#1300 - Empowering Minds with AI: Steven Schrembeck on Technology, Self-Control, and Mental Clarity
Source: interviews/1300-empowering-minds-with-ai-steven-schrembeck-on-technology-self-control-and-mental-clarity.mp3
SHA-256: 28661444f85f0c64fd233548f0597043a622656de87707bc9a1f6ed69b785a94
Model: scribe_v2 | Transcribed: 2026-10-10T18:14:47.317268+00:00
Machine transcript — uncorrected. Speaker labels are local to this recording and do not identify people.

[00:00:00.460] Speaker 1: College football is back, so Hilton called in me, the superstition concierge, to make your fan rituals a reality. Need a room to match your lucky number? We got you. Wanna make sure our team doesn't wash your lucky jersey? [sniffs] Ooh, that smells lucky. [whistle blows] Hilton's unmatched hospitality can keep up with any superstition, even a marching band wake-up call at 5:55 and 55 seconds. Hit it. [marching band music] When you need a team that will do whatever it takes on game day, it matters where you stay. Hilton, for the stay.

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[00:01:02.340] Speaker 3: Good morning, guys, and welcome to the podcast today. I've got a fantastic guest for you coming out of the AI field, Steven Shrembeck from Georgia, rights out of, right outside of Atlanta. It's gonna be a really fascinating conversation because he's a startup founder working on AI for self-control and stability. And I'm always trying to get a pulse of the emerging technologies, trends, and fields, and I'm really in- interested and curious about, or in this area. So I'm really happy to have Steven on. So welcome, Steven.

[00:01:38.100] Speaker 4: Good to be here. Nice to meet you, Chris.

[00:01:40.180] Speaker 3: Yeah. You have a very interesting background and talk about your early experiences and what you're doing, and we'll dive right into the conversation.

[00:01:49.400] Speaker 4: Yeah. I'm gonna sound like the opposite of impressive at first because I started out in, in college thinking that computer programming was something that was too hard, and then ended up switching into a computer science related major. From there, I did a pretty routine software development, and then I got a job at Amazon, not AI related, just regular software. About 2016, I started realizing that deep learning is having a second renaissance. This is incredible stuff. This is now like entering the level of complexity where as a regular software developer you can begin to understand

[00:02:24.260] Speaker 4: it with a little extra work. So I started training deep learning models and, uh, mostly vision models, some audio models, stuff like that. And then of course there is a third wave of AI revolution here where natural language processing, the advances there combined with transformers and other deep learning models to give you, yeah, large language models that you're all familiar with. And all right, great, so now I'm gonna learn this. It's at an even higher level of abstraction. And so I've been building my own stuff for years, some models as well through my day job, and now I'm applying everything I've learned to just

[00:02:59.200] Speaker 4: make tools that help people. Not like sensational AI, just like really practical. I'm using it where it's the right thing to do.

[00:03:09.100] Speaker 3: Really interesting foray, and I was actually have this kind of curiosity 'cause I was watching this YouTube with a podcast with, it was Marc Andreessen and Ben Horowitz and like Peter Diamandis and a lot of these AI innovators, and they were talking, and also Sam Altman, and he was talking about large language models as the baseline and was very akin to the browser wars, like which, which company is gonna come out with the, the most dominant one. And right now it looks like OpenAI, but does doing a lot of things with their LLaMA. But the question I have for you, 'cause it really sparked my curiosity, is like these

[00:03:44.020] Speaker 3: AI models are based on language, but they, he was talking about AI models being based on video and pictures. And what are your thoughts on models, AI models based on things that are not based on language, but like videos and pictures?

