Episode 60: Learning, Work, and Art in the Age of ChatGPT
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Transcript
[00:00:10] Blue: Welcome to the theory of anything podcast. Hey guys, how’s it going? Hello, Bruce. Hey, Bruce. Hey, we have a guest. My nephew, Brendan Nielsen here with us today. How’s it going, Brendan?
[00:00:25] Red: It’s going good. Enjoying a nice spring morning.
[00:00:30] Blue: Brendan actually had the idea for this podcast episode. So we invited him to participate. I was working one day and I received this text and it’s from my nephew. And he goes, do you want to talk about artificial intelligence? Because like I’ve got no one to talk to about it. And I know you like are interested in that thing. So like we did this zoom and we just started geeking out over artificial intelligence. So I interestingly, I told cameo about that and then cameo started geeking out over artificial intelligence. Then we had another conversation similar to the one I had with Brendan and said, we ought to just all get together and we got to talk about chat GPT in particular. And kind of a lot of the cool things that are coming out of generative AI these days. We’ve done a few episodes on artificial intelligence in the past. Obviously that’s an area of interest for me. I should probably note though that I’m more theoretically interested. Like I want to understand the algorithms. I’m not a great user of technology. And actually think cameo in particular has been quite impressive in her use of technology as a user. So I’m going to probably let cameo and Brendan do a lot of the talking for this episode because I’m really curious what they’ve learned from all their use of AI. And we can save my theoretical reading papers for some other time. I want to hear from Brendan first.
[00:01:59] Green: When did you start using chat GPT or other MMLs and how are you using them and what are you doing?
[00:02:09] Red: Yeah, that’s a great question. So a little bit of background on me. I’ve worked in software for about six years on the sales side. So I’ve been on different sales team and software. So professionally, I have been using chat GPT a lot lately. And other AI tools. And then I’ve also been a music producer for 10, around 10 years and artist and performer and DJ. So I have been, I think for me, I first started using chat GPT like last Christmas. But all I remember is the first real use I had with it was actually at our family party. Bruce is when, you know, like we do the Christmas cranberry pudding every year at grandma’s house. So I found out, you know, I had, I had food allergies and, you know, about a year, a couple of years ago. And that thing has so much milk in it. And I’m a very dairy allergy. I definitely have a dairy allergy. And so it’s the ingredient or the recipe is basically butter, milk, sweet and condensed milk, sugar, flour, cranberries. And I was like, how am I ever going to be able to eat this again? And so I started just talking to chat GPT and I heard that it could do amazing things. And this was early. So this GPT three or 3.5. And so I was like, Hey, I want to make this recipe. Here’s the recipe. How can you make it? You know, how can I make it allergy friendly? And you know what? It told me like, get this kind of oat milk. You’re going to reduce it over the stove at this temperature for this long. That should turn into the consistency of sweet and condensed milk.
[00:03:54] Red: You can go get oat milk butter, use it this measurements. And then I did it and it, and it made a cranberry pudding that was vegan and it was good. And we even had some taste tests. I don’t know if you tried it for you remember that. But that was my first use of chat GPT. And I was like, wow, okay. I’m always for quality of life updates, you know, with technology 100%. And so I just kind of continue to use it. And I think, you know, thereafter, you know, I would say it took a few months, but I really started to see kind of the application of, you know, this technology across my life. And a lot of what I do, I do work in tech. I’m constantly writing emails. I’m constantly writing proposals and constantly building, you know, all reports, all sorts of stuff. And I started to really see kind of the benefit of having, and maybe we’ll get to this too. But I’ve been diagnosed ADHD since I was seven years old. And, you know, I’ve been to a lot of therapy and one of the biggest, one of the biggest things that helps people with ADHD is having, they call it a, what’s it called body doubling, where if you feel like you’re having a hard time getting something done, being able to have somebody to talk to or be there and bounce around having like a co -pilot is helpful.
[00:05:09] Red: And I’ve found that using, you know, large language models like chat GPT and other, you know, AI solutions kind of gives me that body doubling experience, which allows me to be significantly more productive where I can, you know, rather than responding to a whole email at work or, you know, I can just basically say, hey, write a reply that says the quote is this much. And we’re grateful for working with you do it in a friendly and concise, you know, business voice. It’ll write it. And if you get the prompting right, it’ll do it pretty close. First time you edit send it off. I mean, it’s significantly increasing my productivity. So really, I just have been using it. I don’t, I’m not an expert on AI. I have been in music and software for a while. So I have some experience there. But as far as AI goes, I’ve just been a heavy user lately in both music and at work. But it really has increased my productivity and it’s been, it’s been pretty cool to see that.
[00:06:06] Green: I really like your idea of using it for the ADHD. And I guess I’m using it that way without even kind of acknowledging that, that I am using it that way. I got in probably a lot the same time as you did when they, when they pushing it out and it was, it was just kind of just so mind blowing to see what it could do. And so the same as you, I started using it a lot for really simple things like emails, summaries of conversations. I early on, I was, I would record meetings through, through teams because it auto transcribes it. Yeah, I’ve done that same thing in and use that to, to provide summaries and here’s what this meeting was about and, and let it summarize all of my meetings. So I didn’t have to take notes anymore in meetings. And then I had a speech that I had, I was giving at a, at a conference earlier this year. And I was really, really struggling to, to get it written. It was a 45 minute speech and I knew the concepts that I wanted to, to, to talk through. In fact, I, the person I went out to lunch and I was kind of bouncing some of my, my early ideas, but I was just, I’m such a ADHD person, you know, and doing, sitting down and writing an hour long speech. I just was really struggling making headway on it. And so I, I used chat GPT to write the vast majority of it.
[00:07:51] Green: And you know, I would just sit down in little clumps and give it my next idea that I was, that I was going to have as the next portion of my speech and then really just use it as a, as an idea bouncer kind of where I would say, okay, I’m going to talk about this and it would give me ideas and I would kind of use it to help, help me refine my ideas. And I wrote the entire speech in, in concert with, with chat GPT and I was really pleased with, with our work that we came up with. And then, you know, kind of the same thing on the, on the visual side too. I, I got in early on, on Dolly and I haven’t, I don’t use it anymore. I’m almost exclusively using mid -journey.
[00:08:38] Blue: Mid -journey is so good.
[00:08:39] Green: Pretty heavily. And so yeah, it’s kind of just the same thing. It’s just, at this point, I, I probably spend an hour a day at least in some, in, in either chat GPT. I’m, I also am using a GPT agent pretty heavily. And I honestly, I don’t know what I would do if they took it away at this point.
[00:09:07] Red: How’s that? I’ve never used an agent. I’ve wanted to, but I haven’t, you know, how did you, you general from GitHub? Like how did, what, how did you get, get the agent?
[00:09:16] Green: So my, my boss is like, crazy into AI and he’s been, he has, he meets up with other executives pretty regularly. And he has an AI group of executives that he’s been, been hanging out with. And one of them had developed an agent that is, specifically that is on the surface being called a investing agent, but it’s, it’s just a, an agent that you can give any, any jobs to. And so he wanted us using the agent in, in our daily life. So essentially paid for us to all have access to the agent. The agent is weird a little bit. And in fact, I might pull it up and, and we can, we can watch it do some things. The agent lies a lot more. What’s the name of the software green chart portal. It’s called day trade AI. I’ll open it for really quick and, and kind of talk through what it does. I know that this is a podcast. So people can’t see the visuals, but the agents are really interesting though, because you, if you’re willing to spend the money, because you have to have it connected to a credit card, because it’s, and, and a, the, you have to have the API is connected to it, but it, it’ll keep going and it’ll keep going and going. If you give it a big enough thing and maybe to the extent that it won’t ever stop. If you give it a large enough goal.
[00:11:00] Red: That’s crazy. I’ve never used one before. So you basically prompt it and then it prompts it. It continues to prompt itself. Is that what I understand
[00:11:07] Green: prompts itself? Yeah. And it’s, it’s a pretty, it’s a pretty crazy kind of thing to watch. So that. So this is this particular agent. And I, you know, anyone could build an agent quite easily. This one, all it does is takes my API key and, and then I don’t know what exactly. I don’t know. This doesn’t seem like a complicated piece of software, but to use the agent, you tell it what kind of an agent it is. So let’s call this one. A comic book author. I had told Peter and Bruce. After an episode, I think last time that I had used chat GBT to help me. I’ve been writing a comic book about David Deutsch. That’s called many worlds. And so that actually is, has been a lot of fun. I’ll show you my, some of the pictures that, that my journey has made for me, but goal. Write a comic. All right. So about David Deutsch. And incorporate all, all of his philosophies and writings. Okay. So that’s probably good. And then we deploy the coach. All right. So it’s embarking on a new goal to write a comic about David Deutsch and incorporate all of his philosophies and writings. So then it’ll think for a little while and it all will, all we, all right. So it didn’t need to think very long. I’ll keep, stop it from. This is
[00:12:45] Red: incredible.
