re: People talking about AI “taking over” always make me laugh.

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If it changes its action based on prior results, it's AI. If it can provide information it doesn't already have programmed, it's AI. Foundationally, AI is anything that can be taught to do what humans typically do.

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So we’ve had AI for 23 years then.

With that in mind, this version of AI taking everything over does make me laugh. This version of AI is more akin to an increased mechanism of data exchange.

If AI became an autonomous self-serving mechanism that could not be controlled (which may happen), then, yeah, this could take a lot over quickly.

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So we’ve had AI for 23 years then.

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Definitely. Probably longer, just maybe not commercially.

Unless you think it's the first tech that will ever regress, 2 more decades with a tech that progresses exponentially should at least raise an eye brow.

Yea the mental instability of modern humans will slow it a touch, but not forever.

The models in use outside of publicly accessible LLMs are much more rigorous in their development.

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work in sales. 90% of the entry level sales work is mass emailing potential customers

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Does this actually get any customers? Unless the email is an invitation to a steak dinner you are hosting (where you sell/demonstrate product in person), I don’t see how a random email blast would generate sales.

Technological shifts usually take way longer than people estimate. If they say 10 years it will be 30.

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It reminds me of the time that someone around here said that GPT is just a search engine. Sounds plausible I guess.. if you ignore the fact that it’s actually incapable of searching the internet for information when you enter a query.

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That was probably me, and I'm right.

Is it searching Google or bing? No. It is looking at its training data to come up with something that is the most likely correct value, and in the case of ChatGPT, that set includes a whole lot of the internet.

Is it a useful tool? Of course, I use it almost every day. It's not going to take over the world, and the hype is getting into the crypto realm.

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Is it searching Google or bing? No. It is looking at its training data to come up with something that is the most likely correct value, and in the case of ChatGPT, that set includes a whole lot of the internet.

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Again, that’s not how they work. The training data is not stored in the model.

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Again, that’s not how they work. The training data is not stored in the model.

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Ok, fair point, it generates a model off the data and predicts what is most likely the next word as it generates text.

It's not aware of what the words mean.

Copilot rewrote this:

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The notion that AI will replace all jobs is a misunderstanding of its capabilities. Certainly, AI has its applications, but it’s not a catch-all solution. Often, jobs susceptible to AI replacement are those with repetitive tasks. AI operates on statistical models and requires human input. As AI becomes more prevalent, we’ll see a rise in jobs focused on developing and refining AI technologies, which will likely supplant the roles AI is automating.

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Ok, fair point, it generates a model off the data and predicts what is most likely the next word as it generates text.

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I think it’s a pretty important distinction though - a neural network capable of “remembering” information from its training without actually storing the training data is considerably different from a search engine or database that’s just looking the information up, in much the same way that a person with mastery of a subject matter is considerably different than someone with access to a library or Wikipedia.

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It's not aware of what the words mean.

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As I’ve said before.. actual “awareness” of anything is nearly impossible to measure. We are seeing developments where LLMs are showing greater understanding of context and connotation. There’s also the fact that the LLM is responding to a prompt - it’s not just stacking words together in an order that makes sense. It’s stacking words together in an order that makes sense given the prompt entered by the user.

That being said, I would not expect an LLM to have true awareness of the meaning of words even if we could measure awareness. LLMs’ entire existence is text-based. They might be able to tell you that green and red are at the opposite ends of a color circle and that red corresponds to light wavelengths in the ~700 nm range, but they don’t know what green or red look like. So how could they possibly understand?

In a similar vein, diffusion models tend to have difficulty with concepts that require an understanding of 3-dimensional space (although they’re getting better). This is not terribly surprising as all of their training data and outputs are 2-dimensional.

I loosely relate LLMs to a person who is blind, can’t smell, can’t taste, can’t feel anything, and has no motor functions. But they can hear and speak (somehow). Would that person ever truly have any understanding of words beyond “pattern matching?” It doesn’t make language processing any less important when you put the rest of the pieces back together.

At some point there will be attempts to unify the AI puzzle pieces and, eventually, connect them to the outside world.