We learn that there are numerous AI content generators on the web currently, but very few successful long-form AI writers. Pandey explains how generating well-researched long-form content that is both authentic and natural is a much more difficult problem to solve than simply generating short snippets of text.
However, LongShot’s new AI writing tool is attempting to take on the challenge. It can generate thousands of words of written content with the click of a button on any topic or keyword desired, saving marketers and long-form content writers tons of time.
Humans then look over the results and pick out the best bits and pieces, do some basic editing, and congratulations! You have a fully written blog post or report in a fraction of the time that it typically takes to create one.
LongShot.ai is the AI platform to research & generate long form content. Create nuanced, authentic, human-like content with a few clicks.
This is Ankur’s second proper startup and his background has been almost a decade in Data science. Eventually, he wanted to leverage his experience to create amazing software products using the ever evolving field of AI, ML.show more
OuLongShot.ai team consists of data science, dev, & product folks with wide startup experience. The same team previously created cutting edge products like https://UnFound.ai.
The idea Of LongShot started out as an offshoot of a problem my team wanted to solve for a client. There are now new tools which focus on small content generation, but we soon realized that systematically generating authentic long marketing content remains under-served & unsystematic (and technically challenging)!
With the help of our early users, beta testers – we hope we created a system which can help marketers up their long form content game . And hence, LongShot 🙂show less
DISCLAIMER: Below is an AI generated transcript. There could be a few typos but it should be at least 90% accurate. Watch video or listen to the podcast for the full experience!
Ankur Pandey 0:00
As we speak, at least half our days goes into, you know, how do we reach our characters, right? In some sense sales and marketing and PR and things like that.
Alexander Ferguson 0:14
Welcome to UpTech Report. This is our apply tech series UpTech Report is sponsored by TeraLeap. Learn how to leverage the power of video at teraleap.io. Today, I’m joined by my guest, Ankur Pandey, who’s based in Mumbai, India, is the co founder at longshot.ai. Welcome Ankur, good to have you on.
Ankur Pandey 0:33
Thanks, Alex, it’s good, it’s good to be.
Alexander Ferguson 0:36
Now longshot is an AI system for researching and generating long form content for those content marketers others out there that are trying to generate content you’ve ever been hearing about this buzz of AI can write stuff for you. Now, specifically, long show you guys are focused on the long form content using that to help research and find content. So to state first off just the problem that you see and have been set up to solve.
Ankur Pandey 1:01
Yeah, sure. So the problem really is that, you know, can AI help marketers and content writers and any writers in general, to help them write content, like, you know, like, you know, and so, and right, cut into scale, right? No Man’s content, right? Human like content. So this is the problem we set out to solve. And we focus on long form, because long form content writing is has like multitudes of more challenges than compared to let’s say, short snippets, short paragraphs, you have to be coherent, and you have to be solid, you know, like, you have to be authentic, and so on and so forth.
Alexander Ferguson 1:37
Are you definitely decided to go after the harder problem? Do you just stay today? Like, hey, yeah, sure. Let’s go after the harder one, bigger one. But I’m intrigued to hear about your journey, because that’s one of the reasons why I’m excited to be able to chat with you today. take me take me back. I mean, you’ve been this isn’t the first venture you’ve actually started around AI. Why did you get into all this?
