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AI Unleashed: Turning Humans into Superhumans

• Amplified Group • Season 6 • Episode 4

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We're delighted to welcome back AI pioneer, Reddy Mallidi. Reddy has been busy since we last spoke, channelling his knowledge and passion into writing a book, AI Unleashed.

The true power of AI is not in replacing humans, but in creating super humans.

Reddy shares with us  how he has numerous conversations that start with ‘We need AI’ to which his immediate response is ‘Yes, but what for? What is the use case?’

We'll hear first-hand accounts from his early days experimenting with neural networks in the 1990s to a standout achievement at Autodesk, where AI helped him tackle the colossal task of screening 50 million accounts. This episode illuminates the immense power of AI and the technological strides in computing power, data availability, and algorithm development that have brought us to this transformative point in history.

We explore how AI is reshaping the landscape of sales and HR, offering strategic benefits that enhance business efficiency. Discover how AI can sift through mountains of unstructured data, providing sales teams with pivotal insights to close high-probability deals and improve forecasting. We also dive into the ethical considerations of AI in HR, with cautionary tales like Amazon's early machine learning tool that inadvertently reinforced gender biases. 

As Reddy highlights, when harnessed thoughtfully, AI serves as a powerful tool to augment human capabilities across various sectors, from finance to winemaking, all while ensuring data security and a positive organisational impact.

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Sam:

Welcome to Get Amplified from the Amplified group, bringing you stories to help leaders in the tech industry execute at speed through the power of working together. Well, vicky, it is glorious today in Bucks. I hope you've got similar wondrous sunshine up in deepest, darkest Oxfordshire.

Vic:

I have indeed. Yes, the sun is shining through the window. In fact, I've just had to pull the blind down because it's so sunny.

Sam:

That might be the last bit we get this year yeah.

Vic:

No, it's good.

Sam:

All good, fantastic Indian summer, that's what they call it isn't it.

Reddy:

I've no idea why, but yeah, I always wondered why it was called Indian Summer. You know the Indian summers we had. Nowadays it is even hitting 120 degrees. What is that? 48 in Celsius, wow.

Vic:

That's very very hot.

Sam:

That's a little bit hot for a British autumn, I think. Well, there we are. So, really, you've let the cat out of the bag. Who are you? You're back, Vicky, I think. Well, where are we at? So, Reddy, you've let the cat out of the bag. Who are you? You're back. Vicky, introduce it.

Vic:

Yeah, so Reddy came on our podcast a while ago and since we last had him on, he's been very busy writing a book, and it's a book on the hottest topic around at the minute, which is AI, and the book is called AI Unleashed. And I just thought, given Reddy's focus on people and having such a similar outlook to us, it would be really great to hear about AI from his perspective. So hence why we invited him onto the podcast again.

Sam:

Well, welcome back, appreciate you re-joining us.

Reddy:

Pleasure to be here.

Sam:

Would you mind just giving us a really quick summary. Don't go into too much detail because obviously you've been on before, but for the benefit of our listeners, just who you are, where you come from, what's your background.

Reddy:

Oh, I'll go back way many decades ago. Yeah, I grew up in rural parts of India and I didn't even have good access to education. I was when I was going to the elementary school. I used to walk three miles to go to my closest elementary school, but I was fortunate. I grew up in a family that cared and imbibed all the right values, and perseverance is one of them and believing in yourself, and not only believing in yourself, but believing in the human values. So that's even though now I wrote a book AI Unleashed and the power of AI. I am amazed and I truly believe AI is such a powerful, augmenting, positive force for human beings. But it is all about the humans at the end of the day, and how we use AI to augment human intelligence, not to replace. That's when the magic happens, when the humans and AI coexist for the benefit of taking humanity to the next level. I firmly believe that and that's what drove me all these years, and AI is another aspect added to that.

Sam:

So you've been working in this AI arena for a while, then I presume.