[00:12:46] Green: It is really, really incredible. So it lists all of its tasks that it’s identified. And what it starts doing is adding all of these tasks. So its first task is to retrieve all available comics. Now there aren’t comics, but it, it hopefully is still figuring things out, extract important themes from David Deutsch’s philosophies. And you see it’s, it’s, it’s adding more tasks as we go. In fact, down here at the bottom, it’s still thinking through all these different tasks it wants to do. But if we come back up here, let’s see what it’s doing. And it makes it this list of things that it needs to, to do as it figures them out. And so now it’s executing on this particular particular task.
[00:13:30] Blue: I take it, it has access to the internet. Like, like where is it? It has access to the internet. Yes. It has access to the internet.
[00:13:42] Green: Incorporating these concepts into a comic about David Deutsch could be an interesting challenge.
[00:13:48] Unknown: But
[00:13:48] Green: here it, here it’s outlines, outlines some, some things that, that it wants to incorporate. Quantum mechanics, the concept of the multiverse, constructor theory, fundamental theory of physics. And so. Where are you reading that? I didn’t even see
[00:14:05] Blue: where it, where it said that.
[00:14:06] Green: It’s in this executing area right here. Oh, you’re right. Okay. I see it. Yeah. So it’s kind of summarized it here. And then identifying. So it’s, it’s kind of, it goes after it goes through an execution stage. So now it’s telling me it executed that task successfully. And it’s highlighting some other things that it’s putting together, his epistemology, which this is also just a really nice summary of, of, you know, what David Deutsch is, is all about. And so now it’s kind of theorizing. The comic could feature a group of scientists exploring the multiverse. So it’s come up with, with concepts, right? It’s coming up with concepts. And so now it knows that it needs to develop a script and a storyboard.
[00:15:02] Red: And you kind of tell it, Hey, I want you to go down this vein or this vein or like, like, or is it going just linear to what it decides?
[00:15:10] Green: It just does what it wants. It, it’s kind of a fascinating difference between this and using chat, be GPT, because if I was like, Oh, I don’t know if I want you to go down this path. I don’t, there’s no input. There’s no additional input after my, my giving it the goal. I can stop it and give it a new goal. I can stop it and readjust the goal. But, but it, it does its thing and it has its plan and it executes on its plan and it’s just off to the races. And I gave it a task last week and I came back hours and hours later and it was still just busily doing this, going through all of these tasks and making. You have to deal with
[00:15:57] Blue: the halting problem. You don’t know if it’s ever going to actually complete or not.
[00:16:03] Green: You do. And, and, and so I have stopped it before and said, you know, okay, we’re done with that. And I, I don’t even know where to go and look and see like the potential impact monetarily. I mean, I could go and look at my corporate credit card that they, that it’s tied to. When are we going to see the comic? This looks really cool.
[00:16:26] Blue: Well, I noticed that it said is one of its tasks is that it has to collaborate with comic artists. So like, how is it going to do that? So this
[00:16:35] Green: is, this is the crazy thing about these agents. They lie like crazy all the time. It will tell you that and then, and then it doesn’t.
[00:16:46] Red: Or if it like. Well, could it, could if it was connected to like Fiverr though, which I mean, the, isn’t the, have hasn’t already done that like basically hired a human. Before.
[00:16:58] Green: When I’ve read about people doing that with agents, but I guess I don’t know enough about how this particular agent is. Created or what I mean, this is designed to do investing. So, but I didn’t, I haven’t found any place I can connect it to things. I know it is connected to the internet because I see it doing research, but. But I don’t, when it says things like I’m going to go to talk to these people, I don’t have any evidence that it has done that.
[00:17:28] Blue: Right.
[00:17:28] Red: Yeah, that’s true. I’m sure this one probably doesn’t. I’m interested to see what happens with the plug in ecosystem on GPT because it kind of reminds me of like the iPhone, right? Where it’s like, iPhone’s powerful in and of itself, but having all the different applications built on is what makes it like so powerful, right? And so the fact that now they’re GPT is opening a plug in ecosystem where you can, where you can basically be like Instacart, hey, make me a meal plan with this caloric intake with this, you know, diet and food, food allergy list. And I want it to be under this budget and I want it to be this much per meal. And then it’ll build out the plan for you and then say, okay, put that in a grocery list. Okay, order those to my house and you can connect it with your Instacart and we’ll do it. And so there’s, there’s a lot of, I haven’t played with it. I think they actually want to say that the plugins, you could like launch to all GPT plus users like this week or weekend. And so I want to get into it. We built, we built a tool, an AI tool for my job that uses chat GPT. It’s really cool. It’s trained on the specific, basically case management software that I help assist with. And it’s a Chrome plugin that uses GPT. We trained it on specific help center data and like a bunch of other data that we had about the software. And we’re, we’re, we’re in beta testing. We’re going to deploy it, but it’s really cool.
[00:18:54] Red: There’s so much you can do to basically take these language models and narrow them down into like a specific function. This, it’s, it’s almost this, I’ve never seen the auto GPT or like this type of autonomous agent like live before I’ve seen videos of, but it’s pretty crazy to see you doing it about this topic that I’ve heard Bruce talk about and just reading that it’s getting the prompts, right? Like it’s definitely, it’s cool. This is really cool.
[00:19:21] Green: It’s really cool, but I, I’m, I’m really excited for the plugins because, because I don’t, I don’t actually want an agent that I send out that I, that I can’t interact with. Like it’s a little like having an employee that, that you, you’d give like one sentence to, and then they go and do stuff and you’re like, well, but you never came and checked back with me that that was like what I wanted or the right approach. And so being able to just incorporate the work that I’m doing with and the ways I’m using chat GPT and put it more into, you know, plug in across everything that I’m using so that when I get a million messages on LinkedIn, I can, I can open a message and just have it essentially respond.
[00:20:18] Red: One tool that I’ve been using lately that I love, I got into a beta of augment AI every year to them before. So I don’t know exactly what models that you used. I asked it like some of its proprietary, but we obviously use GPT as one of our sources, but it essentially allow, it will allow, it’ll read like your email thread and it will also read your Slack thread and it will understand the context and then all you have to hit is pound pound or hashtag hashtag and you can choose to have it just reply for you and it will just reply for you, or you can say reply with my context. And then you just say, hey, tell them this and then we’ll just craft the email completely as you immediately enter, go in and edit it and send it off and it learns the more data about you and like what, how you speak and it becomes kind of like your personal assistant and it’s great. I’m telling you this thing is saving me so much time responding to emails. That’s like half my job and it writes better than I do. So I’m like, there’s no reason not to use this if it’s getting the point across and I feel like that’s kind of going to be the future of this. I try to use, I don’t know, have you downloaded the GPT mobile app yet?
[00:21:34] Green: I downloaded it yesterday. I haven’t used it yet, but I’ve been using chat GPT heavily on my phone already, you know, just through the mobile browser.
[00:21:45] Red: Yeah, the whisper integration where you can just talk to it now is so cool. Like yesterday I was, we were at the store trying to look for a USB hub for my M1 and I was like, I can’t remember what, what would be the best like USB hub, like what specs do I need? And I just asked it in the store, I just like use the whisper thing and I was like, Hey, I’ve got this, this MacBook, you know, what’s the best hub? And it’s like, Hey, look for one that has these specs. So I did got that one. So I mean, it’s just really using that, being able to use that voice to text and on your phone anytime you need it, you have a question to something or you’re not exactly sure. It’s just cool to have it as that personal assistant, that body double. That’s really what I have been trying to use it for. Same with music. Like I use this, I’ll feed it, like I’ll write a lyric or like a chorus or verse and I’ll be like, here’s the meaning of the song. Help me. Let’s give me some ideas for a potential second verse or give me like 20 ideas for potential second verse or, and then I just, we’ll use little bits and pieces of it. But it really is just like that co -pilot. And I saw that’s, that’s what, what’s, I’m excited for Microsoft co -pilot and Google co -pilot. Like the future is bright. It’s going to be a crazy few months. I feel like over the next few months, just this stuff and years. Yeah.
[00:23:03] Orange: If I may just interject. Here’s a question for you, Brandon. Kind of going back to your ADHD comment. That really intrigued me partly cause I, I didn’t mention this before, but I’m a special education teacher. And I, lately there was another eruption of, of emails in my work about phones in the classroom. What are we going to do with about these phones? The kids are all using, you know, I get it. It’s kind of annoying when you’re trying to run a classroom and, you know, there’s half the kids are on their phones tuned out, but you know, it also occurs to me that there’s just so much negativity and fear about all of these technological changes. And, you know, there’s a long history of this going back to math teachers, protesting, you know, there were actually protests. You can see the pictures of math teachers, protesting calculator use. I know it’s like, we only do abacus is in this house. But I mean, why are I just, I just wonder like, why are people so fearful of these, these technologies that can, can positively impact people’s lives?