[00:04:02.820] Speaker 4: Yeah. This is slightly less explored, but this is coming to the foray in multimodal models. There's been a lot of advances in the encoding. At the lowest level, your large language models have taken little chunks of words. You can imagine the word, I don't know, waffle, broken up into just a few pieces. So sound wa and then ful. It's not necessarily how it gets split, but that's about right. That's like the lowest, that's the atoms of large language models. And then those little pieces get rearranged in a sort of autocomplete way, and that's how it thinks, right? It thinks at that low level. It's, those are how it represents its

[00:04:37.340] Speaker 4: information. But how do you go from the word waffle to a picture of waffle? Something only knows text. It has no conception. This is like describing color to somebody who has never seen it in their entire life. So this is a dimension that they've never experienced. So how do you get them to understand it, a picture of a waffle intuitively like we do? And there's a lot of techniques for converting from one to the other, but what they've started doing is actually training these things at the same time, and so that the lowest level encodings are shared representations between all of them, so that you can actually

[00:05:12.420] Speaker 4: seamlessly move from one to the other. It's really crazy. You input like the text waffle, and then it has an internal representation of the different meanings of the word waffle in context, like what a waffle is, what it looks like. It can actually generate output out the other side of a picture of waffle, and that doesn't necessarily look good 'cause that's not what it's for. But it, it shares, like it co-locates these representations together so that... And you can do that with sound, and then you can train it again with other low-level stuff. And now it begins to be able to intuit like how these concepts are related in ways

[00:05:47.240] Speaker 4: other than just text. And I think that OpenAI's model can, what is it, Sora, its low-level encodings are basically pixels and sound. But it als- it does this technique. It also starts to marry these things together with words, and it's pretty cool. It's hard to train. [laughs] These are not easy to build. No one's gonna train them anyway. Just use theirs.

[00:06:11.250] Speaker 3: It's really fascinating 'cause I'm just always trying to just keep grasp 'cause, you know, when OpenAI's, like their ChatGPT came out in November of, uh, '23. Was it '23 or what was... It s- it seems so long ago. It was very clunky. It was just like the texting, it wasn't really... But now it's like the, the large language models have been trained really well that you put in text or even images now, the output is actually pretty decent and it just reminds me of when I was using Google, like Google for search. It was just all text, right? But then you could use like Google Lens, like pictures, and you could use your voice as well, and it's like

[00:06:46.150] Speaker 3: what you were describing, this multimodal. Which brings me to my next question is, 'cause you talk about everyday usage of AI and I had another guest who was also, he was, his focus was to educate those who don't have access to AI so that they're not left behind. So when you talk about these, they're these tools to help everyday people. You talk about developing AI tools to help individuals regain control over their attention and choices in a increasingly distracted world. Elaborate on that and, and what that means.

[00:07:18.250] Speaker 4: Just like the general concept, and a lot of these general concepts you can start to apply in your own life. You don't need to use anything that I'm making or anything else. But think of it this way, like large language models specifically, and all the stuff that gets bolted on top of them, right? The... I'll just shorthand it to large language models. There's a lot of magic under the covers. It's the same with Google. You type in a search box, but you just know that there's an ocean of code under there. So there's a lot of stuff that goes into this, but for now assume it's large language models. It's basically commodity intelligence. You can think of it as not like an especially bright person, just like your average person, like a,

[00:07:53.490] Speaker 4: a, an average level of reasoning in a box. A general reasoning, and that is really powerful. One thing you can use that for, yes, you can use it to replace people. Yeah, however you feel about that, good or bad, is neutral. But you can use it to replace commodity intelligence. That's... Everyone tends to focus on that. But you could also use it in places where it would be unethical, unreasonable, or just not preferable to have a human do the same thing. So think of it like a hazmat suit, or if you've seen the show Cher-

[00:08:28.250] Speaker 4: Chernobyl or whatever, where they have, they try to get the robots to go in and clean it up. [laughs] So like y- you put it in an environments where you wouldn't want a human. So you can imagine there's a lot of environments like that on the internet. It's a lot more dangerous, predatory. There's a lot of influences. So some simple ways to use it are just send an AI ahead of you just to go look for things that it's triggering or is it good, and just pacify it or sanitize some of the things, or even just censor some of the things you don't want to experience. Get rid

[00:09:03.170] Speaker 4: of the noise, the intentional bias and inf- influences, all that sort of stuff, right? So you can think of this as having a hazmat suit. So that is a simplistic way of looking at that, but there's a lot of other environments and situations in which you would like to have human-like intelligence evaluate a situation without a human so that you don't, a human doesn't have to. So not just saving work, it's also sparing a conscious [laughs] creature from having to experience or go through this.