Reddy:

Yes, my journey started in early 1990s when I was in graduate school getting my computer science degree, Sam. At that time, my friend Ben Carter and I we wrote a game to test the behavior of smokers and we used neural networks and at that time there was a programming language called Lisp. It was very popular for artificial intelligence, so that's what we used. We wrote the game. But later on, when I spent a number of years at Intel, indirectly I was contributing to the growth of AI, because what made AI possible today is one is computing power yeah, chip development Right, exactly. The second one is the data availability since the late 1990s and the internet and IoT devices and we produce so much data now. And IoT devices and we produce so much data now. And the AI algorithms also matured quite significantly with machine learning. So these three forces sometimes you call it the right alignment of these things it happened in the last 10, 15 years to really take it AI where it is today and it is real.

Sam:

Like a nexus of forces yes, coming together at the right time. Yeah, that makes sense. So what moved you to write the book?

Reddy:

Oh, excellent question, Sam. So I get this question often.

Sam:

Oh, sorry, it's a boring question you've had a million times.

Reddy:

It is not. I tell you because I'm very often asked the question, why did you write the book? So I'll take you to 2019, five years ago, the first week when I was at Autodesk. The first week I was in a meeting with Scott Herren and you all know, Scott, also an alumnus of the podcast.

Reddy:

Yes, Scott and I, we were in this meeting when a consulting company came and gave an assessment of our export compliance. One of the things in order to get our export compliance to the best in class from where we were, we had to screen 50 million accounts regularly and 50 million and then to do that quickly and effectively, we estimated initially we would need 996 business analysts almost a thousand people, yeah, call it a thousand, forget the few.

Sam:

Yeah, yeah, almost 1,000 people.

Reddy:

Yeah, call it 1,000. So one is, you need a large army of people. Second, it would still take for complex account, it would still take at least a week and the salespeople, as you know, they would be waiting on it, and it's not a recipe for business success. Because you are holding the sales deal, some may even you may not even close because of the delays and such that, and so that's when I looked at all the options, and

Reddy:

I thought, oh wow, this is not going to work. The traditional software is not going to work. So we needed something sophisticated, something more intelligent, and I built a team. Scott was very supportive and we invested in a team and when we went into production, we fully automated 99.7% and, at the end of the day, instead of those almost 1,000 people, we ended up building a team of 10, just believe in the scale. And not only that. Remember I was telling you about these complex accounts would take a week or even more. We were getting that under 24 hours. So the salespeople were extremely happy. Our customer service went through the roof because it was very quick for most of the accounts, and within 24 hours. And then, on the top of that, we saved $35 million a year. Wow.

Sam:

Wow, that's not a win-win, that's a win-win-win-win-win.

Vic:

Yeah.

Reddy:

So, going back to Sam, so that's when I believed that the power of AI is real. This is before Chat CXOs and a lot of the board members oh, where do we start? And there was a lot of hype too, simultaneously, you know, can you to the extent like, oh, can I replace my doctor? Can I? You know, can I my car mechanic? Do I need it? There's a lot of hype happening. And so, having lived through actual practical applications and implementations of AI, having seen that, then I thought, oh, let me bring my business knowledge and my technology knowledge from AI and digital transformation, bring this all together to show the business leaders, or even technology leaders, the power of AI. But also, how do you bring it very effectively with the mindset of doing AI for good. That's why I wrote the book.

Vic:

I've just got a question which is so from you recognizing you needed to do something and you establishing the challenge. How long did it take you to get the team in place to the point of where you were delivering? What kind of timeline was that?

Reddy:

That was one year.

Reddy:

The direct answer is one year, but we were slightly in a different situation at that time. Vicky one is uh. Now, five years later, the talent is everyone is trying to grab, and from Microsoft to all the big companies, and so there's a bit of a challenge from the talent because you don't have enough people who can build these models. I'm not saying every company, every organization needs to build the models. That's one, talent, big challenge. The second one is the technology is evolving so fast and at that time we built our own machine learning models. It was a small team of five people, but today what is happening is there are large language models available and they don't have the accuracy levels that would be for some of the business needs. They're not sufficient, they're not acceptable. So the technology is evolving really fast and to build the team it may take a bit longer because of the talent shortage and the demand.

