Welcome to tech Stuff, a production from iHeartRadio. Be there and welcome to tech Stuff. I'm your host, Jonathan Strickland. I'm an executive producer with iHeart Podcasts. And how the tech are you now, y'all? I think I have made my thoughts pretty clear when it comes to artificial intelligence. For one thing, AI is a very broad discipline. It's huge. It's way more than just generative AI, which is a topic I feel very strongly about, and it's also the one that dominates the news cycle. But it's just one aspect of artificial intelligence. And I feel AI in general has incredible potential to augment our computing tasks if we implement it properly. Well. Recently I got the chance to work with an AI laptop and really get to grips with what that potential can be, and I'm convinced we're on another precipice, one that will transform how we interact with computing devices. Now. First, the AI powered device I used was a Lenovo Yoga Slim seven X laptop with a Snapdragon x Elite processor. It's a Copilot plus PC, which means it features Microsoft's AI Assistant. It's also got an OLED screen, and it's no joke. That's the prettiest laptop screen I have ever used. The contrast on that thing is crazy, it's amazing. It's so beautiful. Now, Snapdragon was generous in sending me this laptop so that I could actually get some hands on time with it. And I'll be talking a lot about the work Snapdragon has done to make the processor really special, but I'm saving that for a bit later. Now, I do have to say that this laptop would immediately top my holiday wish. And I'm not just saying that I could be if I had no scruples, but that's not who I am, y'all. It's legit how I feel this laptops. It's really light, it's powerful, The screen, as I mentioned, is absolutely gorgeous, but the battery life is also really impressive, particularly when you consider the power lifting this thing has to do. Even when it's running AI Enhanced applications, which y'all know AI, it requires a lot of processing power, but this laptop continued to run smoothly and I didn't have to go dashing from outlet to outlet just to keep it going. But I think the thing that really pulls me to this laptop is the fact that I can see AI enabled processors as being the tech platform of the future. So it's my belief that just as smartphones revolutionized how we interact with computing resources, you know, like apps as well as the Internet, AI is going to do the same thing. Now. Before the era of the consumer smartphone, there were very few people who were predicting a move to mobile. Now, there were a few smarty pants is out there who were ahead of the curve, but most of us didn't see it coming. Once smartphones proved their merit in the consumer marketplace, we saw a pretty rapid transition to a mobile friendly landscape. You know, Web administrators were scrambling to make sure that their websites were optimized for mobile devices lest they potentially drive away visitors who were increasingly using their phones to access the Internet rather than say, laptop and desktop computers. Meanwhile, developers began designing apps that would leverage smartphone capabilities, you know, stuff like accelerometers and touchscreens and GPS sensors, that kind of thing. Well, I believe AI is going to do much the same. We're going to see a host of new programs and apps built with AI enhanced features and devices that are capable of providing onboard AI processing are going to be way ahead of the game, while also providing ways to handle AI processing in a more secure and private approach. See, there are different ways that you can handle AI processing. One way is you offload everything to a server farm somewhere, and we hear about these a lot in the news. You know, they're massive buildings, just filled with racks of servers processing enormous amounts of data, powering AI implementations all around the world, and no doubt that will continue, that will continue to be a thing. But a complementary approach involves on device and edge computing cases in which the gadgets that we actually have our hands on can do some or all of that processing on their own without connecting to some distant server. Now it all depends upon the application, of course, but with those types of implementations, you keep the AI computations on your device, and that means you're not sharing data with some server farm that smiles away. Everything stays low, and that is a huge thing when it comes to privacy and security. Let's say that you work for a really big media company, for example, I could be using myself in this example, and you want to make sure that the work you do stays local because you're working with some sensitive information, some of it might be proprietary. You don't want to be sending that off and have it become some kernel of information that gets enveloped in a larger database somewhere. That's risky stuff. So making sure you are able to do this kind of thing locally is important for a lot of people. All right, let's talk about the overview for this whole approach. We'll get into the hows and whys a little bit later, but first I want to talk about the ways I used that Lenovo Yoga seven X laptop. So I wanted to see how an AI enhanced device could potentially help me do my work. I mean, we talk a lot about artificial intelligence augmenting our ability. I wanted to actually put that into practice. So I use the laptop while I was researching a recent episode, one that actually has already published. So I used this laptop, the Yoga laptop, specifically for that episode, and I really wanted to put it through its paces and see if it had a meaningful impact on the way I do work. Now in this episode, I referenced an extremely long research paper that was written for the journal Science and Global Security, and it was an article by Jurgen Altmann. It's actually a fantastic paper. It was incredibly readable, which is not always the case for technical papers. If you've ever tried to read one, sometimes they come across as the most stilted term paper a teacher has ever had degrade, but not this one. It's also an accessible paper. You can find it online for free, so that's great as well. But it's very long, like it's seventy pages long. Now more than ten of those pages are just notes and references, but you still have, you know, fifty nine pages of pure content there. Now, I read the full article for my research, but I need to have access to the salient points without having to thumb through all seventy pages and taking notes as I read the article. That way, I wouldn't have to thumb through a seventy page article while writing the episode. But that's not easy to do. Once you get past like twenty pages, it gets pretty cumbersome. So I use the AI assistant on the laptop to create a summarized, bulleted list of the most important notes in the paper. For quick reference. Now I'm the cautious type, and while I was using this and I wanted to really check and make sure that it worked. I also wanted to verify that the notes that were produced were accurate to the original paper, that they weren't a misinterpretation or a summary that just wasn't accurate. And obviously that added more time for me. If I had not had to do that, I would have been through pretty quickly, but I needed to check. It's not just enough to have it create this list, and it really did show that the summary was accurate to the document I was using, and that it really was the most important points in the paper that were included the summary, and it was really easy to do. It was easy to navigate to the actual source for the bullet points so that I could verify that, in fact, the information was correct, and it really made organizing my thoughts much faster than it would have been if I hadn't been able to access this tool, because while I was taking more time to verify that the bullets were accurate representations of the information in the article, it did allow me to organize the whole approach for the episode. So typically when I organized an episode, I do that by feel, and some of you might be saying, yeah, we know it's obvious, But I've been podcasts for sixteen years. I have a sense of the flow I want for an episode. Now that doesn't always mean it's the best approach, but it is the one that just feels natural to me. However, in this case, it was really nice to consult a different perspective, even an artificial perspective, to figure out how best to structure the episode. So if there was an episode in the recent past that you listened to and you thought, wow, that's more coherent than what he normally produces, well now you know why. But keep it to yourself because words can hurt y'all. One thing I didn't do but I could have done, was use real time translation tools to access information that was presented in other languages. Once upon a time, I took courses in French and in German, but I never got to the point where I was conversational, let alone fluent in those languages. And of course, over the years my skills have atrophied. So I speak two languages, English and Bad English. But I am aware that there is a wealth of information and knowledge that's captured in other languages. While there's some pretty darn good translation apps for stuff like text, the cool thing about AI powered devices is that they have the potential and the processing capability to provide real time translation for other kinds of content like audio. So