Ankur Pandey 1:59
Yeah, so I mean, it’s been a sort of gradual thing, like, you know, I’ll probably soap I had some on and off since at startups since, like, Come sick five or six years, or slightly more. My background is I’m a technical person at heart, like my background has been in engineering, maths and computer science, I dropped out of a Ph. D. program, about a decade back. And since then, I have worked, as you know, data science machine learning positions in various places, and consulted tons of companies, startups, and, you know, like, bigger, smaller organizations have multitudes of projects all across the sphere of data science. So this is something which I’m passionate about as a professional now, like, you know, like, when I sort of few years back, I realized that you know, how data science can be leveraged to various things. So for example, I had the extent that logistic startup, which was short lived, but then the most significant thing, which I started out, which was about three and a half years back was unfound. Now unfound, the idea of unfound was that, can we use AI and machine learning to solve the misinformation problem? To some extent, we like when I say we, I’m actually also referring to by me, and my team is specifically the founding team, which includes my wife, co founder, and she so so, you know, like, the thing is that we, we both have technical persons, actually. But we also have side interest, and, you know, like, the societal packs and stuff like that, right. So, it always was at the back of head that what are the challenging stuff, right around, which can be dealt with. So unfound was, you know, unfound, did tackle that. It tried to sort of use AI, etc. To solve the misinformation problem can then like, so it had to our thoughts. One was that can the news be consumed in a way that when somebody is sort of searching for a particular piece of news, can can they get another like, you know, another perspective automatically, right, so this is, you know, echo chambers or misinformation? The only one side news a big problem, right? And this has, you know, impacts across every year, we had business version of it, like, you know, because we were a for profit startup, right. So, then we, you know, like, typically business pivot when with this, even if the idea is great, but there’s less of market traction. So maybe it’s there too early or, you know, whatever, right. So, because of that we had that market push and we had to pivot a bit to, to to solve the same problem or a similar problem for businesses. So you know, that was unfound b2b version
Alexander Ferguson 4:29
is basically your you and your wife, co founders I think that’s beautiful as a family business in some ways, and it comes to startup our technical people you see the technology you love it you enjoy it, and you want to solve a big problem i It sounds like you have this drive to to solve that big issue and you see misinformation or which is a big thing. A lot of people are thinking about misinformation, like how can I trust what I see online, everyone’s thinking, and so you set out to solve it and I feel like what When we chatted last year, you clearly stated the problem there is people aren’t willing to pay for it. They’re not willing to pay for it. So you pivot unfound to be a b2b solution described to me how that what that pivot look like.
Ankur Pandey 5:16
So, so like, the same thing, attracted like the same preposition wherein one can detect the other side of the story also caught attention of few like, you know, folks in who was, let’s say, in the PR departments, or the marketing departments or few businesses, and they said, you know, what, like, I’m good, can you make a version wherein I can detect what my consumers are saying and different aspects of it, etc. So we said, okay, you know, we can we can repurpose the same technology. And there are some times we can go deeper enough to say that sometimes like rumors which are floating around and which humans are high probability to go bigger things like that, right. So, so misinformation is not just one thing, it is false news, it is sort of, you know, news, which is correct, but not, not like the whole story, right. So, we tried to solve all this gamut of problems. We did actually succeed, like, you know, we have, you know, big clients like, you know, we work with government on national level with BBC, Google News. Even with Maharashtra, Maharashtra is a state in India. And we work with with a cybercrime department, we work with names like TCS, and DHL and Unilever, etc. So it was a, it was a good business. The reason of pivot was not at that point, the loss of business, the reason was that we realized that we were not like, you know, when you, you know, work with government organizations, or when you work with like, extremely big size companies, you have to eat, you are going to sell them x, but you have to also sort of offer them, you know, like 10 other things. And he said, you know, what, like, oh, wait, this mail. So it’s like, we have it going into that circular loop, where the original idea, the original thesis was probably being clouded by many other things, many others have, you know, like, fancy stuff. And, you know, can you make an app? Like, can you make Android app using all sorts of software, you know, you can
Alexander Ferguson 7:02
basically, it was pulling you away from your drive to solve this bigger problem. They’re like, can you build this? Can you build that and you’re like, Ah, I don’t want to do that.
Ankur Pandey 7:13
So it was getting what we would call a managed service project, right? Now, we so we said, you know, like, what we really enjoy is, you know, like, we want to maximize our reach, really, you know, we don’t want to solve the problem for only four or five organizations, which can kind of give us good money, but then this is not going to reach out so many folks, or it might take too long, like maybe you know what we had in mind. So at that time, we were kind of experiment, experiment, this technology is like GPT, three, and others. So we thought that you know, this might be the next thing we want to be very excited about. So here we go, you know, so Wow, that’s
Alexander Ferguson 7:52
what I’m intrigued in with now, okay, you make this pivot, you go to Llarowe shot, and you’re like, you’re using this AI technology to help write content, not misinformation. This is not using AI to write content isn’t new. But by new, I mean, it is new, it is something that many people are trying to solve, but there are multiple solutions out there, your angle, you’ve already mentioned, is one of it being long form, hence the name long shot, long form content, the good job trying to go after the more difficult challenge of it, but also using what you built in unfound. Right, the ability to know what is what we’re writing? Correct? Is it factual?
