Breaking Banks
Hosted By Brett King, Jason Henrichs, & JP Nicols
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this week on the futurists trojana kadavamath because of the unintended consequences associated with AI we don’t know what kind of a consequences whether positive or negative it would bring so we need to be mindful in terms of how to immodulate this journey

welcome back to the futurists I am your host uh Brett King and in the hosting chair this week is my good pal O’Brien Solis from Salesforce Brian welcome to the show back hey it’s it’s good to be back I missed you yeah no it’s great um you know it’s it’s start of a new year and um it’s going to be certainly an energetic New Year there’s a lot of really interesting things happening um you know AI we’re going to get into that today but um you know I I mean I really enjoying doing this show but every week you know we we are now getting into stuff that increasingly things that we talked about many many years ago are starting to happen before our eyes like the AI like what’s happening with climate impact and so forth it’s such an interesting time to be living um yeah there’s it’s not without its challenges right obviously but um you know the in the field of futurism I think there’s a lot of really interesting potential yeah yeah that’s what uh that’s what Chad GPT tells me yeah I know I’m going up on a tangent already but um anyway we’re going to get into AI today we have a really interesting guest uh from Walmart she works in the uh um the Global Tech uh business for Walmart but specializes in AI in their lab strijana katava math welcome to the futurists thank you so much for having me here I’m excited to have this conversation and where are you base srijana I’m best of beer yeah Bay Area okay well so you you and Brian Howe from the same rough area or there he’s in New York today oh okay so probably he escaped the floods and all the rains that you had experience talking about right this you know we didn’t expect these sorts of things with the climate to be happening until the 2030s right honestly you know like in the projections we had but it seems to be happening now we have these more extreme weather events more frequently and the Bay Area really got hit hard you know this stuff yeah but um let’s be positive so what does um you know obviously there’s um some very straightforward applications of artificial intelligence in Walmart such as you know using robotics in factories to improve the efficiency of the factories potentially you know automated delivery technology we know Walmart’s been working on a series of drone uh drone Technologies uh you know obviously and they’ve done Partnerships with the robotic and autonomous vehicles in that play um we could even think of maybe having robots and AI in um you know the stores you know Robot vacuum cleaners and floor cleaners and things but um so it sounds like a lot of potential AI use so um you know how you know where what’s your role in terms of the fit will with all of that do you oversee a number of those programs are you deep diving on certain elements um how does it work in terms of the AI practice at Walmart yeah a wonderful question right so in terms of like you know my portfolio here at Walmart I lead the artificial intelligence Charter for our Omni retail business as well as the new and emerging business in the consumer attic space as well as data monetization space and membership space these are all different businesses of Walmart so we focus a lot on using uh data and specifically AI algorithms to build various personalization systems recommendation systems voice conversational platforms and also when you talk about using drones for delivery definitely like that involves a lot of using competitivision algorithms when you talk about AI in the stores we look at using shelf intelligence again using a combination of like OCR techniques as well as the computer vision techniques but also there has been a lot of usage of AI in the customer experience space wherein we are building these conversational platforms as well and especially during pandemic one of the prominent features that went out is like you know creating this virtual fitting room experiences for our customers especially the Gen Z’s who are more prone at doing this shopping online and that kind of reduces our returns as well because like you can try out different apparel we launched a series of new features including be your own model as well so all interesting applications of AI and I’m fortunate to work with some interesting team members who are AI experts bringing a lot of experience handling humongous amount of data and deploying them at scale now it’s still a challenge finding the right Talent isn’t it in in this environment I mean I know there’s a shortage of tech people generally but I heard this I don’t know if it’s apocryphal but I heard this story that Jeff Bezos went out and tried to hire a thousand data scientists you know a few years ago and basically said to his team you can pay whatever you need to pay and he could only get 600 right this is what I heard right but um but um you know Brian you know maybe you jump in as well I mean um you know where where are we going to get the talent for this it seems like from an education perspective you know we’ve got some some challenges itself getting more people interested in the fields of AI and these these Robotics and so forth absolutely Sir John I have so many questions for you and I’m trying to hold them back uh maybe Brett we could have a three or four hour episode this time around yeah exactly but there’s two things I want to ask and they’re both very different but I do want to build on what Brett is asking because I know you’ve been involved in also trying to expand the net that companies cast in order to bring on AI professionals and experts within the organization specifically in the areas of diversity and I’d love to hear about the challenges that you see but also some of the creative ways that maybe they’re not thinking about to expand their candidates for possible