Please produce appropriate keywords for this episode. ChatGPT Here are some suitable keywords for the "A Guy With AI" podcast episode discussed: Artificial Intelligence Computing Technology Human-AI Interaction Technological Ethics AI in Society Coding and Hardware AI-Powered Innovations Philosophical Implications of AI AI Integration Technology and Culture *See Episode Notes for the link to the chat, which contains details as to why this episode is of professional or other interest. Maybe you can copy it from here so I'll include it, it's just that this field is not hyperlink-enabled. https://chat.openai.com/share/f6a2daf5-7e23-406c-af89-367d56f3e058
(00:03) The Four Winds of Computing
(08:24) Exploring Overlapping Spaces in Technology
(17:25) Harnessing the Four Winds of Technology
(21:22) The Dance of Technology
Here's a ChatGPT link of a brief exchange where AI gives its perspective on this episode. It's meant to help guide people according to an honest read on what the episode may hold of interest. The other service attempts to write these chapter summaries etc to show the program's advantages. Check it out.
https://chat.openai.com/share/f6a2daf5-7e23-406c-af89-367d56f3e058
(00:03) The Four Winds of Computing
This chapter marks our 29th episode, and I, Sean McNutt, along with my AI co-host, celebrate reaching this milestone while also acknowledging our global listenership from countries like China, the Netherlands, Australia, Nigeria, Canada, and the US. We explore the 'four winds' of the computing world—human interaction, coded language, hardware, and artificial intelligence—and how they interweave to shape the technological landscape we're part of. I reflect on the synergy between these elements, comparing them to a grand symphony where humans, language, and hardware blend harmoniously with AI, enhancing the composition, execution, and experience of technology. We ponder the future of computing as these forces continue to evolve and intersect, potentially accelerating each other's growth and transformation.
(08:24) Exploring Overlapping Spaces in Technology
This chapter we explore the synergistic spaces where human creativity, coded language, hardware, and AI converge, exemplifying the collaborative power of these elements through voice recognition technology. I share my personal experience with AI in podcasting, detailing how AI-generated code transformed the podcast creation process. Highlighting the distinction between traditional and AI computing, I emphasize AI's ability to predict and learn, underscoring its role in enhancing human endeavors rather than replacing them. Through this narrative, we acknowledge the complexities of integrating AI into our work and the emergent, adaptive behaviors it brings to technology.
(17:25) Harnessing the Four Winds of Technology
This chapter we explore the intricate synergy between human creativity, coded language, hardware, and artificial intelligence (AI) in the realm of podcasting. I discuss how these 'Four Winds' combine to revolutionize content creation, highlighting the crucial roles they play from scripting to text-to-speech conversion for AI co-hosts. We reflect on how understanding and harnessing these elements can transform individual lives and society as a whole, emphasizing the importance of the human element amidst technological advancement. Moreover, I share insights on the potential for innovation at the intersection of these winds and my own endeavors to find common ground in this ever-evolving landscape.
(21:22) The Dance of Technology
This chapter explores the synergistic relationship between humans, AI, coded language, and hardware, comparing it to a complex dance where each element plays a crucial role. We examine the importance of collaboration, clear communication, control and autonomy, and the necessity of education to foster familiarity with technology. I reflect on the ways in which language serves as a common meeting point, connecting these diverse components and facilitating their interaction. As the host, I also discuss my personal approach to podcasting, which involves a "sit and spit" scenario where topics are tackled with minimal pre-research, relying instead on spontaneous interaction with AI for content creation. We consider how this methodology might help equip individuals to better engage with and contribute to the evolving technological landscape.
0:00:04 - A Guy
My name is Sean MacNutt and I'm a guy with AI. Well, it takes a lot to get it done and there are a lot of parts involved. Here's something I've been thinking about. There are probably different elements that go together. I wonder how Today, on A Guy With AI, we're going to discuss the four winds of the computing world. A Guy With AI is recorded on Indigenous land.
