comfortable saying, "wow, look at the power of logic gates!" because their solution was the one thing holding up functional computers. But I don't think we're in that world with respect to LLMs and "the other core functionality they're implementing".

[1] https://en.wikipedia.org/wiki/Arithmetic_logic_unit?useskin=...

[2] For example, the chaining together of calls to external services for specific types of information.

That's me. After programming since the '80s, I'm just so tired. So much work, so much progress, so many dreams lived or shattered. Only to end up here at this strange local maximum, with so much potential, destined to forever run in place by the powers that be. The fundamentals formula for intelligence and even consciousness materializing before us as the world burns. No help coming from above, so support coming from below, surrounded by everyone who doesn't get it, who will never get it. Not utopia, not dystopia, just anhedonia as the running in place grows faster, more frantic. UBI forever on the horizon, countless elites working tirelessly to raise the retirement age, a status quo that never ceases to divide us. AI just another tool in their arsenal to other and subjugate and profit from. I wonder if a day will ever come when tech helps the people in between in a tangible way to put money in their pocket, food in their belly, time in their day - independent of their volition - for dignity and love and because it's the right thing to do. Or is it already too late? I don't even know anymore. I don't know anything anymore.

> Programming languages are a whole lot more structured and predictable than human language.

> In JavaScript the only token that ever comes after "if " is "(" for example.

But isn't that like saying that it's easy to generate English text, all you need is a dictionary table where you randomly pick words?

(BTW, keep up the blog posts, I really enjoy them!)

I said this to chatgpt: I had a dream that me and my friend were in a car accident, and we had a choice in deciding how to use 1 hour. we could use it to live out our last final moments or spend that hour on trying to think of a solution to survive the wreck. turn this into a short story.

As they sat trapped in their overturned car, Maria and her best friend Rachel had a dilemma. They only had one hour left to live and had to choose how to spend it. Rachel suggested they spend their final moments together, talking about all their favorite memories. But Maria had a different idea. She proposed they use the hour to think of a solution to survive the wreck. Rachel was hesitant at first, but ultimately agreed. For the next hour, they brainstormed every possible escape plan they could think of. They tried pushing against the doors, breaking the windows, and even attempting to signal for help. Just as they were about to give up hope, Maria remembered a tool in the trunk of the car. She crawled over to retrieve it and used it to pry open the door. Rachel followed her lead, and they finally escaped the car just in time. As they stumbled away from the wreck, both girls were in shock that they had made it out alive. They hugged each other tightly, grateful for the hour they spent trying to find a solution instead of giving up. From that moment on, they made a promise to never take a single moment for granted.