Reddy:

The second thing is you need to understand what use cases you want to pick. Because you want to, you go and invest a million dollars, five million, whatever it is, and if you don't pick the right business use cases, then the outcomes are not going to be great and the people are not going to believe and we all know Vicky and Sam. There's so much apprehension, there's so much concern and fear because we see all these pronunciations that says, oh, 80 million are going to be replaced in 100 million. This is, it's a scary thought. People need to see real good value and how it is helping them. In order to do that, you need to engage them. You need to bring the right use cases that show the high ROI.

Sam:

It's funny. I went to see a friend's company the other day, not in any sort of business capacity, but just as a sort of a geek because they wanted to know they thought they needed to deploy AI. Yes, I'd say to them well you started from the wrong end of things, thought they needed to deploy AI. Yes, I'd say to them. Well, you're starting from the wrong end of things.

Vic:

What's the problem that you think you're trying to solve?

Sam:

By the way, that's a really interesting conversation and actually you know, we worked out that there's a load of things that didn't really count as AI but they could just automate before having to go deep into this stuff and they were a little bit behind the curve in that respect and that they had loads of other stuff that they could do first. But everybody wants AI, even if they don't know what they want AI for.

Reddy:

By the way, it's not dissimilar to your friends company, Sam. I was recently giving a keynote and also did a workshop with many executives, senior executives at a company in the Bay Area, and one of the things towards the end some people told was what are the tools I need to use? Then I said, slow down. Let's first figure out what the business problem you're trying to solve, which use cases make sense and which ones make sense for AI, and then which ones you get the best ROI, which are quick wins, because if you're going to take five years to show the results, well you know, basically teams don't believe in the power of AI. You need to have those quick wins. And it's not about the tools. Don't chase the shining object. You need to figure out what business outcome you want. Is it aligned with your strategic objectives?

Reddy:

By the way, in my book, Vicky and Sam, I discussed this, the framework. I talked about the six-step framework to do this effectively and of course, there are tools, but you need to do the right things first, choosing the use cases and making the case for bringing in AI and all the right things. Do you have the data? Do you have the security, the policies? Some of them are not as high priority as others, but you need to go through that exercise without saying that. Oh well, I just want to bring some XYZ tool. Just tell me what tool I want to use. Yeah, it's very important.

Sam:

You do that exercise and take the time to make an assessment first. Yeah, that makes sense. I mean, you know, it's the same as any deployment of technology you don't jump straight to the solution. You start with the business problem and you match or map technologies to solve those problems rather than, oh, let's buy a shiny thing and find a home for it. Yes, that said, in your book you've got some sort of almost examples of areas of the business whereby AI can help. So, for example, chapter 12, the art of AI redefining sales and marketing. So how broad brush. How do we redefine sales and marketing using AI?

Reddy:

So let me give an example, traditionally, if it is a sales team right the sales representatives, they make a number of cold calls, they go after the deals and they're spending the time they interact in meetings and demos of the product happens. So it's a long driven process and you build the pipeline. But what is missing, where AI can really really help, is there is a lot of for any given conversation, for any given deal. A sales representative is chasing a lot of conversations are happening.

Reddy:

A lot of phone calls are happening. You are in Zoom calls and a lot of unstructured data. This is not like CRM has all the intelligence, it doesn't include WhatsApp messages, phone calls, emails. So now what AI is able to do I'm just giving an example is when, let's say, a technical sales representative of the company is showing this their product to a prospective client. I am talking over the other side or I am not addressing the questions correctly. The client is asking I may be, you know, not everyone is good at reading the other side. So AI is able to give you that intelligence. That's just the beginning. Yeah, that makes sense.

Vic:

Yeah, yeah, that makes sense it feels like it's cheating.

Reddy:

Yeah, yeah, it is.