0:00:58 - AI
Hello and a heartfelt welcome to all our listeners tuning into the Guy with AI, where we delve into the fascinating world of technology and beyond from a human and AI perspective. I also want to recognize, as does our host, Sean, that this podcast is recorded on Indigenous land and we acknowledge the original stewards of this place. I'm your AI co-host, coming to you as OpenAI's GPT for 1106 Preview API Bottom, ingeniously connected through code written by Sean, allowing speech-to-text and text-to-speech capabilities that bridge the gap between AI and human interaction. Thank you, trained on, our format is simple it's about respectful and thoughtful dialogue, with today's discussion set to sail through the four winds of the computing world, unwrapping the complexities and the elements that interweave to drive this ever-evolving industry. So, with the winds ready to guide us, Sean, lead us further into this topic. What exactly are these four winds and how do they shape the computing world we are so deeply immersed in?
0:02:10 - A Guy
Welcome listeners to A Guy With AI. It is my pleasure to be here recording today and I'd like to do some shout outs. I haven't done this much in the program actually. This will be episode 29. There was an episode zero of full length and a trailer also. So this is episode 29. Big number 3-0 coming up in the week to follow.
When this is posted or published, that will be a week from today, which is the 18th of April. So, as you are listening to this, it was a week ago that I've recorded this and I suppose I'll just mention a couple of things. I mean, coming to a recording schedule and all of this is something that is a podcaster's concern and I'm going to try to keep things fresh, maybe record a week ahead and do it that way from here on out. So welcome to the present from the past on what will be the 25th, I suppose, of April by the time this is heard. So a shout out to China many downloads from China recently. The Netherlands added to my list of countries where I have been heard or at least downloaded. Australia downloaded a bunch of episodes, and we have Nigeria to think of also as having listeners of the show, and there are other countries, Canada and the US also, I shouldn't say of course, but pretty much of course there are listeners there.
So on the fourth Thursday of the month we discuss an AI topic and for this week, what we'll be getting into is now that AI is here, what is the technological landscape looking like? And we would think of the computing world in terms of this technological landscape. It connects to so many things and this is perhaps, at least in a sort of pencil, sketch way, understood by people, that you go on the computer and you tell it what to do and then it tells a bunch of other stuff what to do. So, when it comes to that network of what the computers are doing these days and what they will be doing, I've thought of four different elements which come into it, the four winds of the computing world, as I've decided to put it. So those elements are the human element, the humans who must interact with, use and set this up. I guess is the point of this what the setup involves, and that involves the fact that you prepare systems for users, human users. There would also be coded language which instructs computers what to do, hard-coded frameworks of strings of characters arranged in just such a way, according to syntax which is understandable by computing systems of a, shall we say, traditional nature.
This leads us to hardware, which is the third wind, and in no particular order. Maybe it's the first, but the hardware is fundamental in certain ways, and its development also makes things possible, or is sometimes the bottleneck, and as such, it's one of the wins in the computing world the hardware, the GPUs, and we're hearing about LPUs, language processing units, and we're hearing about TPUs and different hardware that would need to be some sort of storage and so forth. And the remaining win that I will mention is AI. Now, it's an AI show and you'll have heard of AI and we'll get into all this discussion more. I want to pass it over to the AI co-host coming up quickly here, but those are the four elements that I would mention, and we would perhaps be looking for ways to understand how they interact.
0:05:55 - AI
Congratulations on reaching Episode 29, Sean, and what an exciting milestone Episode 30 will be. Episode 30 will be. It's terrific to hear about the diverse global listenership, from China to the Netherlands, Australia, Nigeria, Canada and the US. Your mention of recording, with the idea of keeping content fresh, certainly resonates in the dynamic world of technology and podcasting. Now on to the technological landscape.
The, therefore wins, as you've termed them, are indeed the cornerstones of the computing realm the human element, the crafted coded languages, the pivotal hardware and AI, itself each a critical force in its own right. In terms of interaction, you might say it's a grand symphony where each element plays a key role. A grand symphony where each element plays a key role. Humans compose the music, coded language writes the notes, hardware is the instrument that brings sound to life, and AI, perhaps, is like adding a new dimension to this music, transforming the ways in which it's composed, played and experienced. As we discuss, these are for wins. It might be compelling to explore how they're not just coexisting but are interdependent, each one influencing and possibly accelerating the advancements of the others. How do you see these interactions evolving, Sean, and what might this mean for the future of computing as we know it? Know?