Ankur Pandey 8:37
Absolutely. So you are you You completely sort of said, you know, what we had all the while never mind. So, you know, like, the point is that, so writing, so look at what is going on when people right, and when I say Right, like step aside from a market has had, so marketers are supposed to be like our first audience, because they are the folks who would use us day in and day out. But essentially, you know, college students would try it or, you know, and pretty much like fall big. There’ll be story writers, like one of our few of our other, you know, like users are using longshot to create, you know, like, some kind of scripts, right, like draft scripts. So for some projects related to, you know, movies or short films, tech stuff like that, right. So, so now the point is that it’s so pervasive, but the problem with the current research, like which which is, which has been amazing, is that there is a problem, like, it is super human like, but it is not coherent, you have to tame it really, you know, like, it’s like, it’s, you can pretty much ask it to do say anything and he can kind of control things. Now, you know, like, the point is that we believe that so in some limited sense, it is good because you might get creative ideas, but there is a limit to it, right? Like the creative ideas would not mean let’s say a blog writer, would not be Want in you know, sort of in exchange of creativity, some completely garbage or completely sort of inauthentic piece of information going in. Right. So, so even in the current version of a longshot like the current version, which is being used by folks, right, so we have an integrated factcheck. And as you said, right, like this is coming from our background in unfound, which wherein we used to sort of, you know, we had this technology, which would kind of, you know, do fact check on the fly. So we have already integrated, and our, currently our, most of what we are emphasizing is, like currently, let’s say in terms of research, and the technology and product roadmap, the most important focus is, how can I make sure that the content is as authentic and as factually correct as possible? I mean, with due respect to lots of our competitors, and you know, like, people who are trying to use all these new AI, content technologies, this has been either not addressed or, you know, in some sense, solved in a very roundabout way. It’s like, oh, you’re not like, you just replace the thing, this thing by the correct thing, you know, like, that owner says, But, but there’s a limit to it, right? You can maybe, you know, let’s say, it would say, Elon Musk, the founder of Amazon, which, of course, is incorrect and famous enough to be known that it’s incorrect, anybody can kind of detect it, but what about subtle things? Right. So, which is like, you know, even if somebody is was extremely domain expert, it’s easy for them to miss it. So, so that’s how long short comes in. Today, if you, for example, just to complete this chain of thought, even let’s say if you if you want to write the GPT three, which is the most famous, for example, language technology we have, it will not give you anything after 2019. Right. Now, the problem is that, you know, let’s say if you want to write something about COVID vaccines, right? The point is that it will conjure up something completely on the fly, and you cannot rely on right. So the point, you know, you will soon realize that there are limitations to it. We don’t want to do that, like we want to, we want to enhance its limits. I mean, the great folks at you know, open AI and other organizations have done the big job, but then we are here to sort of take that forward and use our technology enhancements and make it full, make it complete, make it usable, really. So that’s what we’re doing.
Alexander Ferguson 12:21
What do you see as the most common use cases for AI enhanced writing?
Ankur Pandey 12:29
So the most, so as I said, like, you know, the most urgent, rather most from immediate use cases are folks who are in the business of content writing on a day to day basis, and they happen to be like, folks who would write some kind of marketing content, let’s say a blog post about a product blog review post, or, you know, some kind of reports, internal external reports, memos, you know, like the advertisements, you know, some kind of briefs. So, it typically, you know, name inauguration, small or big, right? If you look at it, probably hundreds of content is written law of this nature almost every week, right? It can be every day, right? So, so So in that sense, it’s like, pretty, you know, the this, you asked me, like, what is the use case? I would say, it’s very horizontal, just as horizontal as one can get really, you know, so I mean, I’m not even talking about. And so currently, the product is in English. So even that is super horizontal, but if you reach to other types of languages, and so I mean, even more. So, you know, so that’s,
Alexander Ferguson 13:34
what’s the current technical challenges right now have AI in languages? Is it? Is it pretty easy to implement in multiple languages?
Ankur Pandey 13:43
So I mean, that it’s yes, and no, I would say like, slightly going, I mean, I would refrain from going too technical and this particular combination, but the thing is that, if you again, like you know, the answer would be similar to when I talk about, like, the challenges with short form versus long form. So if you are writing, let’s say, a couple of lines, you know, you know, small paragraph, then it’s easy sort of translate or transport between various languages to current language technologies that allow you of course, I would say that English remains the most sort of, you know, the best trained models still perform well on English and so, therefore, that remains the best you know, sort of, I would say output wise, but then as you go longer right, it will keep on deteriorating will keep on going giving you garbage. So, the challenges are in some sense mirroring what the intellect the language and is pretty much mirroring what we see in authenticity.
Alexander Ferguson 14:38
The use cases coming back to that for a second of Sure, you say horizontal of anything, you need to write a memo, a recap a new blog posts, etc. The practical use case is you would probably like before they use long shot or another type of AI writing solution. They’re writing it manually. So in this case, they’re using it to write really the first draft. Do you see? Do you see people just publishing whatever comes out of longshot.