[00:09:35.170] Speaker 3: Interesting. It's, and I actually have some follow-up questions around just developing tools for mental clarity and focus, and also self-control and ADHD. I just wanna understand it more. If somebody... 'Cause I'm hearing a lot, 'cause I use the AI for a lot of content creation and, but I hear a lot of people are starting to use like AI for chatbots and assistants. If somebody want- wanted to learn how to use AI for this area, where would they go? Where would they start? How would you recommend them play around and tinker?

[00:10:06.510] Speaker 4: Most awesome part about this like third wave of AI, assuming you don't count the early work before the early 2000s, is that it's mostly at, it's mostly these big foundational models that are trained on millions if not more dollars. There's, nobody can run these things on their computers, not really. Nobody c- definitely can't train them. It's highly sophisticated, but they're so generalizable. It turns out that basically everything I learned [laughs] about how to construct these neural networks and the software on top of it is more or less useless. Okay, it helps conceptually understand it. Like the playing field got real level

[00:10:42.030] Speaker 4: because it's mostly prompt crafting and some light software engineering, but even the AIs can write the software. So it has leveled the playing field immensely to, to the point where, yes, it's a skill to learn how to interface with these things, but once you get good at using ChatGPT, like stitching together some software to do that in an automated way is basically just logic, like common sense, like just trial and error. And then you can use no code tools, Bubble, and there's LLM specific ones like, uh, Flowise, I think is one. There's a couple like them, where it's just like a little branching structure. If you've ever seen like a f- flow

[00:11:16.790] Speaker 4: diagram. It's okay if this, here's the prompt, then do this. Like you've got customer intake or you've got, uh, new patients or something. Did they fill out this form? Okay, was this empty? Check for errors, like talk to them about it. If that's all good, then send them to this sign-up page. Okay, then send them to this thing. It's easy. If you're a human being with a little bit of patience and you're willing to l- learn a little skills, then you don't really need software developers like me. Uh, so that's the good news, is that 80% of the use cases you're enabled to do by yourself,

[00:11:51.790] Speaker 4: and it's much more approachable. So those are the tools I'd recommend trying out, but there is no replacement for getting in there and learning the nuances of how it works, like intuitively. And this is something I'd recommend actually learning how to intuit if you don't already use the AI tools.

[00:12:08.630] Speaker 3: Yeah. I, I love this process, how you're describing just tinkering and just playing around. Um, go in and just like just see what, you know, that's how you best learn. Um- Well, the other question I have for you is, so you talk about, um, the AI tools assisting those struggling with ADHD or addiction and, you know, what are... how is this possible? What are specific features designed to help those struggling with ADHD and addiction?

[00:12:34.702] Speaker 4: There's lots of different hows. It's like a constellation of different tools, and a lot of it's just regular software. But one of the fundamental problems is you have an, the untrustworthy operator problem. Let's say you've got a bunch of system that keeps you healthy, in check. I meditate at this time. I take my medication at this time. I don't go buy drugs or alcohol 'cause [chuckles] I'm not doing that. I don't... I, I make sure that I check into work, or I, I leave by this time. You can imagine a whole bunch of systems that people with ADHD and autism rely on. However, the operator themselves is not trustworthy, both in the sense that they forget, uh, they have

[00:13:09.662] Speaker 4: low object permanence, they just don't even realize that they should be doing this, or they have emotional irregularity or motivational instability. So you simply can't operate in a way that's... Okay, I have a personal rule not to go buy alcohol on the way home. Okay that's not gonna stop you. [chuckles] Like, y- you- the operator themselves can't be trusted. So now what do you do when you- the system you rely on, you can't trust the person who's operating it? And you can have a nanny, or you can have [laughs] I guess a, a babysitter. You could have a sponsor. There are piecemeal solutions to all this stuff.