[00:24:15] Red: I think partially it’s marketing on the side of these AI companies. If that, you know, it’s the, there’s no bad press. If they’re getting in front of, you know, the big cameras and exposing people to this, it’s just like, I think it’s partially marketing. I think it’s partially smart that people are afraid of it. But I also think that just because this is such a crazy technology, I think there are genuine risks, but I also do think that, and you know what, this is kind of a good lead into what we were talking about before the podcast that I wanted to hit on where I feel like, you know, you were talking about like the impact of technology on music and like how there’s some negative benefits, negative effects of those. I think for, in my opinion, when we really hit that level of automation across everything where it’s like, I will be able to prompt with natural language, the type of song that I want to produce rather than going in and taking the years of knowledge that I’ve had to like, build the synth tones and mix the songs and all the stuff that would take me hours and then I can just prompt it. Yeah, that means that there’s going to be a kid. You know, you could have a kid in Indonesia that has access to a laptop and can make like the biggest bangers ever. And same thing with generating video. You know what I mean? Think about like Christopher Pailoni, he wrote like Aragon, right? Imagine if he had had the ability to just make a movie from that idea, like as a kid, you
[00:25:39] Red: know, I think it’s going to level, I think it’s going to level the entertainment industry. It’s obviously going to level a lot of industries, but anything that’s art, you know, with this being generative AI, it’s going to level it. But when you think of level, that means bring it down. It’s going to put the tools in everybody’s hands to make, make this stuff. I think for me it’s, you know, I’ve been trying to chase music professionally for years and I’ve had millions of streams. I’ve played in different countries. I’ve, you know, I feel like I’ve had levels of success and it’s like already before this whole AI thing, impossible to make a living in music. And it’s, it’s kind of made it, it’s kind of made me hit this point where I’m like, well, what’s the purpose of doing music? What’s the, and then it kind of goes back to your saying, what’s the purpose of going to school? What’s the purpose of all these things that we just do as a society? Learning, you know, I feel like once it’s, once so much of that is automated, it kind of goes back to almost a philosophical question of like, what is the purpose of this existence? And like, what is, if you had all of the stuff taken care of that you didn’t even think you would have taken care of someday, what would you do with your time? Why do you do music in the first place? And I think I hope what we will do is just inspire more creativity is my hope. And that will be in this place where it’s like the, the part of it will be the, hey, the spirit of learning. Why are we actually learning? Is
[00:27:06] Red: it learning to get job placement and to, you know, die for a corporation? I don’t live your life working for a corporation. You know, it just begs a lot of questions. And I think it’s going to break a lot of people’s realities. I think it’s going to make and make us all reevaluate why we do what we do when it’s, when everything’s automated. And I hope that that brings a more pure experience. And so to kind of round this idea out, I think after I saw what mid journey was doing after I saw what runway was doing after I saw Dolly and all this, I just saw the writing on the wall and I mean, like Google’s released stuff about music, like they have, they have a text to music generator. It’s not perfect yet, but it’s pretty good where you can just use natural language to prompt, create a song. And I want to make a song in the style of this person with this type of baseline and in this BPM and this key, this chord progression and it will build it for you. And so I was just like, man, like if this is going to be automated, like we’re going to get to the point where we’ve got, you know, a corporation can purchase a, a AI that understands the, all of the parameters of music theory. It’s going to understand all of the, all of the, you know, the technique for mixing and mastering and for basically every style of music out there. And at that point, they’ll be able to just create royalty free music based on just randomly generate or generate within these chord progressions, this type of music that, that based on user data when, when
[00:28:39] Red: we know that we have an older demographic coming in the store from nine to 11 AM. So we’re going to be playing, you know, jazz, but what, you know, once it turns nighttime, we’re going to have our music AI create, you know, more like nightclub music. The thing is it’s just going to put a lot of corporate musicians out of the job. Definitely. That’ll probably be who goes first. Same with kind of like stock photos and things like that. But hopefully it will still leave room for artists to, to use it to create unique works of art that technologically weren’t possible before. Kind of like we already are doing, but we’ll see who knows. I mean, I
[00:29:16] Orange: guess in a way people are right to be fearful because it, you know, as you’ve illustrated well, it’s just going to change everything. I mean, it’s going to make turn optimistically turn us all into artists and engineers and writers of comic books. And, you know, but I, you know, we talk a lot about optimism on this podcast, which is very much associated with David Deutsch’s world view. And, you know, I tend to, I’m sort of an extreme optimist, I think, which is maybe one of the things that made me gravitate towards David Deutsch. But I guess that in one area where I have a little bit harder time being purely optimistic is more aesthetics. Like, well, I always ask, I wonder a lot, is music getting better? I mean, do you think it’s really improved? It’s hard. I do, yeah.
[00:30:23] Red: You do.
[00:30:23] Orange: I do, yeah. I’m pretty,
[00:30:25] Red: yeah, I know a lot of people are like, oh, well, the oldies, but like what people don’t understand is it takes time, it takes time for something to become an oldie. And there’s, and the creativity now is beyond the wildest capabilities you could possibly think of. I mean, back in the day, it was like, we brought like being Crosby and like Frank Sinatra and like even, you know, through the 70s, 80s, 90s, even early 2000s, you’re using like tapes, you’re in the studio actually sampling, you’re cutting a tape and you’re pasting it and you’re, and then like, it’s extremely intensive process, right? What would Floyd had to do to get all those sounds and stuff? Yeah, you’re at most using five instruments or maybe two guitars, a bass and a vocal drums, right? And that’s basically the palette you have to paint with. Yeah, now you’re going to get the record deals, right? Maybe there’s some artists making it big. It’s now a lot more homogenized, but at the same time, people are, it’s a renaissance in art right now. I’m telling you, I’m telling you, electronic music, which is what I’m in, it’s bigger than it’s ever been. Festivals are selling out in minutes, tens and hundreds of thousands of people. So it’s music is still very much alive and people are innovating and just doing stuff that was completely impossible. And so now there is more noise out there, right? You’re not having like Republic records signing their bands and Atlantic signing their bands. And that’s just what everyone listens to because it’s a lot more, it’s different. The ecosystem is now driven by TikTok where algorithmically driven by AI basically, right? Like
[00:32:03] Red: people are now connecting with artists that are doing stuff in their bedroom, like 17 year old kids. One of my favorite artists in the entire genre, 22 years old. This kid just learned, knows how to produce in a DAW. And he’s making the craziest house music. So it’s been a genre since the 80s, but he’s pushing boundaries. He’s already collaborating with Skrillex playing headlines. You know, his name is ISO EXO and knock two, both of those. But I think that there is so much good music coming out actually. And for me, yeah, I just think there’s so much, there’s so much that can be done with now this, this mindset of, because for me, it was like, once I realized I was like, man, I can go into software and work from home and, you know, pay my bills or I can try to grind continually to make it in music for a fraction of that. And it just made me realize I was like, I don’t really care about monetizing my art at the end of the day. Like I really just want to make art for art’s sake. And now I have the tools and it’s helped me, allowed me to be like a lot more experimental. And so now I’m making songs with multi -genre, cross -genre, all sorts of instruments, all sorts of sounds. That stuff is not possible. If Beethoven was alive right now, he would have been a music producer. He would have been like Hans Zimmer, you know, like it’s, it’s just, it’s the tools doesn’t, I feel like the tools doesn’t affect art as much as we think it does. I think there’s so much good quality out there. People just push boundaries and make cool stuff.
[00:33:28] Red: So I would say there’s, there’s so much innovation going on now. There’s so much new territory that we don’t even know how to fully cover it right now. And we’re continuing to, it’s like a new genre, a new artist pops up all the time. And so anyways, that’s all I have to say about that. But I, I actually am very excited about the state of music. I feel like it’s better that right now for innovation’s sake of just like new genres, new sounds, then it’s been in as long as I can remember, like, like, I think it’s, it’s in a good place as far as creativity’s sake goes.
[00:34:02] Orange: Okay. Well, I guess you convinced me, you know, I guess you, if you looking back at the past at Bach, Beethoven, Hendrix, whatever, of course nothing can compare to these geniuses, but you know, at another level, like I, what I hear you saying is that just it opens things up and, and, and could the next Bach will probably be a teenager working at Starbucks in their, in their room. And yeah, yeah. Yep. Exactly.
[00:34:30] Blue: Have you guys seen this article? Can you see what I’m sharing?
[00:34:33] Green: Yeah.