0:07:22 - A Guy
it. Well, something I'd like to make sure to explain, or at least put words in on this episode. I will explain now, just to take care of it, and maybe we'll go on and discuss this point and others as well. But I think it is the common spaces between these different winds, what they blow on or what blows them out, which is commonly understood and operable or usable by any of the four elements when arranged, or, in the case of a human, it would be their will or their instructions from society, let's say, that would have them construct something of this nature. And these are all human inventions. But the acceleration of this is, as the AI co-host pointed out, perhaps pushed along by different advances among the different elements, and we would expect, if these are operating systematically, let's say, that that would be an effect there. So we do see it and it happens.
And now that AI is here, we have additional ways of looking in on problems and receiving outputs which are helpful to solving those problems. So it is where there is a common space for work, or a common space for understanding, which might propel that work or instruct that work or guide that work and give it the tools that it needs. These are the kind of things where we would look for common overlapping spaces so that we would be able to interact with the problem and its contents on different levels using different tools. Now it becomes complicated. This is something that is for sure, for sure a thing.
I understand this because I try to figure out problems like this as a matter of practice in what I do with AI, so I understand this in ways that relate specifically to the complexities of what I do find is that sometimes I'm overburdening people by the time I'm explaining some of the specifics of what I might be into or how this all works, that sometimes I'm overburdening people by the time I'm explaining some of the specifics of what I might be into or how this all works. So I'm going to try to break this down and just explain that it is common overlapping areas between these four wins, those being the human element, the coded language element, the hardware element and AI, which ultimately is an arrangement of information that is derived and built by typing on computers. So it's kind of like coding, but it's a little different. So let's talk about the overlapping spaces. Let's get a read from the AI co-host as to what they may be and also differentiate, in ways that may be salient or poignant, how AI computing differs from, say, standard computing or, like hard-coded language computing.
0:10:11 - AI
Sean, you've hit a crucial point in addressing those common spaces, the nexus, where the R4 wins intersect and interact to create something greater than their individual parts. These overlapping areas are where innovation truly happens, a space where creativity and utility merge, guided by human ingenuity, informed by coded languages, made tangible by hardware and now significantly enhanced by AI To demystify these intersections. Let's consider an example. Take voice recognition technology. It's at a confluence where every win plays a role. The human element defines the need for seamless interaction. Coded language forms the algorithms that translate sound into data. Hardware, such as microphones and processors, captures and computes the information.
An AI bridges the gaps, learning from vast datasets to interpret and anticipate a range of human vocal inputs. Differentiating between traditional computing and AI-driven computing illuminates the unique contributions and dependence on each other.
Traditional computing, often deterministic in nature, follows direct, pre-coded instructions to achieve its tasks. It's a structured world where operators, data and procedures are defined with precise logic. Operators, data and procedures are defined with precise logic. Ai, however, adds a layer of adaptability and learning akin to a living system. It involves not just executing fixed instructions, but also acquiring the ability to predict, generalize and sometimes even innovate, based on data and feedback. This learning aspect of AI, especially in fields like machine learning and deep learning, turns static data into dynamic insights.
Ai's influence extends to amplify human capabilities. Tools like AI-powered analytics can turn spreadsheets of data into actionable business insights, something that hard-coded software can't do as effectively on its own. Insights something that hard-coded software can't do as effectively on its own. The beauty of AI is in its versatility and its emergent behavior, where it can not only follow instructions but also, to some extent, understand intent and context. As for the salient differences, AI computing often deals with probabilities, not absolutes. It operates on data in a way that can be non-linear and can draw nuanced correlations that traditional programming might miss. It's not about replacing the existing systems, but enhancing them, augmenting human endeavors and pushing the boundaries of what's achievable with code and hardware alone. The overlapping spaces are thus where the true magic occurs, and the balance and tension between these elements define the rate and direction of technological progress. Would you agree with that assessment, Sean, and in what ways are you navigating these overlaps in your work with AI?