[00:13:44.782] Speaker 4: But what would be really nice is if you had a system of accountability that understood the nuance. There's that commodified intelligence. This is where the AI part comes in. What state are you in? Can I trust you? Yes or no? Like, normally you can change your rules. It's just a rules engine. Like, I do this, I don't do this, make it hard to do this, hide this from me. It's more or less it, it knows you can't be trusted, so there's like this balance between this is where you need the intelligence. Do I let you just turn all this stuff off? Do I try to block a transaction at a liquor store? Okay I'm just buying this in order to

[00:14:19.822] Speaker 4: make a, a flambé or [laughs] later. There's a lot of nuance here that brute force, like simplistic tools don't work. So in... you need something that understands. Also, you don't want it, it interrupting you or stopping you or turn- blocking your websites when you're trying to do stuff for work. There's an enormous amount of nuance in when to apply, like enforcement, and the net result of all this is that it just makes it easy to do what you wanna do, harder to do what you don't wanna do, and it makes it more or less impossible to not realize what you should be doing. And then the rest is more or less just set up your own rules. So

[00:14:55.002] Speaker 4: that's the general system. But yeah, it's for sleep, it's for electronic addictions, avoiding substance abuse, spending control. These are the most common problems that people have, and so that's what we're focused on. But the principles are general, right? It's whatever rules you got for life. But it's just imagine a little, you know, guardian angel that is constantly paying attention to what you're doing. There's some AI there as well. And then whatever information you choose to give it, it's using that to evaluate whether it should step in to enforce your own rules or not if you don't.

[00:15:27.562] Speaker 3: Really interesting. And then when you talk about ADHD and addiction, the other question is how do the A- AI tools you're developing help users main- attain mental clarity, and can you share examples of how these tools are used?

[00:15:44.222] Speaker 4: Moving things. I'm operating from the state that your standard human at rest is already healthy, so if that's not true, that's a different target audience. So assuming that at rest when healthy you're functional, then it is mostly about removing influences. It's about decreasing your level of stimulation to improve your baseline dopamine. So a lot of this is like the hazmat suit I mentioned, like it's creating different interfaces to influences. Okay, you wanna listen to podcasts? You go through this other tool that desanitizes it. You wanna browse the web, you want to look at social media, you're

[00:16:19.082] Speaker 4: gonna do it through this alternate interface that doesn't allow these things to pull your attention away. You can also tell it what your intentions are. This is what the first version of the software was. Tell it what your intentions are, and then it's paying attention to what you're doing, and if there's a discrepancy, it can just make you aware. But if you choose to... You're doing this to yourself. If you choose to follow up by adding more restrictions, "Hey, I said I was doing this thing for work and I'm not doing it after 45 minutes," go through this pretty well-known psychotherapy routine, mirroring. There's... None of this is new, right? I'm just putting together existing Legos. Follow this step, then this step. If I completely ignore it,

[00:16:54.142] Speaker 4: then I want you to turn off my internet. Not everyone's gonna do this kind of thing, but for certain problems it makes sense. Like substance abuse, for instance. You need a hard guardrail which says, "If a transaction comes through or is trying to be processed from these merchants or in this way, deny it." And that's just a hard enforcement. There are other rules, of course, to... It's never gonna be able to stop you. The purpose is just to add friction or to remove the presence of things that are making your life worse so that you don't have to use willpower. It's the, the whole purpose is you cannot

[00:17:28.722] Speaker 4: rely on willpower. These people specifically, I'm definitely in the target audience, cannot rely on willpower reliably. So this removes, it adds a backstop, and ultimately allows you to retrain your brain for what you want and what you pay attention to because there's something, there is a digital adult in the room that will eventually step in, and that is something that we lose when neurodiverse people come from childhood to adulthood. There's nobody to step in anymore if you live alone or you're supporting yourself or others are dependent on you. You need reliable ways to

[00:18:04.382] Speaker 4: not crash and burn. There's no one to step in. And so now this sort of preserves autonomy and independence and allows some software to step in by your own design. You're doing this to yourself. It's configurable. So that's the premise.

[00:18:18.342] Speaker 3: Really the next question I have for you is, 'cause talking a- about just going away from the AI and just talking about more broader, talk about this what are your thoughts on society's current challenges with self-control, and how can technology, particularly AI, foster more mindful and intentional behaviors?