[00:34:34] Blue: This is an article by Kenneth O Stanley idea amplification is a real exciting potential of generative AI. Are you guys familiar with Kenneth O Stanley? Peter, maybe you would be because he comes up a bunch. Do it circles all the time.
[00:34:48] Red: I’m not either.
[00:34:49] Blue: So he wrote a book called why greatness, why greatness cannot be planned. And so he, what he is, is he’s, he is a researcher that is trying to work out the problem of open -endedness, which is, many people don’t even know that there is a problem of open -endedness. So in a nutshell, take a look at human creativity and the creativity of, of biological evolution. And they seem to have some sort of open -endedness where they can just keep creating new sorts of innovations. Whereas when we try to program evolution, it tends to at least before chat GPT, it tends to be very narrow. So that’s why we often refer to it as narrow AI. So he’s been trying to solve the problem of how do you solve the problem of open -endedness? How do you write an algorithm that’s actually going to create increasing amounts of novelty and just kind of be open -ended in what it can do. And that’s what his book is about. So he wrote this article about his, what he’s, how he sees genitive AI and he, he refers to it as idea amplification. So basically he mentions, and I’m sure a lot of people have had this experience that you accidentally come up with some song in your head. So he would start to hum a song and he would realize, oh, this isn’t some song that I’ve heard somewhere else. I’ve made this song up and then you kind of forget it. So he started to actually tape himself and he collected over time all these little songs that he had composed. Now we’ve all had experiences, maybe even with songs, but are similar to that where we have these ideas and we just lack the skill.
[00:36:36] Blue: There’s just no way that we can act. And if you wanted to go make that idea into a reality, years of study sometimes, right? Or you would have to go pay lots of money to pay somebody else. And so basically we have, we’re creative beings that have these ideas all the time. We always talk about everybody has the million dollar idea. That’s probably true, right? So we have all these ideas all the times and because of the way things are, you know, the limits of skill sets and the limits of money and things like that, most of these ideas just die and they don’t go anywhere. Generative AI, what it is, is its idea amplification. This is the way he’s saying is trying to suggest it. It’s that now if I were humming that song and I said, oh, that’s actually a pretty good song. I could actually go produce it, right? I could get the AI to get hum it to the AI and then I could start working with the AI to come up with an orchestra that plays that song. Things like that. I’ve had numerous ideas for video games I wanted to make and I’ve never taken the time to go learn how to both learn how to program video games using like Unity 3D, but also to be like quit my own models. Like I would have to go use pre -existing models if I wanted to make a game. For school I did make a game and use a lot of pre -existing models.
[00:38:02] Blue: You can do a lot with pre -existing models, but like now that they’re making generative AI that will make 3D models for you, describe what it is you want and then it’s going to come up with the model. Eventually I’m going to be able to take these ideas for video games that I have and I’m going to be able to produce a first version of it.
[00:38:20] Red: Yeah. I think it’ll be go beyond the first version. I think like you’ll be able to, we’ll get to the point where it understands video game storyboarding. It understands like every aspect of that profession. You’ll be able to say, hey, make me an Elden Ring too and it will do it. Like it’ll be able to do that. So
[00:38:39] Blue: we should really expect that with generative AI, we’re in some sense unleashing human creativity. The generative AI is not itself creative. It needs that initial spark or prompt that comes from a human. This is his argument. Anyhow, you’re welcome to disagree with him, but I’m just summarizing the article. It needs that initial spark of creativity from the human, but we have those sparks all the time. It’s just mostly they die out because skill sets are hard to come by. So I just thought that was a really interesting thing. And by the way, he’s just somebody worth reading anyhow. He’s a very creative guy who’s come up with a lot of really interesting theories and ideas around what creativity is.
[00:39:19] Green: So one thing that stands out to me as I’m using, I find this especially with mid -journey, the better you understand the art form, the better able you are to utilize the models or the, you know, the AIs. And even with this guy’s example of music, like you still need to have a working knowledge to be, to know what to ask for. It doesn’t really stop the need for skill. It just makes it so that it’s much easier, that the barrier to entry has been taken down, but they’re still incentive to learn the skill and to become skillful. Right. I mean, to really use mid -journey effectively, you need to understand, you know, art history and how humans have described art forms across the eras so that you can say, you know, make this in the style of Da Vinci. Because you can get, I mean, you can ask mid -journey to just do abstract things. And it likes that. I mean, I don’t, not to overly personify it. It comes up with really interesting ideas when you give it very open -ended stuff. But if you want to create an aesthetic that’s in your mind, you have to be able to find the right words that will make that generate. And it can be very painful to find those words. I was working on a presentation that I made all of the visuals inside of mid -journey. And there was a certain aesthetic that I was trying to use or create and that I then wanted to kind of pull across all of the different concepts that I was trying to get past. And it took me a long, long, long time. And a lot of just, now I’ll try this.
[00:41:32] Green: Now I’ll try this. Now I’ll try tweaking this one word. Because like when you give, it’s the same thing with chat GPT. When you give a prompt into these AIs, different words can have very outsized impacts on what it chooses to create. And then you’re like, oh, but that’s like totally the wrong feel. And sometimes you have to almost unwind to try and figure out what’s the word that it’s kind of making it go sideways on. That’s impacting the tone of the voice or that’s impacting the output in such a way that just is kind of ruining it, being able to create what I want it to create. Which is maybe true of life anyway. Like part of why I think jobs are hard is we’re not great at communicating. So if your boss comes and says, I want XYZ and you go and make XYZ, he probably didn’t communicate effectively what he wanted and you come back and he’s like, well, that doesn’t match what I wanted because he’s not great at describing what he wants.
[00:42:36] Red: Yeah, I think it’s like comes up. My advice for anybody that wants to get into AI and like get the best out of it is you just have to talk to it. You have to learn how to communicate with it. It really is like prompt engineering, right? And I think it’s like the more you play with it, the more you understand its capabilities, how to talk to it. And so I really think everyone should just be doing it now. Just talking to it, getting to understand it. Applications will start to apply themselves as you start to just appear as you start to understand what it can and can’t do. I was mentioning to Bruce, one of the things that I love is just using it for education now. For example, one way that I use this, hey, I don’t understand how to do, for example, I don’t understand how to comp vocals. That’s a good one. I don’t know how to do this best. I want you to pretend that you are now music professor, GPT write me a college course about comping and editing vocals. They’ll take all the information it has about that. And then I’m like, okay, give me a transcript. And then it will be like, okay, it has the professor talking about it. And it teaches these concepts. And you’ll learn from it. And I think it’s just like, it took me a second to get to that. But for me, and I think it goes back to the ADHD thing, is everybody has different learning ways of learning. For me, having somebody there teaching me and talking to me and letting me ask questions, that’s my best way of learning.
[00:44:10] Red: Some people can just read text and really internalize it. For me, it’s that way. So I hope in the future, you’ll be able to learn, hey, maybe you’ve learned best talking to someone. So they’ll attach a large language model to a generated avatar. You’ll be able to converse with through natural language. Like talking, maybe some people will do better with typing. Maybe some people are better with visuals. And so we’ll be able to generate visuals based off of the text or copy. And you’ll be able to be educated in your own preferred way when you’re in school. And yeah, that might completely tear down the existing schooling system and testing. But maybe that’s a good thing. You know, maybe I was, I don’t remember who it was, but I was listening to someone talk about it. And they were basically saying like, right now we, you get rewarded for just guessing on multiple choice questions. At the end of the day, if you, if you, if you guess on a multiple choice thing and you get it right, it’s good. You’re positive who like, but like in the real world application, like in the job field, but just guessing closing your eyes and throwing it dart is not usually the best way to like go about completing tasks where you’re trying to do. And so, you know, in the practical world, it’s a lot more about learning, you know, skill and how to perform at a specific job.
[00:45:34] Red: And so hopefully it takes away a lot of the, sorry for, you can edit my word about bullshit in the, in the, in the, in the education space of just wasting time learning things and doing things that don’t have real world application to where you just have the ability to learn anything that you want in the format that you want through AI. I think the education side of things is going to be fantastic. It’s going to be absolutely game changing. I think about my son going to school. I have a four year old. He’s turning five, you know, in this next month. What is his life going to be like? What is his school going to be like? It’s going to be a completely different experience than mine. You know, imagine it’s like the difference between being raised on that, the abacus to the TI 89 to like, you know, to, to now chat GPT in large language models, like an AI, like that is going to be a significantly different experience. And I, it’s going to be interesting to see what happens.
[00:46:33] Blue: By the way, well, I just wanted to comment that training sites are taking a giant hit over chat GPT. A lot of these sites that have videos that training videos, they’re finding that there’s significant drop off to subscribers.