one thing I could have done was watch a video that had been recorded in another language, and through using onboard AI processing capabilities, been able to read English language captions that were translating what was being said in real time. Now that opens up entire worlds of expertise that otherwise would be very difficult for me to access. And I've always said that diversity is really important. It means you get multiple perspectives providing information, and you can view the world from different perspectives, including ones that you might not have ever even considered otherwise. Now, you might ultimately not agree with this other point of view, but being able to access it is important. Otherwise you just remain ignorant of it. So from a research perspective, real time translation is an enormous benefit, and I imagine we'll see this technology continue to evolve as well. Tools can be pretty good at doing things like translating word for word, but in future implementations. I imagine AI translation will also have to handle stuff like syntax and idioms really well, so that we don't just understand the actual words being spoken, but what the speaker means when they say those things. If someone uses like an idiom like a regional saying, or they're using really complex phrasing that doesn't easily translate to English, I can imagine future AI translation tools handling that and providing a relatable translation to avoid ambiguity, unless, of course, ambiguity was the intent in the first place. Sometimes it is another thing that I could have done at the end of the whole episode because I have used tools like this before, is use AI to generate show notes. So, y'all, Podcasting is a lot of work, particularly if you have a small team. In my case, the team is me and super producer Tari, who also works on other shows. There are a lot of steps in making a podcast. You know, you have pre prep. You've got prep, you've got research, you've got writing and recording and editing and publishing. One post production step that a lot of shows will skip is the production of show notes. So why do so many shows just skip show notes? Well, I can't speak for everyone, But in my case it comes down to being a mental block. When I finish an episode, after I've done speaking my amazing words into a microphone and then shipping off the file to my producer extraordinaire Tari, I'm ready to move on. My brain has effectively said, welp. That closes that chapter, dusts off its hands and whistles as a walks into the sunset. So it can be really hard to stop and reflect on what I just created and then distill that into useful notes for listeners. But AI tools can do that automatically. Of course, after creating the notes, then I would review them to make sure that again they accurately reflect the episode. But that's one step in the podcasting process that I would be happy to hand over to an AI enabled tool, as it is a step that I otherwise find really tedious and it actually discourages me from doing my job. You know, I will find any excuse. I will invent excuses to put off doing that kind of thing. Now, while all my research and writing and recording was going on, I also was using the assistant to keep me up to speed on my daily schedule. I'm somewhat notorious for missing things like important emails and meetings and that sort of thing. I have kind of made it an art formed to make it difficult to reach me because I find it creates an environment that allows me to focus right. I want to really focus on what I'm doing, and that means I need to filter out distractions because otherwise I will stop whatever it is I'm working on, and that just ruins my whole flow. Getting back into that is hard to do. I found using the AI assistant to help block out my time so that I had specific blocks of time where I was doing specific activities made me overall more efficient and effective. I actually one of the In fact, the very first thing I asked my AI assistant to do was to help me create a working schedule and it did, and it even built in things like breaks and stuff, and I followed it. I was like, this is a real experiment. I am going to follow the schedule that's been created for me, and I found that it was incredibly helpful. It really added structure to my day, something that I haven't had a lot of because I work remotely and mostly on my own, so structure is something that I have to create and I'm not great at doing that. So using this tool to help me to augment my abilities and to take on a workload that I otherwise would find difficult to do, that was incredibly helpful and it was a really nice change. Now I can envision other uses of AI as well, though I didn't use them for that particular episode. So for example creating audiograms, and I can already use AI to do this. I have used AI tools to do this, but they were cloud based. And what I'm talking about here is using AI to identify interesting passages in an episode, like a section that's really compelling. And you could do this in different ways, Like you could use AI to analyze the written work that you create, like in my case, I write out episodes, right, so I could actually use AI to analyze what I've written and to identify, oh, this is a particularly compelling section. Or you can use it to analyze the recorded audio. Because I also go off book a lot. I don't just have a script that I read. I extemporize like crazy. If you read what I wrote and compared it to what I say, you would notice that there are a lot of departures. So using AI, I could analyze the recorded program and create audiograms, which are those excerpts you sometimes come across on various social platforms. These are ones that play not just an audio clip from a show. Typically they'll also include stuff like real time captions that will help emphasize the point being expressed. I've had some experience using AI to generate these, and that includes matching text to spoken words automatically, so that you don't have to do it on your own, like you don't have to create an animation or anything. It does it for you. Now, the tools I've used, they're not perfect, but really good. Ones typically include a pretty easy way to edit the text so that if you're like me, let's say you have a little bit of a dialect that occasionally creeps through your spoken words, then you can review and fix the little goofs that the transcription might make when you maybe get a little too southern or whatever. For the individual creator, these kinds of tools are phenomenally useful. They simplify the process of promoting your work, and they help creators make bite sized pieces of their output that are ideal for social platforms to promote and to send people back to a full episode. For example, now I have the luxury of working at a major media company, and so in certain situations, I can actually lean on other people to help me create these kinds of social assets. But even in my case, my resources have their limits. I mean, those departments are supporting tons of other shows, they may not have the capacity to work with me, and most other creators don't even have that kind of help at their disposal to start with. Being able to lean on AI powered tools can give a creator more opportunities to find their audience, to stand out in a crowded field. Okay, back to my personal experiences. One of the big bonuses of using this Yoga Slim seven X laptop is as the name suggests, the laptop is extremely portable. It is lightweight, it has an incredibly thin form factor, and if I felt myself getting restless while I was working in my office, literally, I could just know, save my progress, shut the laptop and carry it upstairs to the living room and then work on the couch. And my dog found that to be a fantastic change of pace. And while he's not quite as good at keeping me on task as the AI assistant is, I definitely appreciated the change of scenery. You know, We're gonna take a quick break to thank our sponsor, but we'll be right back. So let's talk about this processor for a moment, because that's really ultimately what makes this experience possible in the first place. So, first off, Snapdragon obviously has a very long history of developing processors for mobile platforms, and I believe that gives Snapdragon some distinct advantages because the engineers and designers are used to working within tight limitations. I'm talking about tight limitations when it comes to the actual form factor the space. You have to work in tight limitations on how much power you're going to have access to, how much heat you can generate because it is a mobile device and you're not going to have access to like massive fans or water cooling systems. You know, you still need to get all the processing power as well. So all of this sounds like it could be a bad thing, but in my experience, when you are set with tight limitations, it can really inspire innovation and creativity because you still have a goal that you're working toward, right, and then you just have to think, well, how do I achieve this goal? And if you've got those limitations, it means that certain avenues are just cut off, and you have to really focus on what is possible and then push the boundary as hard as you can. And how you create a processor that provides the compute power needed while maintaining battery life ends up becoming kind of this guiding principle. Mobile devices in particular need to