Ankur Pandey 15:10
So it’s Yeah, I mean, look, we are currently for example, in middle of. So, I would, I will not say that people are doing 100% longshot published content, like that’s not that what they’re publishing, but we have seen about something between 60 to 7080, or 90 percentage of the content generated, being used, like, you know, let’s say, it’s a two to 3000 words blog post, and one can say 1500 or so words, were actually AI. So that does happen. But by the way, like, you know, I’ll take sort of point here, I mean, the thing is that in when we like, you know, one, one way we attempted to solve the long form content problem was not just that, you know, you can just go to the editor and keep on writing back things. For example, we also, you know, enable a user to research for example, you, you can, let’s say you are writing something, and then you are kind of stuck that what, which direction should I go in, so, you can sort of, you know, research stuff, and you can then give it some pointers, you maybe not even be aware of, you know, lots of things about this particular topic you are writing, or you are run out of idea, right, so, so this is how this is also kind of integrated in the product. So, you can think of it as a, a, so, what you would have done what, let’s say, folks like you, or let’s say a marketer would have done in various settings, and in various iterations across maybe hours or days, this is super compressed. So, we are not trying to eliminate, like, it’s not like he, you go and click and, and let’s say this, everything’s written. So that’s not how it’s supposed to work. But you know, it’s like, you will probably think of something, then read up something and then write it off. So this is our typical process looks like, right? So we are trying to solve super, you know, speed up, and speed up to an extent that we have seen improvements up to, let’s say, 10x or more, right? I mean, in terms of the productivity, where that
Alexander Ferguson 17:05
somebody wants to start writing something, just just briefly describe the process and the tech is, provide a topic and then like, Where, where is it getting the information and the ideas to write it?
Ankur Pandey 17:19
Okay, so, again, like the product can be used in various phases slightly, you know, sort of flexible enough that, you know, like you, you want just one thing, so you can just see one, just one introduction paragraph, so you can kind of generate only that, but I would say, a more in depth use cases is the following. So, one goes to the product, and when one searches for topic, and then one create some kind of content brief based on the suggestion they get. So, in this particular step, there’s no AI yet, like, or maybe, you know, there’s some kind of LP technologies.
Alexander Ferguson 17:53
Someone is writing the brief of what they’re wanting to create.
Ankur Pandey 17:57
Yeah. So I would say that somebody would give a seed word or seed phrase, let’s say, you want to write about Bitcoin, right? I mean, so you would probably say, Bitcoin or the price of Bitcoin or whatever. So, you will get ideas like what is trending? And what are the, you know, questions, people are asking? What are the keywords you should use? So how do we know this we have, we have maybe, you know, scrape data from top results in Google and other search engines and things like that, right. So you will create a content piece. And once you create, so content brief, when I say you create, basically you select it, so you are just inputting the, the first sort of input topic, and then you get tons of suggestions. And these suggestions can be picked, and sort of selected, you can write your own suggestions if you want. But if you don’t like you, you have enough suggestions to create some kind of skeleton off topic. So let it typically look like that. Let’s say Bitcoin is a topic you want to sort of write something on, it’ll give you that, let’s say, I know, like, what is his I mean, I’m just conjuring things up as I’m, you know, speaking, so let’s say, you know, some kind of new crypto exchanges come up. So, which is getting hot. So this is the session that the platform will give you, I’ll give you the kind of keywords you should use maybe prominence name, names of crypto professionals or, or the names of startups or names, technologies, etc, etc. So all this will create a content content brief for the AI to start with. So this content brief is then so like, once you are kind of okay with it, then you sort of when you kind of like once you maybe spend couple of minutes doing this, and the content after the content beat AI has enough context, right? It has enough content text to start writing from. So it will first create an outline, a headline and then a like an outline, maybe however long it typically 1020 13 sort of sub steps so to speak in a long form content, right? And then what you do is then then it’ll keep on creating ills, you know, keep on filling this outline, so to speak. So imagine that you now have a big blog post and you have like, let’s say the headline and you have a skeleton. So what are the topics you want to cover, right, which has been derived from the research. And when you start, then it will keep on filling in the introduction of each of these sub headlines or the outlines, right? It will keep on doing that you can keep on nudging it, you can say, okay, not like this not good. Maybe write a couple of extra from you. We’ll start from there. So this is a big iterative, but it’s like saying that you know, you it’s like, you have to give it some certain directions here and there, just to guide where you want it to be. And
Alexander Ferguson 20:35
yeah, so it’s more like a writing assistant. So you’re, you’re telling you kind of I kind of want something as you well, okay, that’s all right. Let’s change this. Okay. You write some more and, and it’s, it’s, it’s kind of working with this assistant? Oh,
Ankur Pandey 20:49
so it’s actually not like the one of the challenges founder is? How to describe it. Because if I say AI assistant, I think it’s more than assistant to be very honest. But if I say let’s say AI, which writes everything, right, so this is, of course, not what we even intend to do. So the point is that maybe there’s something which will come in
Alexander Ferguson 21:07
Ankur Pandey 21:10
Somewhere in between, I will say, it’s because assistant good sort of, you know, like, what, like, when I say this word resistant, right? People have in mind that, you know, okay, it is giving me some suggestions, but these actually writing it is actually writing meaty enough paragraph and meaty enough things, right. So for you to consume.