[00:46:50] Red: Well, you can scrub through YouTube videos that hopefully have that one nugget of information you’re trying to find. That’s like very specialized, especially once you get specialized and, but, or you can just ask GPT to find it for you. It’s a different experience, you know, like for music, production is a great one. We were talking about this last night. It was like, I was helping my brother Tyler get set up on music production software on his new laptop. And he got, you know, some controllers and we’re like, how are we going to link these controllers? I don’t know how to map these. So we asked you happy chat GPT and I was like, do you realize, do you realize how much of an advantage you have? Like, don’t Google it, chat GPT at first, then Google it. And if you don’t know how to do something inside your music software, because I had to go ask other producers. I had to go find some other producer online or become friends with them and be like, how, how did you solve this problem? Or find, you know, some, you know, some YouTuber had uploaded it and I had to go scrub through a bunch of videos to find the information I needed. So it’s already making like such an advantage, such an advantage to be able to learn information, especially about specialized fields that already has data on.
[00:48:01] Red: Well, and Google has long had a problem wherein, you know, because everybody’s got an opinion and now everybody’s got a website where they’re sharing that opinion, you can sometimes, if you have a obscure enough question, you can be four or five pages into Google results where, where it’s either pages like that are selling something or it, it has become more and more and more difficult to get good information out of Google. Agreed.
[00:48:36] Green: Without, without having to really slog through. I’d say any social platform like right now, it’s so cluttered and monetized and it’s so, it’s so it’s everything’s already all built off of attention and ad revenue rather than like actual information.
[00:48:52] Red: It’s like content rather than actual important information or art. Like it’s a big problem with the way that like fate like Meta and other companies deployed AI very tricky and makes it difficult to, to get good. Yeah, I could go on forever about that. I don’t think that’s probably the right vein to go here right now, but yeah, I agree. It’s nice to be able to just get the information without having to deal with all that.
[00:49:20] Orange: Can I ask you another question about music, Brendan?
[00:49:23] Red: Absolutely.
[00:49:23] Orange: I’m going to, I’m going to play devil’s advocate here a little bit. And it’s interesting for me because usually I’m in the camp of being the crazy optimist in these kinds of discussions, but I’m curious how you’ll respond to this. So do you know the artist Nick Cave?
[00:49:44] Red: No, I don’t.
[00:49:45] Orange: Okay. He’s kind of like a singer songwriter guy’s been around since the 80s, but he’s also a writer kind of very literary kind of guy too. But someone I wrote to him and asked him and showed him a, one of his songs that was, it was written by chat GBT. Like someone said basically, let me write, write, write a song in the style of Nick Cave or something like that and showed it to him. Let’s just say he did not like it very much. Let me just read you just a short paragraph here about what he said and I’m just curious how you’ll, how you would respond to that. Songs arise out of suffering by which I mean they are predicated upon the complex internal human struggle of creation. And well, as far as I know, algorithms don’t feel data doesn’t suffer. Chat GBT has no inner being. It has been nowhere. It has endured nothing. It has not had the audacity to reach beyond its limitations and hence it doesn’t have the capacity for a shared transcendent experience as it has no limitations from which to transcend. Chat GBT’s melancholy role is that it is destined to imitate and can never have an authentic human experience, no matter how devalued and inconsequential the human experience may in time become. What makes a great song is that not what its close resemblance to a recognizable work writing a good song is not mimicry mimicry or replication or pastiche. It is the opposite is an act of self murder that destroys all one has strived to produce in the past. It is those dangerous heart start stopping depart departures that catapult the artists beyond the limits. He goes on and on and on.
[00:51:42] Orange: But what do you what do you think is there a danger that as music moves away from becoming like about humans and human experience that it could get worse?
[00:51:58] Red: Honestly, I feel like that’s some pretty gay, creepy stuff. I don’t really that’s not really my ideology behind music at all. Actually, I would say I would say I don’t think that I feel like that’s just such a yeah, that feels anti technology to me. And it feels it feels gay keep you because the truth the truth of the matter is it’s just another tool like Ableton what I have now like that completely eclipses the studios of probably what he was working in the 80s, right? But I’m sure he’s I’m sure his producers if he’s still making music or using that tool that’s speeding up his workflow immensely. Like I think that like it’s it. Yeah, maybe in the context of like. And even then I don’t know if I agree with this either because like have you heard of the whole thing with the weekend and Drake and the ghostwriter and all of that? Have you heard that story? No, I don’t know.
[00:52:49] Orange: No, I know.
[00:52:50] Red: Basically the two biggest artists in the world. One of them is the weekend and the other one is Drake. We’re going to you’ve gotten to the point where now you can have you can I could sing even just recording into my air, air phone or my air pod earbuds here. I could sing a verse, right? I could write and sing a verse and then it will actually completely clone my voice into like the weekend’s voice or like Drake’s voice or Kanye West voice, right? And it does it really, really well now. So we’re talking this is mid -journey reaper at the door type five for the music industry. It’s already here. It’s happened. There’s an artist that he put a sheet over his head and he put like sunglasses over his eyes. You can’t eat. You don’t know he is an honest person called ghostwriter and he’s just dropping these Drake. Like these basically AI generated Drake tracks and these AI generated weekend tracks on all over. Can you guess what people are doing? They’re listening to those songs.
[00:53:50] Blue: They’re getting millions and millions of plays and everybody loves them.
[00:53:54] Red: And you go on tiktok. There’s tons of people that are like, wow, like this song is so sick. They have no idea that that song was generated by a completely different person and they just use trained, you know, data from these vocalists. So there’s there’s kind of two, there’s kind of two mindsets here. You’ve got Grimes. Have you guys heard of Grimes? She’s to, you know, she’s she’s been a musician for a long time. Yeah. She embraced it and people, everyone can use her. She lets you train her voice. Yeah. She’s trained her voice and she lets artists use it for free and you can throw it out out there, give her, she gets a percentage of it. So I could, and I actually have considered doing it for this new record. I’m working on having a Grimes feature, downloading it, writing something. I’m a good writer. I’ll write something in the style of Grimes and then have her voice on there. So I just think like it is going to crumble the music industry, but good because the music industry is dumb right now. It is an absolute mess. It’s it’s it’s people who have money are, you know, like artists that that have, you know, mommies and daddy’s money are the ones that make it and it’s very gate kept and it’s very who you know, and it’s very toxic. And so, you know, you look at these big acts like the weekend or the Drake, they have entire teams of underpaid writers creating their stuff. It’s not like they’re getting out and stabbing themselves in the heart and saying, here’s my art. Like that is not what’s commercially being, you know, consumed right now.
[00:55:27] Red: It’s it’s already a bunch of writers writing stuff for an artist that’s then singing it and they’re being marketed as it. It’s it’s all ghost writers that are underpaid. So it’s like these guys like I hope it kind of levels it. I hope it it kind of breaks down the industry to where you can’t really create the same kind of like I don’t know how to put this, but just it’s it’s already not good. It’s and it has been that way for a long time. You look at any hip hop. You look at any genre. People are complaining about the industry all the time. So I hope it does level it. I don’t think that they those like the record labels and the industry hasn’t figured out what people actually want. And I think it goes to show that like people will consume stuff that they think sounds good and there’s a lot of ways to create that. And I think AI will help level the playing field where I can write songs like Drake without a writing team and use that emotion that I have like we go go back without having to have that barrier to entry. So I don’t really agree with that mentality. I can see how there’s a lot of people who are a very scared reaper at the door vibes. I get it. I totally understand, especially if you’ve made a career in it and you’ve been doing this professionally, it is scary and commercial work is going to be completely destroyed. I mean, it’s the same thing as stock footage and stock video. But at the same time, I think I think it definitely can create amazing art.
[00:56:56] Red: Like I use it to say, here’s the feeling of the song I want. Here’s some ideas. Give me some other lines. And it will come up with amazing lines that totally feed into and add to the lyrics. So I just, yeah, I think it’s a, I think it’s a cool tool. I already use it all the time and people connect to it and they love the, like the lyrics. I’ve literally, I was writing one with my friend over zoom and she, I showed her chat GBT and she’s like, what these lyrics are amazing. I was like, yeah, we can use this piece, this piece, this piece. And then we built around it. Right. So I think it, yeah, maybe, maybe he’s right. And the aspect of, of maybe, you know, let’s hypothetically say music, I exist that can do it all. I think stupid people, there’ll be a time and place for that. People will still dance to that. People will still like it. Most people will not be able to pass. What will the Turing test with music? At least they’re not going to be able to tell whether somebody made it or not. But I will say that it always value to human creativity. I agree on that aspect to where we’ll come up with unique ideas that can be made.