conserve battery power, right. I mean, you don't want to have a smartphone that has three hours of useful life in it and then you need to recharge it. But you also need to make sure that it can actually handle the computational jobs being thrown at it or else everything's going to feel sluggish and that's not a good user experience either. So Snapdragon's approach has been to incorporate different kinds of processors all on a single chip. So you've got your CPU, so that's your central processing unit. I think we're all familiar with those. The microprocessor kind of acts like the brains of the operation. CPUs traditionally are very good at handling, you know, like sequential problems, ones that are consecutive problems where the solution to one calculation feeds directly into the next. But then you've got your GPU, your graphics processing unit. Again, I feel like most of us have a handle on these these days. I remember, I'm old enough to remember when GPUs didn't exist. They weren't a thing. You would occasionally get a graphics chip, but it wasn't called a GPU. That didn't happen until you get up into the nineties. Really, and initially these were built to, as the name suggests, handle graphics processing. But GPUs have really come into their own in recent years and have proven to be extremely powerful when handling parallel processing jobs. So those are computational problems that can split into different tasks that a processor can potentially handle concurrently rather than consecutive, so they solve parts of problems all at the same time. Now, that doesn't work for every type of computational problem, but for that particular subset, GPUs are pretty darn good. But the snap Dragon x Elite processors also incorporate an NPU, and that's a relatively new technology. The NPU is the neural processing unit, and that sounds a bit like science fiction, but in reality, it's a processor that's optimized to handle AI related workloads. So think of a highly specialized processor that is ideal. It is optimized for AI operations. It handles those kinds of operations that speeds that even powerful GPUs can't match because they weren't built to handle those kinds of problems. And a good in PU, a well designed in PU, can do this with incredible power efficiency. So an NPU at a very basic level has an architecture that is inspired by the network of neurons that you have in that old gray matter up in your noggin. The component of the processor is great for another subset of computational problems, the ones relating to AI. It doesn't replace the CPU, it doesn't replace the GPU. It enhances the capabilities of the processor as a whole. And I think of that as being the ideal use case of artificial intelligence in general. It's good for an enhancement, it's good for augmentation. Now, we have heard lots of stories about AI potentially replacing people, and in some cases not potentially actually leaders choosing AI to replace staff, and trust me, I know these aren't just stories, and I think that that is a very human problem, and specifically a human problem that originates at leadership levels at some organizations. But I think the real sweet spot for artificial intelligence isn't in replacing humans, and I think a lot of those companies are finding that out too. Instead, I think it's augmenting what people can do so that they can do the things they already do well even better. But they can also lean on AI to help them with tasks that they themselves find challenging. Maybe it's the stuff they don't do so well but still kind of part of their daily tasks. So let me give another example. I'm a writer and i'm a podcaster, but I am not a graphics designer. In fact, I find design to be almost impenetrable. I recognize great design when I see it, like I can see great design and say, wow, that's incredible, But if I were looking at a blank page, it's like a prison cell to me. I have fallen victim as well to the trap of reducing the work of real artists as just an element that they have something that I lack. Right, Like, there's some spark or gift that those people have and I don't have it. You're either born with it or you're not. That is harmfully reductive. And I've actually had a good friend of mine, a talented artist, take me aside to talk about this and set me straight. He was very direct but polite about it, and he described to me his experiences learning art and developing his craft and practicing his skills, and he explained that reducing art to some sort of almost mystical gift is an insult considering the countless hours he and other artists have poured into their work in order to get to where they are. That really struck me and made me look at what he did in a different way. But at the end of the day, I don't have those skills. Now. Potentially I could develop such skills if I gave the skills enough time and effort and practice to develop them. But let's be realistic. There are a limited number of hours in the day, and I have responsibilities that I have to meet. The likelihood that I can make the time to practice a new skill and reach a level of skill that would be considered professional, that's pretty love. Oh, I need help, but I don't have an assistant. I don't have a graphics department that specifically reports to me. I have one that I can share with everybody else, which means they don't always have availability for me. So what if I need to put together a presentation. Well, I could use a standard format in a presentation software package. That's kind of a dead giveaway, right if anyone has ever sat through a presentation and they said, oh, I recognize that layout immediately, like I know exactly which default layout you used. Plus, while I'm a decent writer, boiling things down into slides is not my strong suit. This is an area where an AI powered assist would be incredibly valuable to me. I would still be doing the work. Keep it that in mind. I'm not laying the work onto the AI. I've created all this work. Putting together the content of my presentation was the main part of the job. But the AI assistant can help me lay out a presentation and design it so that it looks great, flows well, and most importantly, that my key points are summarized in a way that is effective on the screen. No one wants to sit down to a presentation only to see a slide that looks like it's a dissertation. I'm sure you have all done that where you've gone in and one slide is just a wall of text that stinks. It's not good design, it's missing the point entirely. It's using the presentation for the wrong reason. And I think the key to using AI in an ethical way is all about boosting your own abilities, not fabricating something out of thin air. The art still has to come from the artist, The content still needs to come from the creator. The words need to come from the writer. The AI's job is to add some polish and to help organize thoughts and help the human make stuff that has the most powerful impact upon their intended audience. Now, on a personal side, I am starting to dip my toe into stuff like AI powered photo tools. So I like taking pictures of my aforementioned dog. His name is Timbolt, and he's a joy. But it could be something of a challenge to get a really good photo of Timbolt while I'm walking him, because he's always on a leash, which means I always have one hand holding the other end of that leash, and meanwhile I'm fumbling with my smartphone in an effort to take a photo of them. I can't tell you how many times I've taken a shot that I thought at the time it was gonna look really good, but then the framing is off, or I caught my dog just as he was looking the other way. You know, just after he was looking at me, or the ding dang dern leash is ruining everything and it's in the way of photos or video that I'm trying to take. Now, some of that can be fixed with AI enhanced photo taking tools. For example, imagine that you open up your camera app and you go to take a photo of your pet, and you call it to your pet and you're trying to get its attention, and it looks around and briefly as it's looking around at glances at you before it bounds off to another pet adventure or whatever. One cool feature I want to play with in the future is one I saw at a Snapdragon presentation recently for the Snapdragon eight Elite processor, and it's a tool that will snap a picture when your pet is actually looking at you, so you get that great eye contact. It does like a burst photo mode where it'll take a bunch of pictures, it will select the best one, and it'll even do a little AI enhancement for fur management, which again I love. Or imagine using it to capture the perfect moment as your dog is catching a frisbee or your cat is leaping in the air to play with a toy. You don't have to count on your own reflexes to snap the photo. I really like that, and I look forward to getting a phone that can actually do this in the future. For now, I guess I'll continue fumbling, but I know something is better right around the corner now. With photo editing, I like having options to do things like remove objects from the frame of photos and video like that darn leash. It's not altering the photo in a fundamental way. It's just removing something that I considered to be a distraction. Now that's something that I potentially could do myself with photo editing tools if I developed the skill set to do it. But it's not something I could do right