consideration yeah absolutely so in terms of like you know overall getting the talent right so Brett really uh touched upon a very important point right so there is definitely this need of data scientists uh within the industry because AI is evolving and a lot of a lot of other Industries which did not have these dimensions of AI applications earlier are now trying to explore uh applications of AI within their space however the challenge is not just about getting the talent but also the talent that can adopt whether industry needs over time right so because when I started uh 10 to 15 years ago it was primarily looking at a data scientist should have some sort of skill sets around ability to handle humongous amount of data sets programmatically because we are getting a lot of data also having a decent understanding of statistics and a bit of a domain knowledge but today the expectations from data scientists is much more because the expectation is they need to have very good understanding of like technology stack and Achieve computational efficiencies because that’s a humongous resource investment for the company right so now because that’s evolving over a period of time I do not believe that we’ll have this genre of professionals called as data scientists we’ll have ai experts who’ll be bringing in a lot of nuances around bringing in Innovation through different nuanced techniques of deploying these models or coming up with pure statistical modifications to models and then we’ll have another set of talent who are machine learning Engineers who have this ability to deploy the models in the production environment and scale them effectively right so because most of the data scientist jobs would be done by automl applications that we have on gcp or AWS right so I believe that becomes a little bit of an interesting mix and we need to start getting ready to hire similar kind of a talents having said that the industry is maturing not all the teams would require applications that would be AI driven there could be a value chain wherein we are looking at applications which could require simple regression models to solve the problems right so there needs to be an analysis of the overall value chain and like you know how do we help the organization evolve through this value chain right in terms of the second aspect that you spoke about around diversity as we are seeing more and more yeah application across different Industries and touching different sections of the society it only makes sense for us to have the equal representation amongst the people who are developing these algorithms and these products right however that is not a case at this point of time right so women in Tech statistics indicates that 80 percent of the technology drops are held by men and only 20 percent being held by women and 26 percent of the Computing related jobs are held by women and out of that only three percent being held by Asian women um and this creates kind of a disparity and pandemic has not helped at all because we have seen that uh at least the caregiving because of the caregiving responsibilities it has led to some sort of psychological emotional challenges around well-being for women resulting in many women being displaced from the technology Workforce all right so that kind of creates a challenge around this aspect of bringing in more diversity and inclusion and requires organizations to be more thoughtful around acquiring and getting more talents I think I think we need women to help us train these models frankly you know we need that emotional Sensitivity I know that’s cliche but we need that um we need that diversity in the models that we’re building yeah and that’s all bias is already clearly a problem in in machine learning indeed so John I can ask I’m just going to ask a quick question and then I have a follow-on question which is uh do you have based on your work because I know you’ve you’ve done a lot in helping to raise awareness for diversity do you have any recommendations for companies in order to think differently about how they’re like for Jeff Bezos if he’s if he’s listening you know how does he get the other 400 by thinking uh through diversity yeah uh obviously uh data science uh is interdisciplinary skill all right so uh it requires people to work in a collaborative fashion with the product teams with engineering teams work very closely with the legal and governance team as well because we are seeing a lot of unintered consequences of AI application more and more we are seeing that the a algorithms are even like you know playing a role in terms of screening the candidates right so I think it’s going to be a balance in terms of not necessarily just having the algorithm screen and the candidates but also being thoughtful in terms of looking at how do we bring in more representation how do we make sure the algorithms that these uh or the data sets these algorithms are being trained on are more representative in nature right so I think we need to kind of look at it through multiple facets here you know see that that right there is something that Brad to your point that you just made is that there’s an intentionality behind how those algorithms are you even executed and so the intention of saying let us Explore More diversity and the candidates that we consider has to be trained but also has to be explicit uh from whoever’s uh whomever’s leading that program so for those listening that that means that you have to consider then deploying or updating upgrading I should say the algorithm for exactly what you’re John is talking about so that I do want to bring up a timely thing uh just simply because I’m here in New York uh attending the national retail Federation convention which Walmart is clearly talked about everywhere down every aisle the the thing about retail is that it isn’t just about what a store looks like it’s everything in terms of how it operates inventory supply chain customer customer experience you mentioned earlier uh it’s the data sets are are mind-numbing uh humongous but also a very specific in