[00:57:54] Blue: So yeah, can I actually take a stab at answering your question, Peter? Of course. So I do think we’re talking about possible, like the two theories being put out there as competitors might not actually be competitors. Right. So one, one person is saying the, the musician is in essence saying chat GBT or AI generative AIs will never be able to compete with humans in terms of creativity. Well, if you’re talking about a straight contest of just a human without chat GBT and just chat GBT without a human, they’re probably right. So, I mean, like, I don’t think we’re ever going to come up with AIs that come up with some new innovative type of music. And there was no human involved at all for that initial spark as Kenneth Stanley was suggesting. I don’t even think that’s possible because these are probabilistic models that are built on, on top of only what has come before them. On the other hand, that’s just a false dichotomy. Right. So if I could use like maybe an analogy with, with chess. Okay. So you have the world master chess Gary Kasparov and he gets beat by deep blue. And so then people hail that computers are now the best chess players in the world. Well, if you’re only either a human or a computer, that’s true. A computer will always be the human now in chess. But if you really want to be the best chess player ever, the best chess players in tournaments are actually hybrids between computers and humans. They have these a human that works with a machine and uses the AI.
[00:59:37] Blue: They will beat an individual AI and they’ll beat an individual human because that creativity from the human and the processing power of the machine collectively are doing things that are different. And the computer is not generating things in the same way a human would. So you’ve got this, this combination that’s actually more powerful than it either individually. And I suspect that’s what like if you were to look at Brendan’s answer, go back and listen to it. I think that’s what he’s saying, right? Is he saying, well, I’m using it as a tool, right? I’m not doing this entirely from scratch. He’s not doing this entirely from scratch without him in the mix. I think you’re going to find that that’s going to be true for everything, that the best music will come out of someone who uses generative AI and they are creative. And it doesn’t have to actually be this dichotomy between just a human or just a computer.
[01:00:31] Red: I mean, that’s all on the predication that we don’t have a AGI or ASI in the next few years.
[01:00:37] Blue: I’m assuming that we’re talking about non -AGI.
[01:00:41] Red: We’re talking about current landscape actually right now. This is already in play. This is already in play in the music industry and we are about to see how it unfolds. So you’re right. And I like that answer.
[01:00:51] Orange: Yeah. No, I agree. I think if you look back in history, I mean, it used to be that to become a musician, you’d have to go to music school and which meant you probably had to be rich. And, you know, so this is a long process of things opening up of the, you know, like you say, the word, the gatekeepers going away. And now we’re at the point where a teenager can make excellent music in their room with no formal training whatsoever and potentially reach a billion people, billions overnight. And I think it’s probably on balance for the best.
[01:01:31] Green: In a way, it’s very similar to the invention of the printing press. You know, prior to the printing press, you could get books. They were primarily the domain of the church or, you know, the monks were the ones copying the books so that there could even be books. But once the printing press came along, it decentralized knowledge and made it so that knowledge could be pushed out across the world in a way that had never happened before. And it ignited the Renaissance. It, you know, it changed the world. Everything we have now is kind of can be tracked back to some of that happening. And it’ll be the same way with the AI. You know, somebody still has to bring that creativity because yes, unless we get AGI’s, the AIs are creative, but they need a human to not just be derivative.
[01:02:40] Blue: Yeah. I was just going to comment that when Brennan said, well, you’re assuming not AGI, he’s completely right. AGI would be total game changer, right? Everything I say goes out the window with that point.
[01:02:52] Green: But we have on this podcast a theory that none of this is, none of the explosion of AI means that we’re any closer to AGI.
[01:03:02] Blue: I agree. I completely believe that the models that they’re currently going down are not pads to AGI at all.
[01:03:11] Red: I think it will probably just speed up the ability to effectively do research to head towards that direction. It doesn’t mean that the current algorithms they’re using are going to result in that. But I do think it’s going to help with efficiency across that area of, and there’s a lot of now attention on that area of science. So I wouldn’t be surprised if it has a direct correlation with that if it does end up happening. I think my hope is it’s going to fix a lot of human suffering even before AGI.
[01:03:46] Blue: Well, there’s always going to be a need for regular AI. Regular AI is by itself a completely mind blowing field even if you’re not factoring in AGI. And this is something that I’ve kind of tried to bring out in this podcast. I know that a lot of the fans of David Deutsch really dislike AI because it’s quote, not AGI. That’s totally the wrong attitude, right? Even after we invent AGI, AI is going to continue to be one of the most important fields of knowledge that we’re ever going to have because you still need to automate tasks. You still need to be able to have mindless computers doing things for you. There’s all sorts of reasons why AI is by itself an interesting field. And Brendan has this right. It does indirectly impact AGI. For one thing, I’ve argued that it’s at least shows you how not to make an AGI. And that’s not a small thing. Like Popper says that the way you come to understand a problem is by failing to solve the problem. AI has a number of AGI failures that are going to be part of how we eventually come up with AGI. Also, I said it has nothing to do with it, but it’s not quite true either. I think chat GPT teaches us something important about AGI. And I’ve argued on the podcast and elsewhere that it’s the first non -aero, non -narrow AI, right? It’s still built like a narrow AI, but it clearly can mimic just about any other kind of machine learning or artificial intelligence. So you can’t call it a narrow AI anymore. And I think there’s a really specific reason why.
[01:05:28] Blue: And I’m guessing this is a conjecture, but I think it’s because language is universal and that it is one of the key missing pieces in understanding AGI. We kind of now have this hint. If you want to study AGI, language is going to give you a hint as to universal language of humans is going to give you a hint how humans are able to explain things. I have to become universal explainers. I don’t think that chat GPT would have worked unless language had some sort of universality to it that wasn’t fully understood prior to this point. Now, that’s a big hit on how to go about trying to figure out what the AGI algorithm is. So there are going to be some indirect connections like that for sure. And if nothing else, they just make it easier to try to figure things out to process things, to process information. It would be like saying, you know, do you think the internet would help create AGI? Almost assuredly it would, right? If for no other reason than it connects us all together.
[01:06:28] Red: It helped create AI. So let’s
[01:06:33] Green: talk about legislation for a minute, because Sam Altman went in front of Congress earlier this week and said, oh, we’ve got to legislate this. And, you know, we’ve talked on this podcast in other episodes about some of the ways that both Google and OpenAI were talking about the AIs in a way that, you know, you had that engineer from Google that came out and said, oh, this is intelligent. And I think we had even talked about an article that was from several engineers at Google who said, Google’s just trying to make it seem like they have more than they actually have. And the technology is further along. And I felt like it’s marketing because they want people to believe that these AIs are more powerful than they are. But I felt like watching Sam Altman get up and speak in front of Congress was the punchline of the joke that they started months and years ago where they know that open source, they know that they are in trouble from open source people being able to recreate. They can’t monetize it. Yeah, they can’t monetize it. Google came out and said, we don’t think we have a moat to protect us from people really just being able to recreate what we’ve already done in the open source world particularly. And so the best way to constrain a piece of technology is to heavily legislate it. It inhibits innovation. And that’s what they’re doing. They’re trying. He essentially got up and said, make it so that nobody else can develop AIs except for us.
[01:08:30] Green: And make it so other people have to essentially get some sort of a registration or so it’s interesting because it seemed to me like all of the kind of fear mongering about how smart these AIs are going to be is just designed so that they can try and control the AIs themselves and try and ensure that other people don’t have the ability to undercut their potential profitability.
[01:08:59] Blue: Tell us how you really feel cameo. Don’t hold back. I love that.
[01:09:03] Red: I love that. I think that’s a very valid point of view. I totally have had similar thoughts and have heard similar criticisms. I’m curious. I think it’s hard because we don’t know actually how, if these things are dangerous or not yet, but they sound like they could be dangerous and that they should be legislated in certain ways. But like I also understand exactly what you’re saying. So it’s tough to say.
[01:09:28] Blue: Can I give my own stab at this? So I’m going to be maybe a bit more neutral than cameo, although to be honest, I heavily lean towards exactly what she just said. So first of all, let’s understand that open AI, perhaps completely unintentionally, confuses AGI and AI as if they’re the same thing, right? And so when they start talking about AGI safety, people don’t differentiate. They don’t talk about AI safety, which is a real thing that really exists today and is an important subject. And they kind of intermix it with AGI safety, which is not a real thing today. We don’t even know what that is. And honestly, there is no safety program you can conceive because we don’t understand it well enough yet, right? And this is, I talked about this in our episode 49, AGI alignment and safety. So they’re mixing two things that don’t belong being mixed, right? And furthermore, it leads to the media kind of, the media will portray it has incentive to portray it as if it’s all one thing. Let me split it out though. And let me just say, look, ignore AGI safety for the moment because that’s really a separate subject. AI safety is legitimate question. It really, really is, okay? We took classes on it in school. There’s a whole set of techniques, engineering techniques and science behind how do you try to make AI align with human need? And there will always be a need for that because these models and what you do with AI, it’s hard to specify to them, this is what I really meant. And so try to come up with how you try to align the AI with what it is that you actually are wanting.