now. I mean I could try, but it would look terrible. You'd say something like, well, yeah, you got rid of the leash, but what the heck is this band of blurry pixels doing throughout your photo because I would have done a bad job. With tools like a video object eraser, I could do this and have it automatically remove the leash even with videos, all with the processing that's happening native to the device I'm using now. To be clear, these capabilities, again, they've been around for a bit, but they have almost always relied upon cloud processing, and that slows everything down, and that means fewer people are going to use it and be able to take advantage of it, moving that compute power to the actual device. By having these AI enabled processors, it not only speeds things up, but again it means you're not sending your data up to some server farms somewhere in the process. Tools like co Creator end up giving me options that I would otherwise be too intimidated to try on my own because I'd be worried I'd just ruin the photo. One application I haven't had a chance to play with yet, but I'm really interested in is AI enhanced Digital Audio workstation programs or apps if you prefer. I'm old, so for me, everything's programs, but I recognize that the terminology these days really tends to be apps. So during the lockdown era of the pandemic, which really wasn't that long ago but feels like a lifetime, I, like a lot of other people, picked up a new hobby, and for me it was learning guitar. Also side note, it's true what they say buying your first guitar ends up being a gateway. Because now I own three electric guitars, one acoustic guitar, one electric bass, and two cigar box guitars. I do have a problem, and I'm not even gonna talk to you about the ukuleles anyway. While my guitar collection has been growing, one thing I haven't really explored are things like effects pedals. I have one effects pedal and I haven't really played with it that much, but I love hearing the output of different effects pedals when I watch videos online. But like photo editing, I don't really have any experience with using these kind of pedals, and I find it intimidating to even dive into that world. I'm worried that I would just buy something that wouldn't really work for what I was trying to achieve. Well, Snapdragon and Microsoft have been working to create low latency AZEO ASIO that actually stands for audio stream input output drivers for musicians. All Right, So this is gonna get really nerdy from both a technical and a musical side. So pardon me as I geek out about this because it's the convergence of two worlds that I love very much. So there are USB audio interface devices that are already out there on the market, And what these devices do is they accept inputs from stuff like musical instruments or microphones. So you plug your instrument or your microphone into this audio device. Then you connect the audio device to a computer using a USB port in this particular case, and that lets you capture or manipulate the audio coming from your device directly into your computer. Now, essentially it's a way to set up a recording studio that's pretty darn portable, whether you're doing music or podcasting or whatever. Now any olden days, which honestly that wasn't that long ago, to get the most out of an ASIO interface, you had to specialize, so they were largely device specific interfaces, and this was to optimize for the purposes of capturing audio. So you would have to have multiple ASIO interfaces if you wanted to work with different types of instruments and microphones and such. A general purpose USB audio interface just wasn't realistic for a long time because you would see a decline in performance or you would have latency issues, both of which are not good news. Like, if you have latency problems, I can't express to you how hard it is to cope for that. Because if you're playing something and you're hearing what you're playing after you're actually strumming the string and you're moving on to the next chord. So what Snapdragon and Microsoft, along with Yamaha have done is create a driver that leverages the Snapdragon processing power to provide high quality and low latency capture support. With the appropriate DAW program. DAW stands for Digital Audio Workspace, you could play guitar directly into your PC for capture, or use tools to create all sorts of effects that you might otherwise only manage. If you had an entire panel of pedals at your disposal. You could even create the effects of different types of amps. So maybe there's a specific kind of amp that gives an output that you really want, Well, there are digital Audio workstation programs out there that can simulate those amps as well as various pedals. Obviously, the features that you have access to are going to depend entirely upon which DAW program you're actually using. But the point I'm trying to make is that this technology enables that kind of feature, that processing power where it does cut down on latency while ensuring high fidelity audio quality. That's what makes it possible. In fact, really that's the key to my whole point of view about the AI enabled processors. They provide opportunities for developers to tap into incredible processing power in order to achieve unprecedented results. And it's hard to talk about what these apps will be able to do because anything I say is likely to not even come close to what people already have in mind. Another program I learned about that haven't used yet but I am eager to is one that reminds me of the video object removal tools I mentioned earlier, except you could do it for audio. So remember how I was talking about how an AI enhanced video editing tool could potentially remove unwanted elements from a video. Let's say you had a shot of acute video of your dog barking at Halloween decorations. But let's say the video also has these annoying homeowners in the background that are just scowling at your dog. Not that I'm speaking from actual personal experience that I had not very long ago. Well, with the AI enhanced video editing capabilities I had talked about, you could just remove those sourpusses and focus on how adorable your dog was. But now imagined something similar except for audio tracks. So let's say you've got a song file, but maybe the baseline just isn't doing it for you. So you use a tool it's called DJ neural Mix, and you identify and remove the baseline and it's just gone. Like everything else is untouched, but the baseline is gone. Now. Typically to do this you would need access to like master recordings in order to be able to remove a specific track, right, Like the bass would be recorded to one track and you would just bring that track down. But usually you don't have access to the master recordings. Usually you get a mixed file, right, it's already been mixed together, and it's not like you can easily unmix it. Typically not without the power of AI anyway. But with AI, the DJ Neural Mixed tool can isolate, say the baseline and separate it from the rest, and you could do that with anything. It wouldn't just be the baseline. You could do it with the vocals or the drums, whatever it might be, which means you could also use this tool to do what DJs do, namely remix music and create new works. It's at the very heart of the transformative nature that is DJing. That's a powerful capability, and again that's one that would be really hard to do without the AI component, or you know, access to those master recordings of somehow you have the magic keys, so it gives DJs a lot of freedom to experiment with different mixes. So maybe you think the drum track from one song would actually sound amazing against the guitars and vocals of a totally different song. Well, you could use a tool like this one to isolate all those components and then remix them together and maybe you would end up with a really awesome groove, or maybe it would be a big mess and you need to go back to the drawing board. With me, it's more likely to be the second one. But you know, you get the idea. There's so much more I could cover here. The Yoga seven X laptop experience I had was impressive, But the crazy thing is I see it as just the starting point. I think the real aha moment for a lot of people out there will hit when they get a chance to see how AI enabled devices will enhance what they are already doing, whether that's work or planning out a vacation or editing and organizing photos and videos. Or accessing a new generation of apps that function unlike anything we've experienced before. The creativity is still going to originate with the person who's behind the keyboard. That's where the heart of all of this comes from, is the person. I still firmly believe that AI is never going to be a replacement for human ingenuity. The genius resides in you, the user. But I do think that AI can help each person unlock options that otherwise would just remain out of reach, and to me, that's the most exciting thing. So yeah, I guess I'm saying my experience with the Snapdragon ex Elite processor and the Yoga seven X laptop really impressed me, and I can't wait to see what's next. That's it for this episode of tech Stuff. I hope all of you are well, and I'll talk to you again really soon. Stuff is an iHeartRadio production. For more podcasts from iHeartRadio, visit the iHeartRadio app, Apple Podcasts, or wherever you listen to your favorite shows.