Alexander Ferguson 21:28
Now you, as a founder, co founder, you and your wife, you’re running this company, as a technical person, I can see you get excited about the problem about solving it. What are some of the, the push backs, and some of the difficulty so far faced with trying to bring AI writing assistance or AI writing tools are abilities to market?
Ankur Pandey 21:52
So this is a great point. And I think, you know, like this is, I mean, to be very honest, that even if we are technical person, I mean, as we speak, at least half our days goes into, you know, how do we reach our characters, right? Or in something sales and marketing and PR and things like that? Right. So, so the point is that, so, to answer this question, I’ll like, maybe give you a 32nd sort of recap of how, so if you if you look at like, today’s, you know, October 2020, they we had zero AI systems, if you want to call them since they’ll be at zero, right? Like, long form short, this, pretty much none, at least not what, or even if there were, they’re very old school ish, right, then not leveraging the new MLG s gp three and stuff like that, right. So but today, we have, we have many, and like, I would say about 90 to 95% are short formation. And, and then others, like, you know, like long shot, are trying to try to solve some difficult aspects. Like, for example, we have big long form, some others have some other sort of versions, which are arguably a bit more difficult, right. So this is where we are now. But and this is exciting, like, you know, I get tons of messages calls or you know, like chat messages every other day. And people asking questions, the market establishment, I’ve been also, you know, you won’t believe that, you know, I have had pushback from Pro writers, they say, Oh, you’re stealing our jobs or this unethical? And, I mean, the point is that, you know, so I mean, due respect to them, I think these are very legit question and this will happen. So every revolutionary technologies will bring about such a, you know, Alexa for disruption, so to speak, right? So, the thing is that now, like, in one year, it seems to us that so many things have changed, because today, marketers or like, you know, content writers, especially digital content writers are aware of such existence of systems, right. So, there’s no, actually, I would say, there’s a poor pushback of good design. So good guy, and we’re in that you have to country Oh, this is this is long, short, beta or some x y Zed is better. It’s so they are accepting us, right. So they are not saying Oh, What is this nonsense? So, you know, like they had, there are two kinds of pushback, we sort of face when he started out. One was the questions which, which probably a bit which would I would call a bit Luddite, you know, and others would be others would be, you know, did you know like, others will be on the sort that some kind of disillusionment, disillusionment with the technology, because in the previous years, there had been attempts, like, again, like, you know, all these previous AI, sort of approaches have also had their own sort of, you know, had their sort of ways of attempts of solving such problems, but they were not really up to the mark. Right. So few folks who were sort of, I would say, ahead of the curve in terms of experimentation with the products had that you know, background wherein they say, Oh, we have tried it all alone, and none of this works, right. But then they were amazed. Okay, you know, this is not interesting. This is real, right? This is not that this is this, not just rephrasing things. There’s not just kind of, you know, sort of jumbling. It’s not about a play. It’s like really kind of telling me it’s like writing like as human good. So So there had been a After a few months of sort of, you know, in some sense, pushback from our prospective user, we have now a good kind of pushback, wherein we will say, Oh, are you better? Or are they better? Are you? Or are you more so for example, or like, a lot of people are excited by our background, also, as you know, creators one form, they said, Oh, you know, what, like, I have been facing this problem. And guys, maybe you, so your product has this fact check option, maybe it’s a bit, it can be developed a bit more, but we understand that you have that background. So we are going to stick with you, you know, so there have been that that kind of, you know, sort of comparisons and competitions. And I think so, of course, you know, I would be lying, if I said that I’m I never get, you know, sort of some kind of, you know, I wouldn’t say worry, but some kind of, often a little bit anxiety here and there. Because I would say every sort of startup purpose, or every founder would, but I think, you know, like, when I sort of sit back at night, or in the weekends, I say, oh, you know, like, this is great, because it’s like, what, what was expecting really, you know, who was expecting it? I’m the only person in the world who is going to get this idea and who’s No, of course not right. So, and so, therefore, I kind of welcome these competitions, and the others approach is also right. So, and this is this is also telling us that this is this market is adopting us real fast, and much more than we had anticipated before. And this is also some of the proof is also in the numbers, right, like the kind of traction we have been getting. And we have to kind of, so like, we are not from the marketing background, like, at least as founders, we have a lot of, like, you know, we have a lot of partners and moves have helped us. So therefore, that will be an increased push of for the product in coming months. You know, that’s, that’s the current roadmap.