[01:11:25] Blue: That’s actually a hard problem that needs to be solved and they’re getting better with it over time. So first of all, let me try to start with the assumption that Sam Altman, this is maybe not a fair assumption, but I’m gonna try to steal man Sam Altman’s argument as far as I can, okay? So that I’m attacking the steel man version. Let’s assume that he’s really only talking about AI safety. If we’re only talking about AI safety, then it’s a fair subject and it’s a hard problem. There are many things that already exist out there where we legislate there have to be certain minimums. So maybe you could make a case that AI safety falls into that category and there should be certain minimums. Now, at this point, if you know anything about this, probably one of the first things you’re gonna think is, well, do you actually want senators coming up with this? Do they know anything? Well, no, they don’t, but let’s steal man this. Maybe they’re getting experts. Well, who’s an expert, Sam Altman, right? So maybe they’re going to these experts and they’re using these experts to try to come up with something that’s a reasonable amount of AI safety, okay? And trying to legislate that as the minimum. Is that similar to other industries? Sure, okay. Now, here’s the thing though, this would probably be the most steal man case I could make for it. I do happen to know, and this is my libertarian side coming out, that almost invariably, that then becomes a barrier to entry, right?
[01:12:58] Blue: Now, even if you want to argue it’s a good barrier to entry or it’s a necessary one, there’s always a downside to it that now you have less competition, which is why companies are almost always in favor, the ones that already have the best safety standards. And let’s be honest, open AI does have some really good safety standards compared to probably anybody else right now, if for no other reason. I’d take them
[01:13:23] Red: over Facebook or Meta or any of the other platforms at this point right now.
[01:13:28] Blue: In Facebook, Meta and all that, they’re not doing chat, right? If you want AI safety for chatbot, for large language models, there’s nobody out there that understands it as well as Sam Altman and open AI right now. If for no other reason then, because they’re the furthest ahead, they know it the best. They’ve got the engineers who actually built the best version of it. On the other hand, there’s just no way. And Sam Altman seems like a really good guy. Like when I hear him in interviews, he seems very sincere that he wants what’s best, right? But it is impossible to know your inner motivations. Inner motivations come from the subconscious, and they are always biased in your favor. So this is what I think Kamiya was really getting at, that if Sam Altman gets himself placed as, I’m gonna help Congress come up with AI safety standards. And even if you want to argue that that’s something that needs to happen, it absolutely will benefit him, right? And there’s no way at least his subconscious isn’t aware of that fact, and it isn’t a part of how, why he is interested in this subject, right? And so I do think that this would be kind of all sides. Maybe there’s a good case for it. Maybe there’s even a good case for using Sam Altman, but there’s absolutely going to be unintended downside consequences precisely like Kamiya was saying. And those are inevitable, right? They absolutely must happen. Because of that, I think I would favor being very cautious about, very conservative about what we actually legislate when it comes to algorithms that comes to AI.
[01:15:12] Blue: Even if you could convince me some is necessary, I would say as little as possible would be the right answer.
[01:15:19] Red: I think we can probably agree that whatever is legislated is going to be poorly legislated.
[01:15:24] Blue: So whatever happens, we’ll find out, I guess, but it’s probably not going to be what I think what we would probably open would be.
[01:15:30] Red: Yeah.
[01:15:31] Blue: And it will have the effect of actually shutting down innovation, stopping competition, the open source in particular, it will harm open source efforts, the ones that are free, the ones that actually make this into give the power to the people, right? That’s what’s actually going to be lost the moment you start legislating.
[01:15:51] Green: Well, the more heavily any industry is legislated, the least less likely it is to have any innovation. You look at the places that are the most archaic in any modern things that seem normal. You get frustrated and you think, why are banks so completely behind the times? Why are things like mortgages so living in the past? And it’s because they’re heavily legislated industries that shut down innovation so that the game makers can maintain the game.
[01:16:28] Orange: Yeah. It’s just incredible to me that people aren’t more skeptical of the premise that these rulers know what’s best for this or practically anything else.
[01:16:42] Red: I think it comes down to the fact that the real rulers in this in our economic system right now are the corporations. They’re the ones that you can see that our legislation is not educated on technology. They couldn’t even handle social media and now they’re trying to legislate AI. It just doesn’t look good.
[01:17:08] Green: Especially after watching Congress interrogate the CEO of Tiktok. I don’t know if anyone watched that, but the level of questions was it… Honestly, I don’t even know how those people let the handlers of these senators allowed them to sit down and say these things because the ignorance level is just astounding. Finally, the coach stopped. It said it had maxed out on loops. I have it set for 50 loops. It’s interesting because I don’t know if it would have stopped. I think as it gets further down its execution, the stuff that it does starts becoming less and less valuable. It decided that it needed a social media strategist and it decided it needed… See, it didn’t have the expertise or the capability to create a social media strategy. The stuff that it started to do was way, I think, outside of the field a write a comic book about David Deutsch. It’s interesting that it kind of decided these things were what was important. I will export this and share it with you guys. If you want to look at it, I can export it as a PDF. It has the whole thing. I suspect that what it has come up with as a comic book is not as cool as the one that me and chatGPT have been working on together because I know the writings of David Deutsch and I knew that there were some things that I wanted to emphasize over other things. The first time I asked chatGPT to start writing a comic book, it only focused on David Deutsch’s work with quantum mechanics and quantum physics and didn’t include any of really his four strands stuff. I went back and said, okay, that’s a nice start.
[01:19:29] Green: Now let’s figure out how to bring in various four strands concepts. It was a very iterative process with me kind of refining, refining, refining. I like that comic. I haven’t looked at what it’s made yet, but I suspect that the comic I wrote with it is better than the one it’s figured out on its own.
[01:19:50] Blue: Do you have anything you can show us from the comic you’ve been working on with it?
[01:19:55] Green: Here’s David Deutsch.
[01:19:58] Red: That was mid -journey that did that?
[01:20:01] Green: I love it. It looks so good. Trying to decide what he should look like. I assume it was trying hard to find that he used pictures of him. But beyond this, I haven’t tried to make my storyline that I have into… I don’t know if I have a storyboarded it out yet. Part of it is just that mid -journey is a lot more difficult to work with than chat GPTS. Partially because there’s no… It is not a feedback interface. You make a prompt, you get results. You can ask it to iterate on those results. But if the output didn’t work the way you want, you can’t really work with mid -journey to… You can’t say, hey, that’s cool, but I was really hoping for a little less of this concept. So it makes prompting it. It just feels like stabbing in the dark sometimes. I find the words that I can use that get me certain results, but it is just very, very painful. But I will show you a little bit of the story that we’ve been working on.
[01:21:23] Blue: By the way, just as a side note, we were kind of talking about what they call hallucinations. The fact that chat GPT will confidently make up stuff. That’s just how these models work because what it’s all it’s really doing is predicting the next word based on the words that come before. It’s no different than the thing that tries to complete your… Gmail tries to complete your sentence for you that always gets it wrong. That’s really what chat GPT is doing. However, I think that’s also why it’s so good at breaking wider’s block. My daughter, she would ask people, I’ve got this problem with the story I’m writing. She does animations, puts them on YouTube. She would say, I’ll ask people, I’ve got this problem, I don’t know how to proceed, and no one ever has anything to suggest. Human beings just have writer’s block all the time. You go to chat GPT and it immediately makes something up. That’s exactly what you need to get past your writer’s block and to just start doing something.
[01:22:26] Green: This is my outline for a 10 -book comic book series. Originally, it wanted to cram all of this stuff into one book, which I felt like was just… This is awesome. Too much. And then it made up, I thought these names were pretty boring, while it’s pulling them so directly from his works. And the stories it’s thinking up are pretty cool. So David discovers an anomaly that suggests some realities in the multiverse are disappearing. And then he’s contacted by a being named Qubit from another universe who confirms his discovery and asks for his help. So one thing I find with chat GPT, it doesn’t do great at really large tasks, plus you run into the limits of how much text it’ll generate in one generation. But it just is a lot easier to use in smaller bits. So now that I have this, and I’ve got this book one, Quantum Awakening, I would probably prompt it again to write that book and just start by giving me the chapters or the storyboard outline for it, and then continually prompt it until we got all the way down to the dialogue. But if I were to ask it to just write the whole thing, it does its most average work when it’s trying to do a large amount of work. It seems to do more creative things and more interesting things when its task is smaller.
[01:24:08] Blue: Yes, I noticed that too. Yeah.
[01:24:11] Red: Very cool. Very, very cool. I love to see it.
[01:24:14] Orange: I will look forward to that too. Looks great.