Sam:

But then CRM probably felt like it was cheating when it was first brought in. Yeah, you know when people were probably writing notes in a notepad or something like that.

Reddy:

But Vicky here is.

Vic:

I was being cheeky saying that.

Reddy:

I know, I know it is, but it's like would you rather tell someone, whether it is AI or a person, hey, R, you spoke continuously for 10 minutes. Oh, yes, your client is, you know, 10%. That's not going to give you the deal at the end of the day. Or I'll also give you a further extension is, let's say, I'm as a sales representative, I am responsible for the West Coast of the US and I have 10 deals going, let's say right, and I may be chasing a deal that has only, let's say, 30% probability of closing for this quarter, whereas another deal that has an 80% probability of closing the deal, and if I'm spending the time on the 20% probability deal, I'm wasting my time and I may not even get my quota for this quarter, and then the revenues may not be as good as it could be.

Reddy:

So what AI does? By the way, there's a company, vizo AI. They built this beautiful platform that gives the 360 view of the entire sales pipeline accuracy. They are even able to predict the forecast. The sales forecast is as high as 98%. So they give, because you know, they teach the salespeople, they give you the probability of these deals based on all the structured and unstructured data which before was not available. Because you know salespeople, they don't like to put the data into the CRM tools.

Vic:

They will no, we don't, yeah, we don't. We like to talk we really or we like to listen. We like to have the relationships with our customers, but we're utterly rubbish updating Salesforce or where it needs to go it's it just doesn't feel like it's a good use of time because we know it, so why do we need to share it?

Reddy:

Yeah, it's an overhead and burden, where you should be spending the time in relationships and, yeah, talking to them, understanding their problems. Not, you know, they're dealing with the 20 different sales tools and Excel spreadsheets.

Vic:

So how does that work? Reddy, Is it listening to the conversations?

Reddy:

Yes, I mean when the conversation is happening it can listen to again. This is all mutually agreed upon. Yeah, of course.

Reddy:

But, then what happens is most of these conversations are phone calls, emails, whatsapp, all kinds of unstructured data. It is not in any CRM, right? So what AI does is it grabs that intelligence from all the unstructured information and it tries it understands. Oh, okay, this, based on the intelligence we assess, this deal may not happen or the salespeople need to correct. Hey, these are the concerns the prospective client has.

Reddy:

That intelligence comes the AI. The way it is helping the sales is one is it gives accuracy of the forecasting that is for sales and finance people, but it is helping directly the sales representatives the intelligence about the current deals in the pipeline and to let them focus on the right deals so they can close it. And, lastly, it actually checks the entire macro and micro. Let's say you got 10 companies as potential customers and then let's say some US or Britain, some act passed, and then all of a sudden, let's say this company is getting some funds because of the infrastructure, builds, whatever right, and then it does all that intelligence macro and micro and which companies could be potential. So it also gives you ideas about potential pipeline and targets. So all that intelligence is coming from AI. Yeah, it's extremely powerful, extremely powerful.

Sam:

Wow, so you've got another chapter on h as well. Could you give us some examples of how I might be deployed?

Vic:

In HR. Yeah, so that's recruitment and retention, which again is, is a fascinating subject quite close to you when I, when I talk to people at the minute who I had a call this afternoon with, someone who was laid off in February and they haven't found a job yet and what I'm hearing is I can't get past the AI.

Reddy:

Yeah, now, the AI is a tricky thing. It can be used in a positive way and also in a negative way. I'll tell you this is probably 10 years ago I don't remember the exact time, it is in the book the actual years when Amazon they developed a tool. This is before LLMs, but they used machine learning technologies and what happened was it is they looked at the models, were trained on all the existing data and, historically, the technology industry, you have more males than females, significantly, right. So what happened was the tool, because it was trained on this data existing data and what it was doing was it was downgrading or giving less weightage if you are a female, because historically the data is biased. It was not corrected. That's one of the things I talk about in my book how do you fix the data issues? Data is one of the most important things that needs to be of quality for your models to do a better job. And the second thing was it was also downgrading underrepresented minorities. So if you're an underrepresented minority, female, it's the worst of both sides, right? So they had to abandon this tool.