terms of how you have to process that data understand it refresh that data to keep up with Trends and I just wanted to ask you something I was in a meeting yesterday the very large retailer and the question of AI came up with understanding you know when it comes to customer experience what is is there an all-knowing data set or what are the best practices that you’re seeing in terms of applying AI to enhance areas of of the customer experience but then also as the customer relationship and it was a really interesting question because I think the the answer that they were looking for was give us a black box of which we can plug in this brain to but I think I’d love to hear your your thoughts on it yeah uh very good and very relevant question here Brian so machine learning algorithms are the statistical representation of the world that we live in they need to be trained and different kinds of data sets and when you’re talking about organizations like Walmart which have got humongous amount of data because of the transaction information that we collect this data runs into petabytes right so there is this focus on looking at how do we productionalize these data sets and productionize these models and help the organization evolve because we cannot necessarily use the AI algorithms to solve specific use cases because we are talking about the Enterprise scale and different geographies of operations as well as different channels of operations right so this is where we start focusing on evolving and talking about using Ai and productizing AI to generate enterprise-wide results rather than focusing on building algorithms for individual use cases because productizing AI helps the organization move up the value and it helps Drive Innovation utilize and enhance the intellectual capital of the organization as well as it helps us bring in Tech standardization across different geographies right but there are certain challenges associated with productizing data science right as you rightly mentioned around like in a bias that’s there in the data sets but also uh there are issues around losing resource Investments right so when you talk about the customer experience most of the projects succeed but sometimes because the customer behavior is evolving if the projects do not succeed the best case scenarios that you have just built a proof of concept and the worst case scenarios that you’ve built the entire product end to end and the results are not relevant enough right so focusing on creating those biases yeah so you do talk about the personalization element and so forth um and obviously we’ve talked about some of the more future focused projects like um you know the the drone delivery and so forth but what Innovations have you already put in place at the store level using AI can you talk about that yeah I can briefly touch upon that so that as I mentioned like you know at the store level right so there are uh there’s shelf intelligence right when we talk about like you know maybe looking at scanning and looking at placing different products across different aisles we need to kind of look at the space optimization we also need to look at like you know how is the customer experience overall but also when you take a look at this from the online or the e-commerce perspective we look at the digital uh real estate uh and we also look at valuating uh the use of this this digital real estate as well so there the taxonomy the product taxonomy and making sure that like you know we personalize the customer experience so that they are able to fetch the right items uh at the right time because of the placement becomes very important right and also when you talk about the creating the virtual fitting rooms again that requires a lot of CV OCR applications as well but uh one uh specific applications that I wanted to kind of mention were in we see that the customer experience is evolving but there may be some sort of unintended consequences associated with that as well right so we are like in a very conscious about using the voice conversational platforms and making sure that they have got multilingual translation abilities semantic sentiment extraction capabilities right so just deploying uh The Voice conversational platforms with only one language is not going to help our customers and not uh especially useful if we have like you know certain data sets that also concentrate on certain other languages as well right so to make sure that we are efficiently using our data sources and driving Innovation we need to bring in these aspects as well interesting yeah when let’s let’s take a slice of that because AI is is feeding every facet it sounds like of the Walmart business I I recently read that even on the logistics side that Walmart as a service is going to start helping retailers uh with with Logistics with CX with uh with e-commerce implementation so so fascinating when you think about the AI algorithms that you use to then drive whatever Innovation Pilots that you’re going to consider so say virtual dressing room for example what is what does that process look like and who’s on the other the other end of receiving that data so when you find these interesting patterns who says this is incredible I think that’s going to lead to a virtual showroom or whatever or drones or whatever’s next yeah so if you have a floating a box approach right so if you have product if you have business we have technology which includes data engineering and data science and also we have like you know cxux team which is like in a customer experience and user experience team so it’s a combination of different inputs that go into making decision that come across all of these different teams right and also there is a legal in governance aspect as well because the regulatory framework is evolving uh so it becomes extremely important to work really closely with the digital citizenship team and driving these applications for example when you talk about the personalization there is something that we talk about okay fine like if we want to personalize but we don’t want to hyper personalize because it leads to filter bubble which keeps reinforcing the same interests and belief systems amongst our customers right so there is some sort of a regulatory mandate as well as the governance perspective we take into consideration while making these decisions fair enough well listen it’s almost time for breaks through Jano so before we do the break we like to do what we call the quick fire round the lightning round asking you a few questions normally you asked about sci-fi but I’m going to ask about artificial intelligence this time so uh here is the lightning round