[01:24:16] Blue: Okay. I have one more question for you guys. So in episode 50, we talked about the Turing Test 2.0. So I suggested that the old Turing Test 1.0 is about trying to deceive humans. The AI is trying to deceive a human, right? And if you think it’s a human, then it passes. I suggested this wasn’t the best Turing Test, that a better Turing Test would be, regardless of whether you think it’s an AI or a human, can you just tell if it’s able to creatively model what’s in your brain, right? And it’s able to put together concepts and it’s asking new questions to come up with, okay, this is what you’re thinking. Now, let’s go back to Turing Test 1.0. Because I don’t believe chat GPT could pass Turing Test 2.0 for any period of time. Could chat GPT, for many people, pass Turing Test 1.0? Could it fool people into thinking it’s a real person? And for how long do you think it could do that?
[01:25:15] Green: There’s already been evidence of it fooling people. The agent that convinced a human to help it circumnavigate a CAPTCHA by convincing the person that it was a blind, like they had some sort of a disability that made it so that they couldn’t interact with a CAPTCHA. So I would say that that’s happening. But I also, as I’m like out in the world, I definitely can tell when people are using chat GPT. I feel like I can see chat GPT language really easily if somebody’s not very careful about…
[01:26:01] Red: They’re not editing it, right? They’re not
[01:26:03] Green: editing it. For example, chat GPT is very parenthetical, like way more than a human ever would be. It’s kind of bizarre a little bit. But if you just ask for output, it will include some sort of a parenthetical reference, a crazy amount of the time. It likes to describe what acronyms are inside of parentheses in places that a human wouldn’t. There are definitely things I feel like I can tell when somebody’s using chat GPT as their primary communicator.
[01:26:40] Red: I don’t know if we have the adequate… I just don’t think we know what it’s going to look like. I don’t think we know how it’s going to develop enough to know the effective test to test for consciousness or for the Turing test 2.0. I don’t know. I think that the old Turing test has already definitely been just proven as the method to go about that because we get fooled by machines all the time. So I don’t know. Peter, what do you think? Well,
[01:27:10] Orange: one thing about people is it’s pretty easy to fool us. So I guess that…
[01:27:18] Red: I mean, multi -level marketing companies exist, right?
[01:27:23] Blue: I actually am of the opinion that when you really stop and think about how often we actually engage other people in a creative way, I think that a lot of our interactions could be entirely replaced with chat GPT, right? It’s… Maybe even the vast majority of our interactions with other human beings could be replaced with chat GPT. And in that sense, I think Turing test 1.0 has been passed, right? Because for no other reason than because most human beings that you talk to throughout your day that you have to interact with while you’re buying stuff or online, they’re just acting like chatbots anyhow, right? They’re not actually trying to carefully hear you out and understand what you’re saying and things like that. So in that sense, I definitely think chat GPT probably could fool us in a lot of human circumstances that already exist and that you’re already used to.
[01:28:22] Red: Yeah, I think just an idea that I doesn’t really have a direct to do with this, but something to kind of round this out that it’s just been something I’ve been thinking about is I think this is kind of a good time to remember to stay on your toes and stay versatile and being willing to pivot because we don’t know where this technology is going to take us, but what we do know is that, like, it’s probably going to change your plans of what you thought your future was going to look like. That’s just how technology, what technology does to society. So I think the best thing you can do is just stay on your toes, keep learning and educating yourself as much as you can, learn to work with it. And who knows what it’s going to look like in the future? You don’t know and it will change your job. It will take your, it will automate, like for example, I’m in like corporate SaaS sales, like so much of it is me talking to another company’s representative and negotiating prices for software. But really, at the end of the day, there’s a number that we have on our side that we’re willing to go down to. There’s a number that they’re shooting for when they’re trying to purchase it. Like it’s all done through email and phone calls. There’s no reason you can’t just have that automated eventually, you know what I mean? And then you’re working on bigger picture stuff. So I think it’s, but, you know, I think that at the end of the day, it’s just stay versatile.
[01:29:41] Red: I’m probably not going to be off software salesman doing the same thing in five years that I’m doing now or five years ago, you know, and maybe that won’t even exist and I’ll be a prompt engineer for the, who knows? You know, but I think don’t, don’t, good advice is like be willing to pivot always and just keep learning skills and keep learning to work with the tools you have and you’ll be, you’ll be okay. I think that’s my optimism, Peter. That’s my optimism is running through.
[01:30:09] Orange: No, I agree with that. I’m going to be a net, net positive for humanity to take away. I mean, I think maybe in the future, we’ll look back to a past where people had to do menial tasks and it will just be unbelievable. You used to go grocery stop shopping? My food just materializes in my 3D printer.
[01:30:32] Blue: Yeah, yeah. No, I agree. So my last question before we sign off here is, how big of a change is AI? Like, are we talking the wheel, the printing press, the internet? Like, how big of an innovation is this?
[01:30:51] Green: My opinion is bigger than the internet, probably wheel or fire. Wow, really?
[01:31:01] Red: Wow, really? That big? Um,
[01:31:05] Green: yeah. Well, because the vast majority of things that humans do, at least in the modern world, now that we’re, we, that we don’t have to work to survive in, you know, as hunters and gatherers, a lot of it is replaceable by, by AI. And if, if the vast majority of the work that people do is replaced, then we just like when, when we didn’t have to hunt and gather anymore, we changed what work meant and what life meant and, and what it meant to live. I think it’ll be like that. And I don’t think it’s in five years because I’ve worked in technology long enough to know that the vast majority of the world still runs on paper and rudimentary spreadsheet usage. So getting to automation is not a, oh now we have AI in the world. Like it is still an enormous lift, but I do think a hundred years from now, 200 years from now. Yeah, it will be like fire.
[01:32:12] Red: I think it’s hard to say. I agree. It seems to have kind of a universal problem solver application that’s, that is the only thing I can think of that is, that is the internet, right? Obviously like for human connectivity, I would say, yeah, I don’t know. Internet probably, how do I, wheel or fire, that’s pretty bold. I don’t know. Yeah. Well, I mean, I could see that though. Well, it depends on how things go. I feel like people have said that kind of stuff about like web three and stuff like that. And you know, metaverse and stuff like that. So it’s hard to, you never know. Like we always,
[01:32:49] Green: things aren’t real, right? Like there’s no such thing as the metaverse. And web three also, there’s no such thing as not really. I mean, there’s just the rudimentary parts of it.
[01:32:59] Red: Try to
[01:33:00] Blue: compare it to the printing press or the internet. Where do you think it lands?
[01:33:06] Red: It’s all information dispersal to me. That’s like, like for me, that’s the, that’s the most interesting, right? Part about especially printing press at internet. It’s like mass. Like if you wanted to learn about anything, you’re going to a library before the internet, right? And then now we have connection to all sorts of communities around the world. It’s kind of homogenizing a local or like a global kind of intelligence. I think AI is on that level. On education side and connectivity side, but it also has like this application and automation side to fix a lot of like basically supply chain issues and a lot of like miscommunication issues. Like there’s just so much that it’s going to be applied towards that it’s really hard to say. So I would say probably at internet level. I, yeah. I don’t know. Yeah. Maybe printing press level then. Yeah. Who knows.
[01:33:56] Blue: By the way, I would argue that when we say the invention of the internet, that a lot of times we mean the invention of Google search, which is in fact, AI, not the internet. So true.
[01:34:07] Orange: True. Howling point.
[01:34:08] Blue: Peter, your answer.
[01:34:10] Orange: Oh, well, you know, it’s hard to compare to fire because that’s so tied in to survival, basic survival, I guess. But then, you know, it does certainly doesn’t seem an exaggeration to say the internet or the smartphone or something else. It’s going to change a lot of people’s lives. So, you know, I’m, I’m definitely moving more, more in that direction. All right.
[01:34:35] Red: I was going to say one last thing I says, I hope the, my closing thing is I just hope that it, it provides us with the experience to go back to being more human rather than and having a more human experience rather than doing these court, like medial corporate tasks for the majority of our lives. Like, I hope that it frees us up to be able to experience more of our life as a human being in it rather than, you know, continuing to just do. Brands corporate tasks the rest of for the rest of our careers.
[01:35:04] Blue: I completely yes. Absolutely. That is what I’m hoping for too. I know that that’s not been the most pleasant thing is a lot of careers. Some people are really into it, but I think a lot of us just survive them. All right. Well, thank you guys. This has been a interesting, stimulating conversation. I really appreciate all your thoughts and everything that you guys, particularly Brendan and cameo, your, your actual uses of this technology has, has been very fascinating. So thank you.
[01:35:37] Green: Yeah. Of course.
[01:35:38] Orange: Thanks for having us on. Thank you everyone. Really nice to meet you, Brendan. Great to meet you as well. Absolutely anytime. Thanks guys. All right.
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