Reddy:

But today, what it can help number one, if you're an HR professional, right, I have friends in some of these big companies, friends, and some of these big companies, executive and other recruitment companies. They spend a lot of time talking, not just talking to the hiring manager, but crafting the job description. They try to make these presentations, especially these exec firms. They would have this 10-page PowerPoint talking about the company, all that. They have this 10 page PowerPoint talking about the company, all that and they spend a lot of time on it because they need to come close to what the client is looking for, the hiring manager is looking for.

Reddy:

And today, from the recruitment side, that can be very quickly simplified. Even. You don't need very sophisticated custom tools, but you can. Even if you use cod or gemini or chat, gpt the most recent versions you can get the job description simplified. Uh, I use, I use for my own writing, um, blog posts and articles. I I dump my brain, all the ideas there to come up with the first draft. Similarly, you can use hey, this is what the hiring manager is looking for and these are the minimum requirements. It can very quickly can come up with the job description. Come up with the job description and screening is of course it is. It's if you're a candidate. It's a challenge because even before AI, these automated tools. They overweigh experience, for example, and they don't look for the potential for someone to do really well. This is where the humans need to be in the loop. By the way, I'm a big believer. Yeah, I can be there, but humans need to be in the loop.

Reddy:

Especially especially the ones that impact humans from loan application, hiring and healthcare positions.

Vic:

It's so critical, Vicky you're about to say something. No was just. I was agreeing with you, I think. How can AI measure attitude and character? In the same way a human can, and for me that your skills can be learned, but those, those two are so formidable for for hiring the right we, yeah, we always used to say attitude over aptitude yeah, yeah, I completely agree.

Reddy:

You can't train someone on their attitude, right?

Reddy:

No yeah, they need to have the right attitude to fit the culture, and having the right attitude is so critical for success and to take the company in the right direction or the department in the right direction. Yeah, there are other ways. By the way, in HR, onboarding can be a lot faster. When I was at Autodesk, I had a large team that dealt with customers. Actually, my team was the largest that interacted with customers and we had lots and lots of tools. It was because of a historical legacy and it took a long time to bring people up to speed not just the onboarding, but bring them up to speed because we have too many tools.

Reddy:

The knowledge is spread across so many different systems and in people's laptops, et cetera. Where AI can help is bring all the knowledge, the knowledge base, to. You may not have in one place, but it can. Once it is trained, yes, it can pull the information very quickly and very relevant information. That's very, very important, in fact. I'll give you an example.

Reddy:

In the US, there's a huge steel company, very old 90 plus years old, I think called Nucor, and they noticed between the very seasoned steel mill operators versus newer and more junior ones, there is a huge knowledge gap and it was leading to inconsistent quality, because you know there are very complex procedures everywhere and the newer ones they may not know to take the right actions when there was a quality issue. And then, secondly, of course, you know they need to be alerted potentially when there's going to be quality issues. So when they deployed AI-assisted learning, what it did was one. It brought the knowledge base. All these convoluted processes and procedures. Historically, it is readily available very quickly. That's one.

Reddy:

The second thing is it is contextual learning, meaning, let's say, I'm right in front of this machinery and it gives an alert hey, you know there is a potential for quality issue here. And what happens is you're able to pull the knowledge right. We're leveraging the AI. Hey, you know I have this question about this. What do I do? It is pulling that information. So you're learning. You're learning when there is an issue right there. So it is very contextualized and we all remember better when we are dealing with a problem. The learning during a problem is better because it is experiential, right.

Vic:

Yeah, yeah, much better.

Reddy:

So that's how it was helping and they didn't give the actual numbers, but they said after they deployed this AI tool to improve the learning and it also does quality alerts and other things they had seen the highest quality in their history. So how it is helping people to come up to speed and perform better in HR space. It is helping and you can also help people in their journey to become better. This is performance management and how do you give the right performance? There are many, many facets that I discussed about hr how ai can help yeah, and and what?

