EP 72: How Startups Can Adapt to AI Innovation

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How can startups use AI and what does it mean for everyone else? Right, there's AI just about everywhere you turn and look right now. So that is one of the things that we're going to be talking about today on Everyday AI. My name is Jordan Wilson, I'm your host and as a reminder, this is for you, this show, Everyday AI. It is where we can learn about AI together and how we can leverage it in our daily lives. So if you're joining us on the live stream, welcome. If you're joining us on the podcast, make sure to check the show notes. Come join us on the live stream as well. Also make sure to check out our daily newsletter, your everydayai. Com. So before we talk about the world of startups and how startups can even adapt to innovation in the AI industry because it is going at a breakneck pace, let's first take a look at what's going on in the world of AI news. There's a lot. All right, so first and foremost a chip mech chip maker has brought in a big investment. So the AI chip firm Ten Storent has raised 100 million doll dollars from Hyundai and Samsung. We obviously talked about Nvidia earlier in the, earlier in this week and talked about how important these, these GPU chips are not just for startups and the AI industry but even for how we're now function functioning in our day to day using all these AI technologies. So something to keep an eye on there next. Google's AI search is getting smarter. So Google has their new SGE feature which is essentially generative search. Know it's getting rid of the old traditional Google and bringing in kind of this, this next phase of AI powered search from Google. You do have to have that enabled in your search lab, so we'll share about that in the newsletter. But if you do have it enabled, you're going to start to see a lot more multimedia results now coming in. You know, not just plain text. You're going to start to see a lot. All right, last but not least, meta. Meta's llama 2 may have a new open source competitor. All right, so we've talked about this on the show as well. Meta has released llama 2 which is essentially an open source alternative for something like GPT or chat GPT. So Meta made huge news when, when they announced that this was open Source and Llama 2 is out, but Alibaba has just rolled out their version of open source AI model. So a lot going on in the open source large language model kind of race. Right. So I'm excited, I'm excited for today's conversation. We already have a ton of comments coming in, a lot of people joining the show. So with that let's, let's start talking, let's start talking startups and how they can adapt to AI innovation. So I'm going to welcome in my guest for the day who has a just great background in working with startups for a very long time. Xiao Chin Chang is the president of Fintech for Good. Thank you for joining us.

Thank you for your invitation and looking forward to the conversation.

Oh yes. Oh Jesus. Everywhere you look now, I feel so many startups are raising money and startups you didn't think would be using AI, they're using AI. But before we get into that, just tell everyone a little bit about your background working with startups in Fintech for good because you're involved in a lot of ways. But just tell people how you're working with startups right now.

Sure. And Fintech for Good is a venture building studio where we help basically identify the most promising emerging technology based startups and then bring the right ecosystem around them and help them to grow, to be successful. And of course that's the startup that we focus on need to solve the right type of problem because the for good part is really as important as the tech part where that's, you know, we hope that our startups are able to bring positive change to the world, including financial inclusion, poverty reduction or economic growth, gender equality and climate change or environmental protection. Those are the type of problems that we hope that our startups can just help to solve.

Yeah, and you must look at a ridiculous amount of startups. A lot of people probably looking to fintech for good, for support, mentorship, investment.

Right.

So first of all, how many startups are you looking at and have you seen any change over the last year or so kind of with this new. Not just the generative AI boom, I would say, but it also seems like there's a lot more money now on the VC side going to startups that are trying to incorporate AI into their product, their service or their offering. So yeah, just talk about just the number of startups you're seeing and if you're seeing any change or trends with how they're using AI.

Sure. And fintech focus started in 2017 where that we had a lot of focus on blockchain and just recently we included artificial intelligence as another core focus. Before on a weekly basis or even on a monthly basis. And we may just look at one or two AI startup, but the rest are really blockchain startup. But just from ChatGPT was introduced and then the startup community entrepreneurs are really responding to the markets. The fattest, faster than capital, faster than corporate, faster than government. So then immediate, many of the entrepreneurs started to really build very exciting AI based or general AI based innovations which are pretty exciting. And then on a weekly basis now that we are looking at at least 10 to 15 AI based startups for now. Yeah.

