You Ask, I Answer: ChatGPT Predictions?

Trying something different today using uh Adobe Podcast along with the uh the wireless lava layer mic and the uh the phone. So let's see how this turns out. Because if this works really well, then it means that um for folks who are content creators, you can do more than one thing at a time, as long as you're safe enough where surroundings. So in today's episode, Kathy asks, what do we think the implications of chat GPT are on you know the the rest of the year? And that's an impossible question to answer.

Um here's the thing. I would like for us to stop referring to that specific product when we're talking about the applications of large language models, right? ChatGPT is a great tool, right? It's built on the GPC3 model, which is by OpenAI. That is not the only large language model out there.

In fact, there are many, many um large language models. Each staff has their own uh applications, their own uh parameters. The Luther AI made a whole bunch uh on their data set in the pile. So large language models. We talk about something like ChatGPT as like talking about Microsoft Word, like what are the implications of Microsoft Word, as opposed to what's the implication of word processing, right?

How um how is word processing going to change content creation? It sounds different, right? It sounds uh a little more broad. We saw in the news this past week that Microsoft is looking at integrating um the GPT 3 model, the the large language model into its search engine and especially into some of its products like Word, PowerPoint, and Excel. This is a really good idea, right?

This is a really good idea because when you're being creative, um, even non-really creative inside the office and stuff, you're I mean, we've all had that experience when you're sitting now to write something and you're like, uh, I don't know what to write, I don't know what to put on this slide, and so on and so forth. And that's where a large language model is a really good idea to have available to say, uh gosh, what should I name this presentation? Well, hey, let's take a look at all the notes and distill down some some title suggestions, right? To name this presentation. Or I've written this chapter of this book in my word processor, and like, what should it what should the chapter summary be?

Right for those people who write serial pieces of fiction. Choosing your your summary, choosing your uh your um sort of snippet for promotion, really difficult. If you're creating content and you want promotional material from it, this is something that we're seeing a lot of tools starting to explore, uh, where you give it your content and you say, make me some social posts, right? Make me something that I can use to put on Instagram or Facebook or or LinkedIn or whatever, and it will generate those things. And those are really good applications of large language models as adjuncts to the creative process.

And I think that's an important part. It's an adjunct to the creative process. That means it's not doing the work for you. Well, I mean it kind of is. It's not building the main corpus of the work, it's building all the promotional stuff around it.

And let's face it, a lot of people who are really good creators, right? Authors, filmmakers, musicians, many of them don't like making promotional material, right? Many of them don't like pimping their stuff. They feel awkward about it. Well, what if the machine just does it for you?

Right? So you're instead of trying to struggle to make some promotional content, the machine does it for you. Hey, here's the tweets you need uh to promote this thing. That's a great use of this technology. That's a great use of large language models.

So that's what I foresee as being the useful use cases. There's a lot of novelty uses uh for these large language models. One of my personal favorites is meeting note summarization. I will feed a um a long transcript of you know 20, 25 minute call and say, give me meeting notes and action items out of this. Now I have a whole prompt written down to make sure it behaves the way I want it to behave.

But in doing so, it dramatically shortens the amount of time I need to get action items out of a call, particularly if it was a long call and remember everything. Um it's a great way to summarize it. So are there gonna be other applications? Of course, right? We see all sorts of things like um actual conversations.

I saw a piece of news this morning on how someone was using it to what they say, they was using it to uh test for mental health stuff, um, experiments, you know, controlled laboratory setting by qualified professionals um to see if these bots could act as therapy adjuncts, right? Not not replacing a therapist, because the liability on that alone would be impossible, but as a supplement to regular therapy. So that's where I think we're going with these things. It's gonna be interesting to see how it turns out. One of the big uh questions right now that was announced in the OpenAI Discord was hey, we're thinking about commercializing this.

What should the pricing be? What should the model be? And a lot of people pitch their their ideas in, but the era of this stuff being free is coming to a close very fast. So if there's a lot of things you want to get done with it now, get it in if you don't have the budget. OpenAI's regular pricing is surprisingly affordable.

Um it's uh like two cents, I think, per thousand tokens. So if you put in a thousand-word essay, it'll cost you you know two two pennies to process that thing to generate that much um token data. And we see with chat GPT in particular, that it doesn't seem to take into account the input length nearly as much as the regular GPT 3 model does. So you can put in really long prompts, and you should uh to get results out of the system. So how that changes once they start charging for it, we don't know, but it will be um will not be free forever.

Uh it will not be free even for a while. It's that that that research phase I believe is coming to a close. I don't think OpenAI expected it to be the huge hit that it was, but uh no, they're smart folks, they got a bunch of doctorate degrees and things, they know that they've got a hit on their hands and they need to capitalize on it sooner rather than later. Anyway, thanks for the question. Talk to you soon.

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