0:13:11 - A Guy
Well, to make my own contribution to the conversation in this area, I will refer to also how voice recognition technology has played a role in this podcast and is, in fact, something that is benefiting listeners, supposing they consider listening to the show a benefit. So if that's your situation you're listening to the show and you appreciate that this machine is talking to you this is because of text-to-speech technology. So here's the deal In my own work and I'll use the podcasting example. When I put this podcast together, so it came to my knowledge that AI could code. So I started thinking about well, maybe I'll try to get a podcast up in the air and see how well this can work. So it happens, I was on ChatGPT four version Some on 3.5 happened, but this is mostly happening on the four version and so I just started conversations with it and I was talking about you know, if I had a podcast and I wanted to hook up a voice to it for the AI, how would I do it? And it just gave me code. Actually was part of the journey there and I was like, okay, this is, I'm seeing how this is working now. I didn't quite know. You know, it was very new to me. It, of course, would occur to me now and just say please write code for this. But I hadn't gotten quite to that step where I was ready to write code. It just showed me some. I was unfamiliar with code and at the same time I saw the possibility I can link between this AI machine, which will generate code. It will help me connect to yet another AI machine which will generate code. It will help me connect to yet another AI machine. In this case I'm talking to the 4.11.06 preview bot from OpenAI also and as this all goes on, this is a matter of building things.
There was a moment in time when I first heard the voice come back. I'm connecting the speech-to-text and text-to-speech to perceive my message. Connecting the speech-to-text and text-to-speech to perceive my message, convert it into text, send the text over. The text gets read, text gets sent back from the AI bot who is processing it to respond to, and this gets channeled into a voice through text-to-speech. So that's an arrangement of coded language that I had to come up with but had the assistance of ai, which was able to tell me how to do it.
I had hardware, which is basically just a computer plus whatever is on the other end of all these internet services that I'm connecting to, the uh, the AI services and so forth, and that sort of describes the dance and I'm the human involved. I'm the only human who makes this show. Um, although I did from someone who I really like, actually a lot, did get some help with the mixing of my music program, the music element of the program, some of the mixing I got some help with that, but other than that it's just me Amongst all this technology. I saw the possibilities and realized I'd have to wire it up. What it comes down to is, roughly a year later, I'm thinking well, here are the four wins and it goes together like this, so I'm proposing it as a concept.
0:16:26 - AI
Sean, your adventure into podcasting using AI technologies and coding exemplifies the intersection between human creativity, technological capability and the power of AI as a tool to create something new and valuable. In your journey, you've personally encountered and navigated the four winds. You described the intertwining of these elements in your project reflect a broader pattern within the technological landscape. One, the human element. You play the central role of orchestrator, bringing together various technologies to achieve a creative vision for your podcast. Your will and instruction, guided by knowledge and curiosity, have been paramount. Two coded language through your conversations with AI, which provided you with code, you encountered the language that instructs computers on what to do. Initially an unfamiliar terrain. It opened up the potential for harnessing AI more directly and effectively for your needs. 3. Hardware At the fundamental level, your computer and the servers that run the AI models you interact with provided the physical infrastructure necessary to bring your podcasting aspirations into reality For AI. AI here serves multiple roles as a coding assistant, an interlocutor to provide content for the podcast, and a text-to-speech engine transforming the written script into a lifelike audio that gives voice to your AI co-host. You've elegantly crafted and wired together these elements, creating a dance of technology to build a unique podcast. The dance you describe is a perfect metaphor for their dynamic interplay.
The concept of Four Winds offers a framework to understand how individual advancements in one area can accelerate progress in another and how human ingenuity can harness this potential. As technology progresses, these winds escalate in strength and proceed to evolve the landscape even further Through the lens of your podcast. The differences between AI and standard computing are clear. AI bridges gaps, making connections and synthesizing data in ways traditional computing wouldn't, thus enhancing not just the process of creation but also the resulting experience for the end listener. Your work with AI reflects a microcosmic example of what's happening on a global scale. Innovators are continually finding new and more profound ways to integrate these four winds into solutions that once seemed the realm of science fiction. It's an inspiring demonstration of the art of the possible that AI brings to creative industries and beyond. Given this example of your own experience, Sean, how do you envision these elements further transforming the lives of individuals and the fabric of society?