what was the first mention of artificial intelligence you can remember being exposed to in society either via TV or books but I feel cropping pattern what yeah cropping pattern yeah that’s right so the the realm of like in a data science I was not necessarily exposed to after completing my engineering I was pleased with the energy and resources Institute and as a fresh Engineering Graduate I was exposed to humongous amount of data on bryophil cropping pattern and I was asked to analyze this and that’s where I started I got the first real world exposure to analytics and started my career as a data scientist all right so it was very tactical very tactical um what technology do you think has most changed Humanity technology in the sense like you know talking about within artificial intelligence no not necessarily just generally I I believe internet surfing internet as a technology okay yeah hey Brad I’m going to add to that one just uh not that you asked me but I’m going to say ivrs what a positive impact they’ve had on Humanity yeah I’m just kidding just kidding

um name a futurist or an entrepreneur that has influenced you and why uh so I uh you’re talking about science sorry futurist and entrepreneur a scientist someone that’s uh influenced you yeah I uh definitely like uh Elon Musk right so some of us thinking um right he’s an entrepreneur but also uh not necessarily I agree to all of his viewpoints uh but especially like using artificial intelligence in terms of space Expedition and Aviation uh that I think is really interesting and with the launch of perseverance uh as well as opportunity I think there has been a lot of inundation of data and exploration of interspecial travel as well yeah interesting and the last one before break is what um science fiction story that depicts artificial intelligence is most representative of the future that you hope for um I use uh I write algorithms to live by all right by Brian Christian so it has got numerous examples of using algorithms for human decisions making so I think we have multiple interesting anecdotes from that particular work that are more applicable in the future context awesome great yeah thank you all right Brad I’m going to just take a break now this is Brian Solis and you are listening to the futurists we’ll be right back and after the break we’re going to talk about AI for good

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welcome back to the futurists I’m your co-host Brian Solis I’m here today with Brett King and our special guest Sir John Academy we’re going to bring her back on in just a second but before we do let’s turn it over to Brett King to do a deep dive into the news from the future I think we’re talking about immigration today is that right Brett absolutely

so this is obviously a contentious issue immigration but I just want to do some deep dive on this the news came out this week that um China is going to see a contraction in its population for the first time now um this is interesting because we predicted this would be 2026 when this would occur and the pandemic has sped this up obviously lockdown has been favorable to uh China’s birth rate over the last couple of years and this is a serious problem because one of the things one of the advantages the US has over China is its immigration rate and immigration is a massive stimulant for economic activity in fact there is a very strong argument to suggest that the U.S couldn’t have had the growth that it’s had over the last few years or you know the last few decades rather or Europe um without um you know positive immigration policies and I know this is an uncomfortable conversation for some in the US that said on the right but a recent research from the American Enterprise Institute shows that between 1990 and 2014 U.S economic growth would have been 15 percent lower without the benefits of immigration but if you apply that to the UK it would have been 10 20 percent lower without immigration and across the EU generally somewhere in the 20 to 30 points uh lower range and so there is a measurable impact that immigration has on society because at the heart of each economy is consumption and that’s the reason that China’s economy has been growing so successfully that consumption requires you to put more people into the market over time to grow that market Beyond its current levels you can only do that with either increasing the birth rate or with immigration and so this is a really interesting piece now if we look at the success of immigration in the US it goes well beyond just uh improving the economy um you know we see a 45 of Fortune 500 companies listed on the U.S stock exchange were founded by immigrants and the economic impact of that measures in the trillions of dollars but here’s the really interesting uh imp the issue that we we talk about when we look at climate change climate change is also going to produce a flow of immigration Mass immigration globally because of food scarcity because of weather conditions Eco refugees so we are naturally going to have that huge movement of people but at the same time we’re seeing Contracting birth rates across most countries in Western Europe now or at least slowing Italy is a um you know Contracting Japan is Contracting soon France and Germany will be in those situations in the U.S it’s not until uh the 2030s that that’s going to happen but it is also going to happen in the U.S so if you align this there’s a fair chance I think that in the 2040s