[00:18:37.578] Speaker 4: Anyone relatively studied in like psychology or sociology recognizes just how we like to think we're, we have free will, but... And like we have a lot of agency. But most of our behaviors and the ways in which we can be influenced are very well documented. Like we are very well doc- they're super well-documented blueprints on how to get humans to do what you want them to do. And the sad part of this is, is that has been very well perfected and engineered upon by basically everything. Everything from business processes to the well-known attention and influence

[00:19:12.538] Speaker 4: economies, ads, all this sort of stuff. Um, it's obvious people have figured out really how to perfectly manipulate others through technology. The nice part is that you can do that to yourself, and you can also detect that, and you can stop it. So that is the role of software in this, is that you can use software to harm yourself or to be harmed, and you can just accept that. Or at the individual level or an organizational level, you don't have to wait for society to change. You can just make your own tools or set your own rules, like none of this has to be software. But what to access and what not to

[00:19:47.158] Speaker 4: access, um, and become aware of what's manipulating you or influencing you. And so that is really how I see it, is yes, collective action is great. The man is slow, frustrating, and often ineffective. Solutions are not great. So if you're waiting for US Congress to pass laws banning social media so that your 12-year-old isn't being unduly influenced, I think you're gonna be waiting a long time and you're gonna be disappointed. However, you can begin to take action now beyond just... A lot of it's simple, and a lot of it is the willingness to

[00:20:23.058] Speaker 4: notice how things are making you feel. That is su- such a simple thing to say, but notice what is making you feel bad, become committed to that, and then be willing to live differently or to be creative on how you remove those, remove or blunt those influences on you. That's like the most important thing to do regardless of what ch- tools you use, 'cause nothing is ever perfect. You gotta fit it to your life. Remove the bad stuff and do more of the good stuff. I don't think that any of this is actually surprising. My insight for building a business in software was that people know what to do. The average

[00:20:57.958] Speaker 4: person knows what is healthy for them and not healthy for them generally, but they have trouble actually doing it or not doing it. So that's where you should focus. Less on shame. Stop using effort and willpower, and just make it so that it's really hard, if not impossible, to do the things that are bad for you, and it's really easy, if not inevitable, to do the things that are good for you.

[00:21:19.278] Speaker 1: [upbeat music] College football is back, so Hilton called in me, the superstition concierge, to make your fan rituals a reality. Need a room to match your lucky number? We got you. Wanna make sure our team doesn't wash your lucky jersey? [sniffs] Ooh, that smells lucky. [whistle blows] Hilton's unmatched hospitality can keep up with any superstition. Even a marching band wake-up call at 5:55 and 55 seconds. Hit it. [marching band music] When you need a team that will do whatever it takes on game day, it matters where you stay. Hilton for the stay.

[00:21:49.858] Speaker 2: This episode is brought to you by PayPal. [upbeat music] Holiday rush? Skip the mall traffic and shop online with PayPal. Shop your favorite online stores like eBay, Fanatics, Walmart, Sephora, Target, and TikTok Shop, and choose to pay now or pay later at checkout. Plus, Pay in 4 with no interest and no late fees. Shop now with PayPal. Pay in 4 is subject to approval. Learn more at paypal.com/payin4. PayPal Incorporated, NMLS 910457.

[00:22:22.318] Speaker 3: Very insightful, and I'm sure the audience is gonna have a lot of follow-up questions. I have two more questions before we have around three, four minutes left. The other question is, the... One is AI can feel impersonal, and how do you ensure your tools foster genuine human agency and are accessible? Because I was... There's this concern from people that have access to AI and that know how to use it. They're gonna use it to, of course, enrich themselves and progress, whereas the common average person that doesn't know or is gonna get left behind. How do

[00:22:57.157] Speaker 3: you address this?

[00:22:58.897] Speaker 4: That's a profound problem, and I think that it's accurate. But that's a question that is well beyond the scope of just AI. This is any technology, what happens when you have exponential, uh, abilities. Like some people are becoming superhuman. That's a major challenge that is really a philosophical one. So that's... I won't weigh into that too much other than I would advise you don't need to be on the cutting edge. But, uh, uh, usually being about 20, 30% behind the cutting edge, being an early-ish mainstream adopter is about good. Just pay attention [laughs] and try to use these things. There was a second part to that question that I

[00:23:33.598] Speaker 4: forgot.