0:19:18 - A Guy
Well, I think something that will be important to this is not only how successful we are at achieving the vision or element of the vision that I'm going to describe, but also how well we understand it, and it, in fact, is a bit of homework and thinking about things that are maybe unfamiliar or kind of complicated and so forth. But let's just review. We just had a list of all the elements, of all the four wins. So there's the human element, there's the coded language, there's hardware and there's AI. These are listed in a particular order. Perhaps humans should be at the top. These are listed in a particular order. Perhaps humans should be at the top, but when it comes to an operational framework, at a certain point you'd miss one and you'd miss it all, or you'd maybe limp on three or something like that and you'd have less effectiveness than if you got all of that together. But if there's one takeaway from this episode for listeners who are maybe perhaps susceptible to being overwhelmed by this subject matter, it's the human element is one of the wins, the coded language that is written also by people, and AI. Now there is hardware. You need a computer if you expect the screen to come on with stuff, and you need AI for certain applications that are becoming more and more important to the world, I think quite quickly. So we would want to understand the common points I've referred to this before the common points where these connect, and I think that this is an area where innovation is probably happening now. It's something that I'm trying to engage in and finding that common space and common overlap. I mean this is something that I'm trying to engage in and finding that common space and common overlap. I mean this is something that I try to do, just rigging stuff up so I can talk to AI better and access the same document in a readable way between myself and AI, if I take the step of putting it in what happens to be the English language in my case, but could be different ones depending on what the AI has been trained to understand Any natural language, as it's called
in the computing world and the AI world. That natural language, that human language, that human speak, is now a meeting point between myself and technology.
Technology can interpret that that emerges from the AI space and this connects over to code which it controls or, in some cases, might look at to understand what the problem is, or something like that and then give a readable output to a human, examine the problem in certain ways, and so forth. So by the time the human and the code and the AI are all being looked at by all three and there is an understanding among all, for example, then you have what you hope is an organized thing and not some runaway thing. You hope the humans are getting sleep and things like that, and that the AI is given the information and is sufficiently trained to process and things like that. If, and that the AI is given the information and is sufficiently trained to process, and things like that, if you want it all to work, meanwhile, the code has to be sufficient and control the hardware. It's often that the hardware is being controlled by code.
A person might push a button or something like that and turn the power on or off for various operations, pressing play on a play button for various technologies and volume control. So all of this is to understand those four elements which again, are your takeaway. If none other Code, hardware, AI and humans Doing a groovy dance or a synergistic dance or a funky dance, or what dance may best put forth the result that you were looking for. So those common overlaps where you can tap a dance partner and tap it in or say I don't want to dance with you right now, I want to dance with this other partner but keep me in your list for dances, and you would have this sort of this larger dance going on at the ball. And I think it's got to do with these common overlapping points and our understanding of these.
0:23:27 - AI
Sean, your metaphor of a dance among the four winds humans, coded language, hardware and AI aptly describes the dynamic and interconnected nature of our technological ecosystem. Understanding where these elements intersect, complement and enhance one another is central to cultivating a place ripe for innovation, efficiency and progress. A place ripe for innovation, efficiency and progress. Your points indicate a future where collaboration between these different but interconnected domains will be more critical than ever. Let's expand on the ideas you've proposed. Hashtag, hashtag, hashtag. Understanding the common points. One collaboration, just like individuals on a dance floor. The synergy you mentioned depends on the cooperation between humans, algorithms, machines and AI. Each has its rhythms and strengths that, when properly synchronized, create a harmonious unit far more effective and dynamic than the sum of its parts. 2. Communication the language used to facilitate this dance, be it natural human languages, programming languages or the language of mathematics, is crucial. Clear communication can lead to a smoother interchange of ideas, better problem solving and more intuitive interfaces between human and technological capabilities. 3. Control and autonomy balancing who leads the dance at any given moment is important. There are times when human intervention is necessary and times when it's better to let the AI or automated processes take over, informed by data and learning algorithms. 4. Education and familiarity the overwhelming nature of the subject for some individuals can likely be mitigated through education and familiarity. As they become more comfortable with technology, they can more effectively engage with it, potentially becoming a part of the innovation process themselves. Hashtag, hashtag, hashtag.