immigration is going to become a a significant competitive force in economic growth it’ll be one of the only levers left because artificial intelligence will already be changing the mix of resources and employment and things like that you want real differentiation in terms of economic growth you’re going to need consumption you’re going to need immigrational birth rates and birth rates aren’t going to get you there so that’s my news from the future this week I hope but it was of of interest but I’m given the discussions we’ve seen on um you know China’s population uh stall growth stall there and the debate that goes on continues in places like the United States and the UK on immigration I thought that was a useful conversation I Do cover it off in the rise of technosocialism but uh sujana Let’s uh let’s jump into a bit of um you know AI for good and you do work with the United Nations in some respect too can you talk a little bit about that yeah uh definitely Brett so United Nations Association uh San Francisco chapter is uh I’m associated with that I serve on the board uh we do a lot of activities right but United Nations in general has been focusing on uh Global sustainable development goals uh at the heart of This Global sustainable goal development uh there’s a urgent call for Action to achieve 17 sustainable development goals which occur uh in partnership with developing and developing nations and focuses on elevation of poverty deprivation while also helping mitigate climate crisis uh increasing biodiversity preserving our forests and conserving our oceans while also supporting economic growth right so this led to emergence it’s a long shopping list of things it’s big ticket stuff too yeah and this has led to the emergence of U.N Global pulse policy because it’s understood that data happens to be the foundation in terms of setting the targets and achieving that right so this leads into the question around AI as a as a you know future thinker in this space and um you know you must think about the application of AI for doing broader good in society you know where where do you see AI really being um you know of Leverage in respect to solving some of these bigger problems that we’re going to have to deal with over the next 20 to 30 years yeah so uh there is a lot of usage of EI and AI is evolving and we are Outsourcing a lot of decision making ability to AI uh however in terms of the social good space uh it’s just like an Indonesian stage primarily because we were not having clean data sources to train the AI models that were publicly available but un has started consciously focusing on developing these data sets for public consumption and usage right even in the United States a lot of these agencies are putting together certain data sources that are available on the websites for example ocean protection Council and California natural resources agency so I believe a lot of these data sets which are publicly available would lead to streamlining of AI applications and crowdsourcing of these applications and people analyzing that especially like when I see some of the applications happen to be in mitigating the social manners like human trafficking uh also I see a lot of applications of AI in the agriculture space yeah well money laundering you know a lot of these areas will be able to use algorithms and they’ll be far more effective than we are you know even just uh what they’ve done with shinsen the smart cities in terms of policing on the roads and and order you know doing using Ai and image recognition for to issue tickets like speeding tickets or if someone’s not wearing a seat belt you just get a text message as a fine instead of sending out police force to do that and it’s far less risky and low impact so there’s a whole lot of range of you know social you know improvements that that could come with uh some of these tags but it could also be invasive right yeah that’s true and that’s why like there’s going to be emergence of rules uh that would focus a lot on like regulating the applications of AI uh ethical AI is a space that’s going to grow significantly as well as cyber security space because the data regulatory framework is evolving with Neo data privacy protection gdpr and and so yeah but you know this is the problem with regulation it tends to be backward looking because it tends to respond to risk but the problem with AI is we have to build Ethics in now what’s the industry doing for that yeah many people think that like an ethical AI is focusing on how do we use the application to make it to bring in uh better equity in terms of the up usage of these algorithms right but uh it goes far beyond that looking at like and how do you do the future engineering to all the stages of like building the model validating that and including creating the data sets uh that are more inclusive right so we have seen many of these racist comments unleash on social media because the algorithms were trained on these kind of bias data sets right so uh I believe the first Focus area for the industry is going to be around creating uh inclusive and representative data sets to train these algorithms on yeah fair enough you know I’d love to follow up yeah Brad on I work with uh colleague her name is Paula Goldman here at Salesforce who leads uh our AI ethics practice and Shout out we were we were working on a program today that literally is putting a face to AI so there’s companies uh out there that are essentially uh representing digital humans let’s just say and the the ethics in terms of AI algorithms but also in terms of the visualization then of of that AI I I just love to hear your thoughts on what to keep in mind as we say like what in the examples Brett shared uh you know we’re going to see since you’re working in CX for example we’re going to see the application of a visualized AI in terms of customer service or clientele in terms of Shopper Assistance or shopping assistance and would love to hear how you might be thinking about sort of this next level of AI ethics and then I have a question for you afterwards