Welcome to tech Stuff, a production from iHeartRadio. Be there and welcome to tech Stuff. I'm your host, Jonathan Strickland. I'm an executive producer with iHeart Podcasts. And how the tech are you now, y'all? I think I have made my thoughts pretty clear when it comes to artificial intelligence. For one thing, AI is a very broad discipline. It's huge. It's way more than just generative AI, which is a topic I feel very strongly about, and it's also the one that dominates the news cycle. But it's just one aspect of artificial intelligence. And I feel AI in general has incredible potential to augment our computing tasks if we implement it properly. Well. Recently I got the chance to work with an AI laptop and really get to grips with what that potential can be, and I'm convinced we're on another precipice, one that will transform how we interact with computing devices. Now. First, the AI powered device I used was a Lenovo Yoga Slim seven X laptop with a Snapdragon x Elite processor. It's a Copilot plus PC, which means it features Microsoft's AI Assistant. It's also got an OLED screen, and it's no joke. That's the prettiest laptop screen I have ever used. The contrast on that thing is crazy, it's amazing. It's so beautiful. Now, Snapdragon was generous in sending me this laptop so that I could actually get some hands on time with it. And I'll be talking a lot about the work Snapdragon has done to make the processor really special, but I'm saving that for a bit later. Now, I do have to say that this laptop would immediately top my holiday wish. And I'm not just saying that I could be if I had no scruples, but that's not who I am, y'all. It's legit how I feel this laptops. It's really light, it's powerful, The screen, as I mentioned, is absolutely gorgeous, but the battery life is also really impressive, particularly when you consider the power lifting this thing has to do. Even when it's running AI Enhanced applications, which y'all know AI, it requires a lot of processing power, but this laptop continued to run smoothly and I didn't have to go dashing from outlet to outlet just to keep it going. But I think the thing that really pulls me to this laptop is the fact that I can see AI enabled processors as being the tech platform of the future. So it's my belief that just as smartphones revolutionized how we interact with computing resources, you know, like apps as well as the Internet, AI is going to do the same thing. Now. Before the era of the consumer smartphone, there were very few people who were predicting a move to mobile. Now, there were a few smarty pants is out there who were ahead of the curve, but most of us didn't see it coming. Once smartphones proved their merit in the consumer marketplace, we saw a pretty rapid transition to a mobile friendly landscape. You know, Web administrators were scrambling to make sure that their websites were optimized for mobile devices lest they potentially drive away visitors who were increasingly using their phones to access the Internet rather than say, laptop and desktop computers. Meanwhile, developers began designing apps that would leverage smartphone capabilities, you know, stuff like accelerometers and touchscreens and GPS sensors, that kind of thing. Well, I believe AI is going to do much the same. We're going to see a host of new programs and apps built with AI enhanced features and devices that are capable of providing onboard AI processing are going to be way ahead of the game, while also providing ways to handle AI processing in a more secure and private approach. See, there are different ways that you can handle AI processing. One way is you offload everything to a server farm somewhere, and we hear about these a lot in the news. You know, they're massive buildings, just filled with racks of servers processing enormous amounts of data, powering AI implementations all around the world, and no doubt that will continue, that will continue to be a thing. But a complementary approach involves on device and edge computing cases in which the gadgets that we actually have our hands on can do some or all of that processing on their own without connecting to some distant server. Now it all depends upon the application, of course, but with those types of implementations, you keep the AI computations on your device, and that means you're not sharing data with some server farm that smiles away. Everything stays low, and that is a huge thing when it comes to privacy and security. Let's say that you work for a really big media company, for example, I could be using myself in this example, and you want to make sure that the work you do stays local because you're working with some sensitive information, some of it might be proprietary. You don't want to be sending that off and have it become some kernel of information that gets enveloped in a larger database somewhere. That's risky stuff. So making sure you are able to do this kind of thing locally is important for a lot of people. All right, let's talk about the overview for this whole approach. We'll get into the hows and whys a little bit later, but first I want to talk about the ways I used that Lenovo Yoga seven X laptop. So I wanted to see how an AI enhanced device could potentially help me do my work. I mean, we talk a lot about artificial intelligence augmenting our ability. I wanted to actually put that into practice. So I use the laptop while I was researching a recent episode, one that actually has already published. So I used this laptop, the Yoga laptop, specifically for that episode, and I really wanted to put it through its paces and see if it had a meaningful impact on the way I do work. Now in this episode, I referenced an extremely long research paper that was written for the journal Science and Global Security, and it was an article by Jurgen Altmann. It's actually a fantastic paper. It was incredibly readable, which is not always the case for technical papers. If you've ever tried to read one, sometimes they come across as the most stilted term paper a teacher has ever had degrade, but not this one. It's also an accessible paper. You can find it online for free, so that's great as well. But it's very long, like it's seventy pages long. Now more than ten of those pages are just notes and references, but you still have, you know, fifty nine pages of pure content there. Now, I read the full article for my research, but I need to have access to the salient points without having to thumb through all seventy pages and taking notes as I read the article. That way, I wouldn't have to thumb through a seventy page article while writing the episode. But that's not easy to do. Once you get past like twenty pages, it gets pretty cumbersome. So I use the AI assistant on the laptop to create a summarized, bulleted list of the most important notes in the paper. For quick reference. Now I'm the cautious type, and while I was using this and I wanted to really check and make sure that it worked. I also wanted to verify that the notes that were produced were accurate to the original paper, that they weren't a misinterpretation or a summary that just wasn't accurate. And obviously that added more time for me. If I had not had to do that, I would have been through pretty quickly, but I needed to check. It's not just enough to have it create this list, and it really did show that the summary was accurate to the document I was using, and that it really was the most important points in the paper that were included the summary, and it was really easy to do. It was easy to navigate to the actual source for the bullet points so that I could verify that, in fact, the information was correct, and it really made organizing my thoughts much faster than it would have been if I hadn't been able to access this tool, because while I was taking more time to verify that the bullets were accurate representations of the information in the article, it did allow me to organize the whole approach for the episode. So typically when I organized an episode, I do that by feel, and some of you might be saying, yeah, we know it's obvious, But I've been podcasts for sixteen years. I have a sense of the flow I want for an episode. Now that doesn't always mean it's the best approach, but it is the one that just feels natural to me. However, in this case, it was really nice to consult a different perspective, even an artificial perspective, to figure out how best to structure the episode. So if there was an episode in the recent past that you listened to and you thought, wow, that's more coherent than what he normally produces, well now you know why. But keep it to yourself because words can hurt y'all. One thing I didn't do but I could have done, was use real time translation tools to access information that was presented in other languages. Once upon a time, I took courses in French and in German, but I never got to the point where I was conversational, let alone fluent in those languages. And of course, over the years my skills have atrophied. So I speak two languages, English and Bad English. But I am aware that there is a wealth of information and knowledge that's captured in other languages. While there's some pretty darn good translation apps for stuff like text, the cool thing about AI powered devices is that they have the potential and the processing capability to provide real time translation for other kinds of content like audio. So