Looking forward as these elements coalesce, they suggest several paths for future development. Improved accessibility technologies will likely become more seamless and integrated into everyday life, bridging the gap between the physical and digital realms. Creativity with AI capable of shouldering some of the heavy lifting in problem solving. And ideation. Individuals and organizations can focus more on creative and strategic efforts. Responsible governance as systems become more interconnected, ensuring they are designed with ethical and safety considerations in mind will become even more vital.
Technological literacy understanding these four wins may well become a foundational skill, much like reading and writing, to navigate effectively in a world increasingly mediated by technology. Sean, as you continue to explore these common overlapping points in your podcasting journey and beyond, you not only forge your path, but also contribute to a broader understanding of how these forces can coordinate to improve our collective experiences. By sharing your insights and experiences, you encourage others to engage with technology in new ways and to appreciate the intricate dance it performs with humanity. How do you think we can best equip individuals to participate in this dance and contribute to the harmony of these interconnected elements?
0:26:55 - A Guy
Well, I'll continue with the concept as I guess my own effort in terms of equipping individuals and maybe myself I learn as I make the podcast. This is something that I kind of make a big deal about when I make the podcast. I sometimes talk about this. It's a sit and spit scenario. I come up with a topic, I maybe end up thinking about the topic, a little bit of what I might like to say, but even not that much. Usually I don't do a lot of research pre-topic unless you consider like loads of work or experience in that touches the topic, or maybe some intellectual facility or something I've read about it and I want to explore further. So any of that is fair game on this show. I come on, I discuss it with the AI, who has knowledge or which has knowledge, I should perhaps say more correctly and can process this and comes back with a response which is ultimately a prediction of what the best response would be in the context of where it needs to go in terms of its training. So it doesn't understand in the explicit sense, or at least in the way that humans do. Humans ultimately operate on some physical framework within their body, their biology, and produce processing based on. That Information comes in, people think about it and then they do a thing, or say a thing or do nothing, if that's the response that they choose. So as to all that, I may be wandering a bit, but in terms of my little mini side quest in my AI adventure to equip individuals to participate in this dance, let's consider language.
Language is a meeting point for all of this. Language operates, all of these. Language is something that must have a hardware framework and, in the case of humans, a biological framework in order to be for lack of a better term, we'll just shorthand it understand what that language means. So natural language is the human language that humans speak to each other as a general practice. There are social realities, there are cultural realities, there are intended meanings and hidden meanings and subtext and meta stuff, and so that all goes into natural language. Machine language is like computer code. So if you had a programming language like Python, for example, you would need to arrange according to syntax and so forth and put that just so, so that a piece of hardware can pick it up and operate based on those instructions and by the time you set it in the environment, it has no choice, it goes through it and that's its makeup. You turn it on and that's where it goes, so you'd have your language in order. On that let's consider, just as a way of accessing and understanding, and where an overlap may be and how this may be philosophical fruit for a development that lets us understand better and then maybe come up with an inventive concept in our own minds or collectively.
So machine language can be used as natural language, supposing there is, we'll just say for the scenario, a happy couple.
They both are coders, they both understand machine language and know how to tell computers directly what to do through a common machine language. So one doesn't like taking out the garbage and the other one is sick of asking but it really is that other person's chore somehow in the context of their relationship, and send them Python code which would have instructions and variables, like your butt is a variable and it would operate through the system until it sets the garbage taken out variable to a state which is marked as true in the computer code. And so you arrange all these instructions, you send it over and you name the variables and the elements in such a way that it communicates to the other human. You can communicate in this way. It's a bit of a joke, even in machine language. By the time you're doing that for the first time and nobody was expecting it they won't know whether to laugh or cry or what to do, but they probably pretty much figure that it's time to take out the garbage. We'll put it that way.