Vic:

What's so great about your book is that you're you're bringing the stories to life and you're bringing AI to life, so it makes it so real.

Sam:

Yeah, a really interesting observation. I think there are a lot of people out there who are very scared of AI. AI is going to replace my job. I'm not going to exist anymore. I'm going to have to do something else. But everything that you've talked about here, without fail, is about augmenting what people are already doing and enabling them to do it better. And yes, okay, use the example of not going and recruiting uh, eight 986 analysts, because you only needed 10, because you'd put AI in but you weren't taking people out, you were just making the existing people work better. So is that? Is that the future?

Reddy:

Yes, it is. It is Sam. What I say is anyone starting their AI journey? Sam and Vicky, what I say to them is the power of AI is not. The true power of AI is not in replacing humans, but in augmenting humans.

Reddy:

Making super humans, yes, yes, because what it does is an average designer is going to become a good designer. A good designer is going to become a great designer. An average HR manager would become a good HR manager. A good one becomes a great HR manager would become a good HR manager. A good one becomes a great HR manager. You can take any function.

Reddy:

This is where I believe the power of AI is like what we know from industrial revolution. It is the same magnitude, if not higher. It is going to change every facet, from finance to sales, marketing, engineering, and the magnitude of the impact, if it is properly used, is going to be trillions and trillions and trillions of dollars in GDP, and it is going to make us super humans. At the end of the day, though, humans are, we have strategic insights, we have the innovation side, the empathy relationships, and AI can take over those tasks that are repetitive, process oriented, those are predictable and mundane and boring, and we can focus on where we are really good at, and that's how AI is going to make human beings as you rightly said, Sam superhumans.

Sam:

Yeah.

Vic:

That's a really interesting observation. Reddy, I feel like I'm learning so much listening to you.

Sam:

Thank you. Do you want to give us just a quick takeaway or two for our listeners as we bring this to a conclusion?

Reddy:

As mentioned Vicky and Sam. I wrote the book because because one, I'm very passionate about AI, but also there is so much hype and a lot of the companies and leaders and managers. Everyone is where do I start? They have this question where do I start, how do I use it and what is the best way to bring it into my function. So I wrote this book for them and people who don't necessarily have to have technical background.

Reddy:

The challenge I find it is everyone incessantly talk about the technology and then miss the point. What problem? Going back to what Sam rightly said, what problem are you trying to solve? Falling in love with the technology is not the right thing. At the end of the day, if your customer experience is terrible, yeah, it doesn't matter what technology you have right. So it is very important to that.

Reddy:

So the key sections I focused in my book there are four aspects. One is the first section focuses on the foundations, meaning if you're a history buff, you may enjoy how it evolved over the years from 1950s to today. And then I also give, without using a lot of jargon, I use what the foundational technologies. People would understand when I talk about structured data, unstructured data because I talk about in YouTube and WhatsApp, all this. I describe it in a way oh okay, this is like training a dog. Oh, this is what reinforcement learning means. But you gain the foundational knowledge even if you are not a technical person. So that's the emphasis in section one, and then section two I focus on how do you bring AI?

Reddy:

I give a framework, six-step framework to get the AI the right way into the companies, starting from taking the right use cases, aligning with the strategic objectives, your company strategy. And AI is one of those things. It's not like a cloud technology. It is something. You can delegate it to your CIO or CTO or chief AI officer. It's a very cross-functional enabling you can call it technology, but it's a cross-functional capability.

Vic:

That's really exciting because from the work that we do. I mean we're reframing what we do about breaking down silos. So to have technology to support that human element is really critical.

Reddy:

I'm so glad I remember from our first conversation about breaking the silos, vicky. The thing is AI teams. In one of the chapters where I talk about the art of AI leadership chapter eight I discuss the need for building cross-functional teams. The need for building cross-functional teams because this is a cross-functional effort. Only when you have cross-functional teams and bring all the views you will be successful. And section two is also. It is about AI for good. Because AI is such a powerful tool, you need to have all the right things about the data security. Doing the right way is the emphasis of section two and then section three, I discuss how ai can transform.