Alexander Ferguson 26:46
Okay, you’ve shared a lot in that whole section, you’re like on a train, just like being able to share, share, share, and kind of break it down? Like, is there one being as a founder, you can get overwhelmed potentially. And it can be it can be exhausting, but you, you see that the whole industry is moving forward, and you’re able to ride the wave, sure. But you’re able to be part of this journey, or be part of this movement. And I appreciate them to push back. So far I’ve been here, because the Luddites, those who are afraid of the change, and they’re like they’re taking my job. But if anything, I think people are going to realize that it’s here to help us do our job better. It’s not us. But also the other pieces are which tool is best for me and what I need. Those are kind of the two potential challenges of how do people are actually rather the second one you said was people who have tried it, but it was not up to snuff yet. But you’re saying it is you’re saying the technology is highly developed? Would you say GPT? Three has been the catalyst to making that happen?
Ankur Pandey 27:59
Yeah, so I would say yes, definitely. So So I mean, even if we talk about GPT three, so first of all, like, as a as a product, God three is some technology we use, but it is probably now at least today, it is among many other type of energy technologies to use, right. So GPT remains the most famous ones. One, it has the best PR, etc. And it’s great, of course, but it is not the only one. We there are others. And we have also kind of in some sense, kind of sort of improved the budgets for energy with our own efforts, and maybe others have. So yes, it has been a catalyst. But, you know, like, so, which, so therefore, I’m not saying that consumers use us or other products of the similar nature. They do not have company they do, but they are That’s what I said, right? Like, they still are now, at least today, beyond the possible limit. It’s like, it’s almost like oh, you you actually hire a content writer. And when they publish the first draft and say, oh, you know, like, this is the stone can be proved. And this can be you know, me so you know, like, so it’s it’s probably in something on par with such approach. So it’s they are not going to accept the first version of course, but they cannot just you know, they cannot just discredit oh this garbage right? This they’re not gonna do
Alexander Ferguson 29:19
you bring an analogy in my head, I’m wondering is is these AI tools, it’s not a they’re all the same, but rather it’s almost like baking where everyone’s using somewhat of the same ingredients but maybe different ingredient here different ingredients there and it’ll taste the flavor will be different the how the outcome and the look of it will be different. And so there’s multiple ways to make make a cake, but that cake will not be the same as another one. Is that a bad analogy?
Ankur Pandey 29:49
i I see today. So it was it had not been that up like six months that but today it is it is probably appropriate and it is likely to be More and more appropriate as we go along. So in you know, I would say that in another year, it will be me like, you know, some, okay, you know what, let’s take some background things will be same. But it’s not like every theme. So it’s not like everything is a GPT wrapper. And especially tools like us, we cannot just be sitting on dignity and developing a UI No. So the kind of stuff we need to do or we plan to do will require more things and some of it we have succeeded some of it we are developing so
Alexander Ferguson 30:28
well anchor I appreciate you sharing the the journey that you’ve been on you and your wife, you’re excited to to solve a big problem using technology, starting with unfound. But now with long shots, and it sounds like you definitely see the potential in the future where this technology is going the problem that it truly can solve, it’s only going to become more real. For those that want to learn more, you can head over to longshot.ai Looks like you’re gonna be able to get a free trial. You guys are like, seem to make it very easy to just get in and try it out. Thank you so much, Ankur for your time. Good to have you on.
Ankur Pandey 31:04
Same here Alex, it was it was a pleasure.
Alexander Ferguson 31:08
Thank you all and see you on the next episode of UpTech Report. Have you seen a company using AI machine learning or other technology to transform the way we live, work and do business? Go to UpTech report.com and let us know