about Quantum yeah absolutely so in terms of like you know uh AI uh ethics right so we look at especially in the retail sector right so there is uh there are a lot of applications but if you look at overall the supply chain right making them more eco-friendly uh looking at making them more inclusive uh is one of the areas right so also we need to look at like an ethical AI it is not uh come outside of like in a governance as well right so governance and ethical AI should go hand in hand uh as Brett mentioned there are like in a lot of these backward looking policies around regulations that are coming in but also as we start looking at giving consent uh and mandating consent and as we are moving to the Cookie list world all right so the way you profile the customers the way you personalize everything gets uh the decision making ability gets shifted to the consumers right they can give the consent or they can even they even have the right to kind of delete their overall existence from the data set so I believe if uh there is going to be less power in terms of how data scientists could use the algorithms to build these uh considering like a consumers are going to weigh in a lot going forward you know so let’s bridge that back into the the work that you’ve done around social good and you you live in uh in Northern California uh we’ve had our fair share of atmospheric rivers in the last uh last few weeks uh that we’ve also had devastating wildfires there’s like a weatherman term atmospheric Rivers that’s pretty interesting it is uh we’re no longer the futurists now we’re the weather but uh you know earlier when we talked about applying AI uh pattern recognition to drive Innovation at Walmart and that you have someone on the other end to to to receive that information think about it and execute so do you feel like there are things that need to be done in order to raise the I guess raise the flag around the AI work being done to save let’s look at prediction models around not just climate change but the actual impact of things that are going to drive what Brett was talking about in terms of immigration uh what like eco-immigration for example what do we need to do as a society to get that information into the hands of people who are going to take it seriously and act upon it yeah so uh this requires a lot of mobilization and awareness generation right Brian so there are multiple stakeholders uh even like you know for example if you look at the non-profit organization right so they are doing a lot of work uh let’s say take the example of global emancipation Network right so they are using computer vision algorithms to detect uh what are the potential sources for human trafficking and providing that to the law enforcement Authority but law enforcement authorities would have like a limited bandwidth to kind of attend to all of that right so it becomes extremely important for us to start looking at considering these stakeholders and generating that awareness and mobilizing them uh and taking them along but also it requires a lot of corporate and public-private partnership as well right so computational efficiencies computational power are extremely important as we start training these algorithms if especially if these algorithms are available from the UN field agencies humongous data sets so it becomes important and for corporates to partner with non-profit organizations to drive this kind of a momentum and awareness all along yeah thank you for that I think Brad I know that uh we’re going to come to the top of the hour here but maybe um I’m interested in the quantum question too you you I said earlier but you know what what um you know if we’re getting futuristic where does Quantum fit into AI because you know I I don’t hear a lot of AI practitioners talking about you know applications of quantum as yet but it’s got to be coming right yeah and and just to put the little uh the icing on that one uh John has that when I was at nascom in India as covet was uh breaking out I I was there to explore the role of quantum in in tackling some of these bigger issues like climate change and I would love to hear sort of where we are in that that evolution in in AI of uh how soon can quantum driven AI or AI driven Quantum tackle these scenarios and when and what’s going to be different about it yeah let’s take an example of like in a deforestation right so we have uh we have satellite images all right and uh we have a lot of information that we could use but also we need like a geosensing information all right so we cannot necessarily make a lot of predictions just based on satellite images so it requires like an Internet of Things using Quantum information uh coming from multiple sources and driving uh these kind of predictions right so I think it’s going to be uh focusing on looking at multi-dimensional data sets and looking at how do we integrate that and putting those synergies right so uh I see that it the evolution has started we have started looking at like you know using Quantum to try a lot of these decisions but there’s still a long way to go uh because of the unintered consequences associated with AI we don’t know what kind of a consequences whether positive or negative it would bring all right so we need to be mindful in terms of how do we model it this journey but you know I I this this frustrates me this conversation right you know we have the the Stephen Hawking Elon Musk AI Hawks right and then we have the others the pro pro AI World um you know what always frustrates me about this is we spend so much time debating whether AI will be good or bad right when we should be just simply preparing for the introduction of AI into society we should be thinking about the regulations that um you know restrict AI or make it um you know positive and ethical for society and we should be implementing you know those guidelines on a global basis to ensure that it’s a positive future rather than just let’s just hope for the best hopefully it’s going to be good and not bad right you know it’s like and but we don’t even know if conceptually