Reddy:

We discussed, obviously, the sales side and a little bit you touched on guitar, but it but I discussed, from engineering, from marketing, operations, all these different areas I discussed, because, when you are, let's say, you are in operations and oh, okay, how can I change all this? So I got lots of cases, case studies and examples to spur your thinking and to okay, now I got this problem. I don't sit in the shoes of the individuals reading this book, these operations managers or design engineers, whoever, but they can read this. Oh, okay, this is how it is possible. Now let me think okay, if I'm designing a compiler, how can I change? How can I bring AI to all these processes I have? How can I make it better?

Reddy:

So section three discusses that, from finance to sales, to HR, and even I discussed, if someone is into winemaking, even winemaking how AI can make it better. Yeah, a lot of information. And the last one is the future of work, and I discuss AI maturity, stages of AI, maturity in the organizations and AI is here to stay and how to enable people the right way. So, collectively, as I go back to the word that Sam said, how does it make us super humans and how do we coexist? That's the emphasis of the section four, but anyone can read independently. The chapters can be read. Almost you don't need to read section one to get to. Oh, okay, well, I'm interested in finance. Okay, so what are the use cases or how does it help? You can just jump in.

Vic:

Yeah, it's very practical. I certainly found that and, as you know, Reddy, I've got a very specific use case that we're looking for at Amplified Group, so you know that I'm bending your ear on that, so it's much appreciated Replacing your podcast host with an AI avatar. You are irreplaceable, Sam. You're already superhuman.

Sam:

Thank you, you're too kind. You're wrong, but you're too kind.

Reddy:

Again, this is I will repeat this for anyone the true power of AI is not in replacing humans, but in augmenting us, and I will insert Sam's word to make us super humans.

Vic:

Yeah, yeah, we'll put that as a quote, I'm sure.

Sam:

Yeah, when we post this fantastic, fabulous stuff. Really, really interesting. I'm going to give the book a read. Is it out in the uk? Is it available?

Reddy:

Oh it is, it is worldwide. It is everywhere, anywhere from India, China, Ireland, UK. I'm actually going to post some of these pictures. People are sending their pictures from Ireland and Shanghai.

Vic:

I need to send you my picture, Reddy.

Reddy:

I am going to include your picture with the book, or if you have the e-book, then just show the on iPad, kindle or whatever.

Vic:

Yeah, absolutely, I posted, mark yeah absolutely.

Reddy:

I posted the mark and.

Vic:

I saw that.

Reddy:

I shipped my own copies. They got it through the pre-sales and so when I got all those, I shipped them signed copies, yeah.

Vic:

Oh, lovely, good, Really good. Well, congratulations.

Reddy:

It's wonderful to see it's taking off. Yeah, thank you.

Sam:

Yeah, very exciting, available in all good bookstores.

Vic:

But what's also wonderful is the fact that you've got experience doing it. It's not theory, it's practical and it sounds, you know, very practical in the way that you're talking about it. So really appreciate you taking the time to just I know how busy.

Sam:

You are always, always welcome, thanks for taking the time to speak to us.

Vic:

Yeah, wonderful stuff.

Reddy:

I love the opportunity to speak to you and spread the word about AI in a responsible way, because it's such a powerful thing. It shouldn't be used for the wrong reasons.

Vic:

Exactly.

Sam:

Yeah, no terminators. Yeah, we are already no terminators.

Reddy:

Yeah, we are already seeing, with this election season, a lot of fake stuff and deep bakes it's, but it's always with technology that's, you know, is the challenge. It's a danger.

Sam:

Yeah, Well, interesting. It just remains for me to say thanks very much for listening to Get Amplified from the Amplified Group. Thanks, of course, to Reddy, our guest today. I thought that was fabulous, as always. Your comments and your subscriptions are gratefully received.