one thing I could have done was watch a video that had been recorded in another language, and through using onboard AI processing capabilities, been able to read English language captions that were translating what was being said in real time. Now that opens up entire worlds of expertise that otherwise would be very difficult for me to access. And I've always said that diversity is really important. It means you get multiple perspectives providing information, and you can view the world from different perspectives, including ones that you might not have ever even considered otherwise. Now, you might ultimately not agree with this other point of view, but being able to access it is important. Otherwise you just remain ignorant of it. So from a research perspective, real time translation is an enormous benefit, and I imagine we'll see this technology continue to evolve as well. Tools can be pretty good at doing things like translating word for word, but in future implementations. I imagine AI translation will also have to handle stuff like syntax and idioms really well, so that we don't just understand the actual words being spoken, but what the speaker means when they say those things. If someone uses like an idiom like a regional saying, or they're using really complex phrasing that doesn't easily translate to English, I can imagine future AI translation tools handling that and providing a relatable translation to avoid ambiguity, unless, of course, ambiguity was the intent in the first place. Sometimes it is another thing that I could have done at the end of the whole episode because I have used tools like this before, is use AI to generate show notes. So, y'all, Podcasting is a lot of work, particularly if you have a small team. In my case, the team is me and super producer Tari, who also works on other shows. There are a lot of steps in making a podcast. You know, you have pre prep. You've got prep, you've got research, you've got writing and recording and editing and publishing. One post production step that a lot of shows will skip is the production of show notes. So why do so many shows just skip show notes? Well, I can't speak for everyone, But in my case it comes down to being a mental block. When I finish an episode, after I've done speaking my amazing words into a microphone and then shipping off the file to my producer extraordinaire Tari, I'm ready to move on. My brain has effectively said, welp. That closes that chapter, dusts off its hands and whistles as a walks into the sunset. So it can be really hard to stop and reflect on what I just created and then distill that into useful notes for listeners. But AI tools can do that automatically. Of course, after creating the notes, then I would review them to make sure that again they accurately reflect the episode. But that's one step in the podcasting process that I would be happy to hand over to an AI enabled tool, as it is a step that I otherwise find really tedious and it actually discourages me from doing my job. You know, I will find any excuse. I will invent excuses to put off doing that kind of thing. Now, while all my research and writing and recording was going on, I also was using the assistant to keep me up to speed on my daily schedule. I'm somewhat notorious for missing things like important emails and meetings and that sort of thing. I have kind of made it an art formed to make it difficult to reach me because I find it creates an environment that allows me to focus right. I want to really focus on what I'm doing, and that means I need to filter out distractions because otherwise I will stop whatever it is I'm working on, and that just ruins my whole flow. Getting back into that is hard to do. I found using the AI assistant to help block out my time so that I had specific blocks of time where I was doing specific activities made me overall more efficient and effective. I actually one of the In fact, the very first thing I asked my AI assistant to do was to help me create a working schedule and it did, and it even built in things like breaks and stuff, and I followed it. I was like, this is a real experiment. I am going to follow the schedule that's been created for me, and I found that it was incredibly helpful. It really added structure to my day, something that I haven't had a lot of because I work remotely and mostly on my own, so structure is something that I have to create and I'm not great at doing that. So using this tool to help me to augment my abilities and to take on a workload that I otherwise would find difficult to do, that was incredibly helpful and it was a really nice change. Now I can envision other uses of AI as well, though I didn't use them for that particular episode. So for example creating audiograms, and I can already use AI to do this. I have used AI tools to do this, but they were cloud based. And what I'm talking about here is using AI to identify interesting passages in an episode, like a section that's really compelling. And you could do this in different ways, Like you could use AI to analyze the written work that you create, like in my case, I write out episodes, right, so I could actually use AI to analyze what I've written and to identify, oh, this is a particularly compelling section. Or you can use it to analyze the recorded audio. Because I also go off book a lot. I don't just have a script that I read. I extemporize like crazy. If you read what I wrote and compared it to what I say, you would notice that there are a lot of departures. So using AI, I could analyze the recorded program and create audiograms, which are those excerpts you sometimes come across on various social platforms. These are ones that play not just an audio clip from a show. Typically they'll also include stuff like real time captions that will help emphasize the point being expressed. I've had some experience using AI to generate these, and that includes matching text to spoken words automatically, so that you don't have to do it on your own, like you don't have to create an animation or anything. It does it for you. Now, the tools I've used, they're not perfect, but really good. Ones typically include a pretty easy way to edit the text so that if you're like me, let's say you have a little bit of a dialect that occasionally creeps through your spoken words, then you can review and fix the little goofs that the transcription might make when you maybe get a little too southern or whatever. For the individual creator, these kinds of tools are phenomenally useful. They simplify the process of promoting your work, and they help creators make bite sized pieces of their output that are ideal for social platforms to promote and to send people back to a full episode. For example, now I have the luxury of working at a major media company, and so in certain situations, I can actually lean on other people to help me create these kinds of social assets. But even in my case, my resources have their limits. I mean, those departments are supporting tons of other shows, they may not have the capacity to work with me, and most other creators don't even have that kind of help at their disposal to start with. Being able to lean on AI powered tools can give a creator more opportunities to find their audience, to stand out in a crowded field. Okay, back to my personal experiences. One of the big bonuses of using this Yoga Slim seven X laptop is as the name suggests, the laptop is extremely portable. It is lightweight, it has an incredibly thin form factor, and if I felt myself getting restless while I was working in my office, literally, I could just know, save my progress, shut the laptop and carry it upstairs to the living room and then work on the couch. And my dog found that to be a fantastic change of pace. And while he's not quite as good at keeping me on task as the AI assistant is, I definitely appreciated the change of scenery. You know, We're gonna take a quick break to thank our sponsor, but we'll be right back. So let's talk about this processor for a moment, because that's really ultimately what makes this experience possible in the first place. So, first off, Snapdragon obviously has a very long history of developing processors for mobile platforms, and I believe that gives Snapdragon some distinct advantages because the engineers and designers are used to working within tight limitations. I'm talking about tight limitations when it comes to the actual form factor the space. You have to work in tight limitations on how much power you're going to have access to, how much heat you can generate because it is a mobile device and you're not going to have access to like massive fans or water cooling systems. You know, you still need to get all the processing power as well. So all of this sounds like it could be a bad thing, but in my experience, when you are set with tight limitations, it can really inspire innovation and creativity because you still have a goal that you're working toward, right, and then you just have to think, well, how do I achieve this goal? And if you've got those limitations, it means that certain avenues are just cut off, and you have to really focus on what is possible and then push the boundary as hard as you can. And how you create a processor that provides the compute power needed while maintaining battery life ends up becoming kind of this guiding principle. Mobile devices in particular need