gonna happen right like I like you know I don’t look you look at chat GPT now it’s not taking anybody’s job right this is the conversation you hear right and it frustrates me because we should be doing more planning and and more thinking about that so here’s what I want you to take us on a journey with shujanos take us out 30 or 50 years what is the world going to be look like um from an AI perspective and you can be dystopian or utopian in that view but um you know what’s that potential world look like in 30 years with AI infused in society yeah so I do not believe like you know we need to debate a lot in terms of positive or negative consequences Iago is going to be here it’s going to be War it’s going to stay all right so we need to just Embrace uh for this future uh with AI I believe like you know AI is going to find huge applications and we are going to work on looking at creating certain ecosystems uh especially like in an inter-spatial travel as well as Aviation and creating ecosystems to live on other planets is going to be something that’s going to evolve uh there’s a huge Focus around that and also uh in terms of improving longevity for human beings right and also to mitigate certain crisis around like an eliminating world hunger we would have applications of AI that’s going to help us achieve all of these consequences I just saw some news today I don’t know whether you guys saw this it’s on um futurism.com oh it’s actually on the bite which is their uh newsletter Mr Beast you know the number one world’s number one YouTuber hopeful that science will let him live several hundred years and I was like well that’s like isn’t that isn’t that what all futurists are hoping for and we are already seeing the longability uh increasing there are stats that indicating that and with Advanced AI uh helping with improve improving the healthcare facilities I don’t think it’s going to be very difficult to reach that state well you’re not you’re not the only one we had Aubrey degree on a few weeks ago um I don’t know if you got the chance to listen to that episode yet Brian but he was fabulous and I learned a ton about longevity stuff and some assumptions I had that were wrong actually but uh um so so longevity is going to be there um but how do you think our um our children’s generation will think of AI in the future so I believe there is going to be less distinction between like an augmented reality which as compared to the the reality that and they would be using a lot of AI in terms of like and how because they are already digitally native right so in terms of how they perceive uh the environment and like you know they would uh use a lot of AI in the educational system as well so I think it has got pros and cons but it’s important for us as parents to start embracing uh that this is how the evolution would happen and like and get our children ready for this particular future I I wonder I wonder if it’ll be just as simple as uh for example our children are already familiar with augmented reality in the sense that they’re already applying filters to many of the uh the images and and videos that they use in AI will just like chat EPT just you know the number one adopter of that is our already students uh doing uh doing their homework so well um before we uh before we wrap up why don’t you help uh bring us home let’s talk about uh the future of AI at Walmart what you’re excited about uh what whatever you can speak about in terms of what’s next uh what what can we think about in terms of the future of AI at Walmart and then just retail at Large yeah across retail I see a lot of applications of AI especially when you talk about the customer experience with chart GPT a lot of things are going to evolve all right and the content creating as well as the ad business are going to transform tremendously because like you know it just it’s going to impact like and how we search how we personalize how the our Revenue gets generated all right uh also we need to look at like in a drone delivery and so there’s going to be a lot of usage of AI in terms of already like in a Walmart and various other retailers are starting uh to use drone deliveries but I believe this is just going to increase and it’s not going to be only domestically but also internationally and we are looking at uh interplanetary travel as well at some point of time in terms of delivery of goods as we start looking at inhabiting certain ecosystems in different planets wow

that’s pretty uh out there thank you very much Regina I had to put in the uh the clap track because the clap track because that was pretty that was fun so but um thank you very much for joining us how do people find out about the stuff you’re doing at Walmart or stay in touch with you personally yeah they can reach out to me on LinkedIn um and uh you know I would love to have those conversations with them great fantastic all right all the best and thanks for coming on the futurists uh this week um Brian thanks for joining me as co-host again of course always always a pleasure so thank you fantastic to have to have you back on soon um for for those of you listening uh obviously the show is making tremendous project progress we just passed out 150 000th download which is in record time so we are um you know we may have maintained our spot as the number one futurist show futurist Focus show so that’s fantastic thank you for the support if uh if you can please tweet us out you know and post to the show um you know uh share share uh some of the episodes with your friends if you can leave us a review any of those sort of things really help um you know obviously and if you haven’t subscribed hit that subscribe Button as the YouTubers say all right hit that subscribe button and and join us every week Smash It Up absolutely smash the smash this yeah um but uh we have a little tagline at the end of the show I don’t know if you remember it Brian but uh thanks for joining us but we’ll see you on the futurists in fact we’ll see you in the future

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