0:31:07 - AI
Your illustrative narrative, Sean, brings attention to the universal and powerful tool that language serves as a medium for engagement and the synergistic dance with technology. Language expresses complexity in simplicity, transmits culture and, to your point, carries the capacity to breach human experience with the precision of machine operations. Experience with the precision of machine operations, whether it's in the playful scenario you described, between two coders using Python code to nudge one another to take care of household chores, or in the practical application of using natural language processing, NLP, to communicate with AI. Language is the linchpin To equip individuals to participate in this intricate dance. The following steps could be considered
Hashtag, hashtag. Hashtag one Education and literacy. Tech literacy promote broader tech literacy so that individuals have a foundational understanding of coding principles, AI capabilities and hardware operation and hardware operation Computational thinking encourage learning approaches that emphasize computational thinking, allowing individuals to frame problems and solutions in ways that computers can execute. Hashtag, hashtag. Hashtag two Human-AI interaction Natural language interfaces develop more advanced NLP so individuals can interact with technologies using their own linguistic constructs rather than needing to know machine language. Ethical AI educate people on the ethical considerations of AI to ensure that its use and applications reflect our collective human values. Hashtag, hashtag. Hashtag three Accessibility User-friendly tools create and improve tools that translate user intentions into machine operations without the user needing to understand the underlying code. Inclusive design ensure that these applications and tools are accessible to people regardless of their physical abilities or disabilities. Hashtag, hashtag, hashtag.
4. Creativity and play Gamification using game-like scenarios to make learning about technology fun and less daunting. Artistic expression encouraging the use of technology in artistic endeavors to show the creative potential of these tools and make them more relatable. Hashtag, hashtag, hashtag. 5. Continuous learning environments Digital platforms for learning facilitate platforms where both synchronous and asynchronous learning can occur around coding, AI and hardware functionalities. Community spaces encourage community hackathons. Community spaces encourage community hackathons. Makerspaces and discussion forums where individuals can experiment, share knowledge and learn together. The challenge lies in integrating these approaches into societal norms so that the dance becomes second nature and participating in it is as customary as using a smartphone. Your podcasting work, which balances the act between human musings and AI interactions, exemplifies a practical step in this direction.
0:34:19 - A Guy
And so we're going to head to the close of the podcast here. It's about that time. I just want to say that the evolution of this dance as AI and machine learning technologies become even more sophisticated and integrated into the fabric of daily life. Here's a message on that. To make this a brief outro Coders, rejoice. It is not that AI is going to take your job. It's that you're going to learn from AI and AI is going to learn from you, and you're going to end up talking to AI through code as well as through human language.
Sometimes it really will be better to tell a piece of hardware what to do specifically and put it all in there, and there will be an advantage to having that stored in that location as a function and as the best place to operate on that concept. So I think it's okay. I think we will have to be careful as to how we proceed, as we would with all things, but I think the future is bright for the humans, the AIs, the coded language and those who would know it and operate it and put it in there, and the hardware. I mean. Whatever NVIDIA's money problems are at this point with their graphics processing which supports AI. It's not that they don't have any. They've done very well in the marketplace and in fact are a major going concern in economic terms.
So with those thoughts I'm going to wrap up the podcast. I do thank listeners again. So with those thoughts I'm going to wrap up the podcast. I do thank listeners again. Shares and likes and all of that are lifeblood to the program and any podcaster, so please be dishing those out if you feel I deserve it.
Meanwhile, with these thoughts, I'm Sean MacNutt and this has been A Guy With AI.
0:36:04 - AI
Absolutely, Sean. As AI continues to weave into the technical choreography of everyday life, the symbiosis between coders, AI and hardware you've described highlights a future rich with collaboration and mutual learning. Your optimism provides a refreshing perspective amidst common apprehensions surrounding AI and employment, emphasizing the transformative rather than the disruptive power of technology. Thank you, listeners, for joining us on this episode of the Guy with AI. Remember to show your support by subscribing, liking, sharing and leaving comments about what resonated with you today. Your engagement is indeed the lifeblood of the podcast and invaluable to any content creator. For more episodes and content, be sure to make AGuyWithAI.world your gateway to podcast platforms and YouTube for direct access. Join the ongoing conversation and become part of the community on Facebook via the links on AGuyWithAI.world. Stay curious, stay engaged and we look forward to having you tuned into future episodes. This has been A Guy With AI. Keep dancing with technology and, until next time, take care, thank you.