to conserve battery power, right. I mean, you don't want to have a smartphone that has three hours of useful life in it and then you need to recharge it. But you also need to make sure that it can actually handle the computational jobs being thrown at it or else everything's going to feel sluggish and that's not a good user experience either. So Snapdragon's approach has been to incorporate different kinds of processors all on a single chip. So you've got your CPU, so that's your central processing unit. I think we're all familiar with those. The microprocessor kind of acts like the brains of the operation. CPUs traditionally are very good at handling, you know, like sequential problems, ones that are consecutive problems where the solution to one calculation feeds directly into the next. But then you've got your GPU, your graphics processing unit. Again, I feel like most of us have a handle on these these days. I remember, I'm old enough to remember when GPUs didn't exist. They weren't a thing. You would occasionally get a graphics chip, but it wasn't called a GPU. That didn't happen until you get up into the nineties. Really, and initially these were built to, as the name suggests, handle graphics processing. But GPUs have really come into their own in recent years and have proven to be extremely powerful when handling parallel processing jobs. So those are computational problems that can split into different tasks that a processor can potentially handle concurrently rather than consecutive, so they solve parts of problems all at the same time. Now, that doesn't work for every type of computational problem, but for that particular subset, GPUs are pretty darn good. But the snap Dragon x Elite processors also incorporate an NPU, and that's a relatively new technology. The NPU is the neural processing unit, and that sounds a bit like science fiction, but in reality, it's a processor that's optimized to handle AI related workloads. So think of a highly specialized processor that is ideal. It is optimized for AI operations. It handles those kinds of operations that speeds that even powerful GPUs can't match because they weren't built to handle those kinds of problems. And a good in PU, a well designed in PU, can do this with incredible power efficiency. So an NPU at a very basic level has an architecture that is inspired by the network of neurons that you have in that old gray matter up in your noggin. The component of the processor is great for another subset of computational problems, the ones relating to AI. It doesn't replace the CPU, it doesn't replace the GPU. It enhances the capabilities of the processor as a whole. And I think of that as being the ideal use case of artificial intelligence in general. It's good for an enhancement, it's good for augmentation. Now, we have heard lots of stories about AI potentially replacing people, and in some cases not potentially actually leaders choosing AI to replace staff, and trust me, I know these aren't just stories, and I think that that is a very human problem, and specifically a human problem that originates at leadership levels at some organizations. But I think the real sweet spot for artificial intelligence isn't in replacing humans, and I think a lot of those companies are finding that out too. Instead, I think it's augmenting what people can do so that they can do the things they already do well even better. But they can also lean on AI to help them with tasks that they themselves find challenging. Maybe it's the stuff they don't do so well but still kind of part of their daily tasks. So let me give another example. I'm a writer and i'm a podcaster, but I am not a graphics designer. In fact, I find design to be almost impenetrable. I recognize great design when I see it, like I can see great design and say, wow, that's incredible, But if I were looking at a blank page, it's like a prison cell to me. I have fallen victim as well to the trap of reducing the work of real artists as just an element that they have something that I lack. Right, Like, there's some spark or gift that those people have and I don't have it. You're either born with it or you're not. That is harmfully reductive. And I've actually had a good friend of mine, a talented artist, take me aside to talk about this and set me straight. He was very direct but polite about it, and he described to me his experiences learning art and developing his craft and practicing his skills, and he explained that reducing art to some sort of almost mystical gift is an insult considering the countless hours he and other artists have poured into their work in order to get to where they are. That really struck me and made me look at what he did in a different way. But at the end of the day, I don't have those skills. Now. Potentially I could develop such skills if I gave the skills enough time and effort and practice to develop them. But let's be realistic. There are a limited number of hours in the day, and I have responsibilities that I have to meet. The likelihood that I can make the time to practice a new skill and reach a level of skill that would be considered professional, that's pretty love. Oh, I need help, but I don't have an assistant. I don't have a graphics department that specifically reports to me. I have one that I can share with everybody else, which means they don't always have availability for me. So what if I need to put together a presentation. Well, I could use a standard format in a presentation software package. That's kind of a dead giveaway, right if anyone has ever sat through a presentation and they said, oh, I recognize that layout immediately, like I know exactly which default layout you used. Plus, while I'm a decent writer, boiling things down into slides is not my strong suit. This is an area where an AI powered assist would be incredibly valuable to me. I would still be doing the work. Keep it that in mind. I'm not laying the work onto the AI. I've created all this work. Putting together the content of my presentation was the main part of the job. But the AI assistant can help me lay out a presentation and design it so that it looks great, flows well, and most importantly, that my key points are summarized in a way that is effective on the screen. No one wants to sit down to a presentation only to see a slide that looks like it's a dissertation. I'm sure you have all done that where you've gone in and one slide is just a wall of text that stinks. It's not good design, it's missing the point entirely. It's using the presentation for the wrong reason. And I think the key to using AI in an ethical way is all about boosting your own abilities, not fabricating something out of thin air. The art still has to come from the artist, The content still needs to come from the creator. The words need to come from the writer. The AI's job is to add some polish and to help organize thoughts and help the human make stuff that has the most powerful impact upon their intended audience. Now, on a personal side, I am starting to dip my toe into stuff like AI powered photo tools. So I like taking pictures of my aforementioned dog. His name is Timbolt, and he's a joy. But it could be something of a challenge to get a really good photo of Timbolt while I'm walking him, because he's always on a leash, which means I always have one hand holding the other end of that leash, and meanwhile I'm fumbling with my smartphone in an effort to take a photo of them. I can't tell you how many times I've taken a shot that I thought at the time it was gonna look really good, but then the framing is off, or I caught my dog just as he was looking the other way. You know, just after he was looking at me, or the ding dang dern leash is ruining everything and it's in the way of photos or video that I'm trying to take. Now, some of that can be fixed with AI enhanced photo taking tools. For example, imagine that you open up your camera app and you go to take a photo of your pet, and you call it to your pet and you're trying to get its attention, and it looks around and briefly as it's looking around at glances at you before it bounds off to another pet adventure or whatever. One cool feature I want to play with in the future is one I saw at a Snapdragon presentation recently for the Snapdragon eight Elite processor, and it's a tool that will snap a picture when your pet is actually looking at you, so you get that great eye contact. It does like a burst photo mode where it'll take a bunch of pictures, it will select the best one, and it'll even do a little AI enhancement for fur management, which again I love. Or imagine using it to capture the perfect moment as your dog is catching a frisbee or your cat is leaping in the air to play with a toy. You don't have to count on your own reflexes to snap the photo. I really like that, and I look forward to getting a phone that can actually do this in the future. For now, I guess I'll continue fumbling, but I know something is better right around the corner now. With photo editing, I like having options to do things like remove objects from the frame of photos and video like that darn leash. It's not altering the photo in a fundamental way. It's just removing something that I considered to be a distraction. Now that's something that I potentially could do myself with photo editing tools if I developed the skill set to do it. But it's not something I could do right