[00:23:35.438] Speaker 3: Yeah. It was this, the kind of the, the next question is just with AI, how do you help people use technology to create more meaningful lives? Just 'cause I know in our day and age, it's really, it's just more efficient, instant gratification, just more effective and just bam. But ultimately, with technology, we're losing meaning. For example, we're very connected, but we're in the, we're what some of the most disconnected people in human history, even though the technology is supposed to bring us together. So how, how do you, uh, use AI to create

[00:24:10.378] Speaker 3: more meaning for people?

[00:24:12.618] Speaker 4: Okay. That's a great question, and I'm willing to be late for my next thing to answer that because that's an amazing question. And I feel very strongly about this. We should not be replacing the behaviors that we want to do. We... This is where capitalist profiteering, like efficiency mindset falls flat, is that it, it... If we keep going, we've automated away everything, right? We have AI raising our children. We have technology that does everything for us. Eventually, it can just live for us, and what are we? You can just be- Put on a, uh, a feeding tube,

[00:24:47.606] Speaker 4: um, and just [laughs] go unconscious. Uh, what are you replacing? Uh, I think this is where we, we have to be quite mindful of the fact that we are... At an individual or even an organizational level, what are you omitting? What are you actually replacing? Did you get rid of the things that you wanted to do? The purpose of an AI tool is the obvious that most people talk about, to replace the jobs and tasks that people don't want to do, or that it can do it better. Sure, that's fine. Go use it for those things. That's obvious. Pay attention to where it's overrunning and recognize

[00:25:22.566] Speaker 4: that there were... there is meaning in work, there's meaning in helping people, and that you're not remove... What are you doing with this extra time? Unfortunately, if the common denominator, like the status quo, is that you go back to the attention economy, you start grazing for information, or you're in a world where nobody else is around, in the physical world it's very lonely because they're all zombies, that's bad. What are you freeing up your time and energy for? So you want time, energy, and attention freedom. That's awesome. You can keep opening that up, but if the way you allocate it is

[00:25:58.406] Speaker 4: just pointless leisure or it has no meaning for you, then you're just getting more of a terrible thing. So this is, uh, again, a neutral tool. All it does is give you more time, energy, and attention freedom, maybe some financial freedom as well. But what are you gonna do with that? You have an excess, you have a surplus of these things, but how you allocate that for meaning is critical. It doesn't... It creates more of a thing, but it doesn't mean that you're gonna use your f- newfound freedom and resources. That is an entirely different, uh, conversation and problem. I have a, a lot to, to

[00:26:33.426] Speaker 4: say on those, but I think we'll have to leave it at that for now.

[00:26:38.726] Speaker 3: Yeah, I really enjoyed this conversation, and very insightful just coming from a SaaS founder and just a leader in this area. And what if people wanted to follow you and reach out to you and connect with you, how could they do that?

[00:26:51.106] Speaker 4: Uh, there's a website, impossiblelaboratories.com. If you're a software dev or a designer or project manager, I, I'm looking for collaborators. This is a lot of work.

[00:27:00.686] Speaker 3: [laughs]

[00:27:01.446] Speaker 4: But now that I've started, like, doing user interviews and all this stuff, running a business is, like, crazy hard. It's... I don't have time for all this.

[00:27:07.386] Speaker 3: [laughs]

[00:27:07.886] Speaker 4: The loose collection of contractors plus me is not cutting it anymore. So yeah, if you... It sounded cool and you wanna try it out or you wanna help, this is mission driven. Uh, it's got profit motive because this is America. You can't do anything without a profit motive. But really it's a... This is not the easiest way to make money. I could just-

[00:27:24.386] Speaker 3: [laughs]

[00:27:24.866] Speaker 4: This, this is about helping people. So if that sounds cool, give it a shot. That's impossiblelaboratories.com. I'll put some links on there.

[00:27:32.586] Speaker 3: Excellent. Yeah. And, uh, keep up the great work, and I really enjoyed this conversation.

[00:27:37.386] Speaker 4: Awesome. Well, it was nice to meet you, Chris. And, uh, cool. Yeah, maybe we'll do a follow-up in a while.

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