now. I mean I could try, but it would look terrible. You'd say something like, well, yeah, you got rid of the leash, but what the heck is this band of blurry pixels doing throughout your photo because I would have done a bad job. With tools like a video object eraser, I could do this and have it automatically remove the leash even with videos, all with the processing that's happening native to the device I'm using now. To be clear, these capabilities, again, they've been around for a bit, but they have almost always relied upon cloud processing, and that slows everything down, and that means fewer people are going to use it and be able to take advantage of it, moving that compute power to the actual device. By having these AI enabled processors, it not only speeds things up, but again it means you're not sending your data up to some server farms somewhere in the process. Tools like co Creator end up giving me options that I would otherwise be too intimidated to try on my own because I'd be worried I'd just ruin the photo. One application I haven't had a chance to play with yet, but I'm really interested in is AI enhanced Digital Audio workstation programs or apps if you prefer. I'm old, so for me, everything's programs, but I recognize that the terminology these days really tends to be apps. So during the lockdown era of the pandemic, which really wasn't that long ago but feels like a lifetime, I, like a lot of other people, picked up a new hobby, and for me it was learning guitar. Also side note, it's true what they say buying your first guitar ends up being a gateway. Because now I own three electric guitars, one acoustic guitar, one electric bass, and two cigar box guitars. I do have a problem, and I'm not even gonna talk to you about the ukuleles anyway. While my guitar collection has been growing, one thing I haven't really explored are things like effects pedals. I have one effects pedal and I haven't really played with it that much, but I love hearing the output of different effects pedals when I watch videos online. But like photo editing, I don't really have any experience with using these kind of pedals, and I find it intimidating to even dive into that world. I'm worried that I would just buy something that wouldn't really work for what I was trying to achieve. Well, Snapdragon and Microsoft have been working to create low latency AZEO ASIO that actually stands for audio stream input output drivers for musicians. All Right, So this is gonna get really nerdy from both a technical and a musical side. So pardon me as I geek out about this because it's the convergence of two worlds that I love very much. So there are USB audio interface devices that are already out there on the market, And what these devices do is they accept inputs from stuff like musical instruments or microphones. So you plug your instrument or your microphone into this audio device. Then you connect the audio device to a computer using a USB port in this particular case, and that lets you capture or manipulate the audio coming from your device directly into your computer. Now, essentially it's a way to set up a recording studio that's pretty darn portable, whether you're doing music or podcasting or whatever. Now any olden days, which honestly that wasn't that long ago, to get the most out of an ASIO interface, you had to specialize, so they were largely device specific interfaces, and this was to optimize for the purposes of capturing audio. So you would have to have multiple ASIO interfaces if you wanted to work with different types of instruments and microphones and such. A general purpose USB audio interface just wasn't realistic for a long time because you would see a decline in performance or you would have latency issues, both of which are not good news. Like, if you have latency problems, I can't express to you how hard it is to cope for that. Because if you're playing something and you're hearing what you're playing after you're actually strumming the string and you're moving on to the next chord. So what Snapdragon and Microsoft, along with Yamaha have done is create a driver that leverages the Snapdragon processing power to provide high quality and low latency capture support. With the appropriate DAW program. DAW stands for Digital Audio Workspace, you could play guitar directly into your PC for capture, or use tools to create all sorts of effects that you might otherwise only manage. If you had an entire panel of pedals at your disposal. You could even create the effects of different types of amps. So maybe there's a specific kind of amp that gives an output that you really want, Well, there are digital Audio workstation programs out there that can simulate those amps as well as various pedals. Obviously, the features that you have access to are going to depend entirely upon which DAW program you're actually using. But the point I'm trying to make is that this technology enables that kind of feature, that processing power where it does cut down on latency while ensuring high fidelity audio quality. That's what makes it possible. In fact, really that's the key to my whole point of view about the AI enabled processors. They provide opportunities for developers to tap into incredible processing power in order to achieve unprecedented results. And it's hard to talk about what these apps will be able to do because anything I say is likely to not even come close to what people already have in mind. Another program I learned about that haven't used yet but I am eager to is one that reminds me of the video object removal tools I mentioned earlier, except you could do it for audio. So remember how I was talking about how an AI enhanced video editing tool could potentially remove unwanted elements from a video. Let's say you had a shot of acute video of your dog barking at Halloween decorations. But let's say the video also has these annoying homeowners in the background that are just scowling at your dog. Not that I'm speaking from actual personal experience that I had not very long ago. Well, with the AI enhanced video editing capabilities I had talked about, you could just remove those sourpusses and focus on how adorable your dog was. But now imagined something similar except for audio tracks. So let's say you've got a song file, but maybe the baseline just isn't doing it for you. So you use a tool it's called DJ neural Mix, and you identify and remove the baseline and it's just gone. Like everything else is untouched, but the baseline is gone. Now. Typically to do this you would need access to like master recordings in order to be able to remove a specific track, right, Like the bass would be recorded to one track and you would just bring that track down. But usually you don't have access to the master recordings. Usually you get a mixed file, right, it's already been mixed together, and it's not like you can easily unmix it. Typically not without the power of AI anyway. But with AI, the DJ Neural Mixed tool can isolate, say the baseline and separate it from the rest, and you could do that with anything. It wouldn't just be the baseline. You could do it with the vocals or the drums, whatever it might be, which means you could also use this tool to do what DJs do, namely remix music and create new works. It's at the very heart of the transformative nature that is DJing. That's a powerful capability, and again that's one that would be really hard to do without the AI component, or you know, access to those master recordings of somehow you have the magic keys, so it gives DJs a lot of freedom to experiment with different mixes. So maybe you think the drum track from one song would actually sound amazing against the guitars and vocals of a totally different song. Well, you could use a tool like this one to isolate all those components and then remix them together and maybe you would end up with a really awesome groove, or maybe it would be a big mess and you need to go back to the drawing board. With me, it's more likely to be the second one. But you know, you get the idea. There's so much more I could cover here. The Yoga seven X laptop experience I had was impressive, But the crazy thing is I see it as just the starting point. I think the real aha moment for a lot of people out there will hit when they get a chance to see how AI enabled devices will enhance what they are already doing, whether that's work or planning out a vacation or editing and organizing photos and videos. Or accessing a new generation of apps that function unlike anything we've experienced before. The creativity is still going to originate with the person who's behind the keyboard. That's where the heart of all of this comes from, is the person. I still firmly believe that AI is never going to be a replacement for human ingenuity. The genius resides in you, the user. But I do think that AI can help each person unlock options that otherwise would just remain out of reach, and to me, that's the most exciting thing. So yeah, I guess I'm saying my experience with the Snapdragon ex Elite processor and the Yoga seven X laptop really impressed me, and I can't wait to see what's next. That's it for this episode of tech Stuff. I hope all of you are well, and I'll talk to you again really soon. Stuff is an iHeartRadio production. For more podcasts from iHeartRadio, visit the iHeartRadio app, Apple Podcasts, or wherever you listen to your favorite shows.