I'll ask this because there's a story a couple of weeks ago that kind of made headlines. It was a group of former, a group of former people that worked at companies like Meta, you know, big names and they created kind of a generative AI company and before they even had a product, they had raised more than $100 million. Number one, is that, is that a good thing? And do you see that as a problem at least for startup founders, maybe that have a great product, a great service, a great offering and maybe they're just not generating, they're not using AI really in any marketable way at least. So do you see a problem with maybe an over reliance on AI at least when it comes to fundraising?

Yeah. So when the answer to whether it is a good thing or bad thing, you have to say that the good thing for whom and for the market in general. If you look at the startup community, that's a good thing because in the sense that AI is still emerging and this is really the beginning of leveraging general AI for solving challenging or impactful problem. And by having startups who are successful in fundraising and you are able to send the rights or send the message to the market, to the innovator, to the ecosystem, that's AI innovation can help you to be successful. That message itself is very important for the sustainability or the growth of the AI innovation market. Then if you just talk about the specific startup who received that large amount of investment, I don't think that's a good thing in the long term. And many times that you see that those startups, if they still don't have a product and you know, there that's, you know, you may not have the right team who can manage a larger enterprise and you may not just have the right incentive to even to, you know, dive deep and then to just get half dirty to do the building because now you have all the capital available to hire the you know, engineers and others, then the founders really just, you know, before you becoming a founder, then you're becoming a large enterprise operator manager. And then that is really not the skill set of a typical, you know, entrepreneur at, for a startup. Yeah, yeah.

Do you think just, you know, obviously you've been working and investing in startups for kind of long before this, you know, this generative AI boom, but do you think it's now more difficult, you know, even for startup founders, that maybe, maybe they're pre seed, maybe they haven't raised a lot of money yet? So in my head, part of me thinks, oh, there's all these great user friendly generative AI tools that you can, you know, code faster, you can get a better business plan, all these other things. But then on the other side, I think it might be hard if they're not integrating AI into their end offering. It might be harder for fundraising. So I guess what advice might you have for a startup founder? And they're just confused, right? They're saying, oh, should I go all in using and incorporating AI or should I just stick, you know, should I stick on a path that is not reliant on that, whether it's for fundraising or for operating?

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Yeah, and there's not a strategy which, you know, fit for all and it's really, you know, you have to look at the nature of your solution and also the market fitness. And you know, one example is that if you're working on a solid product which has market fit now and you should just not trying to ride with the hype and changing your strategy, changing your resources. Because Biden update the number one challenge for startup is to stay focused and you know, because your product is still early stage and you can go to many direction because you are a startup, you don't have many resources and because you a startup that's you know, you have a lot of noise destruction. So the you know, number one factor to for a startup to fail is that you lost the focus and if you lost focus and then you will fail no matter the hype now is AI or another, you know, emerging technology. If you lose focus and focus on wrong things, send you know, put your resource into wrong strategy and then you will fall. And of course that's you know, for some, for other startups who you know from beginning build, they try to build an AI startup and that's natural that this is good time for them and where that's to double down of their investment and if they for example are still a part time startup founder and it could be a good time that to try to accelerate their you know, prototyping or product or strategy. So to make sure that when this is at an early stage and when the you know, market is still hot and especially you know it's easy for them to find co founder, it's easier for them to find the technical resources and also it's easier for them to tap into the bigger ecosystem who want to be part of the AI cake. And I think that's a good time for them to double down their investment. Yeah, yeah.

You know, earlier the name was escaping my mind. I think it's Mistral AI that was the, the startup with the co founders who worked in big tech. So even when we talk about situations like that, are you seeing too many of these new startups pop up saying hey, we're going to offer all these generative AI tools because they're seeing just the sheer amounts of money and investment coming in. Do you see that as a problem or do you think that there's still going to be use cases for you know, so many different people, companies, enterprise to be using these, these different tools that these startups are promising to create essentially is it going to get oversaturated because of all of the money right now going into kind of, you know, AI related companies?

Yeah, and again that's you know from beginning we talk about entrepreneurs are the most sensitive to market trend and, and then they are fattest and then they are also the most innovative. In essence, when there is a Trend emerging and then there is market message that they received naturally that they are going to just responding to that. That happened during the, you know, the dot com era. That's happened during the, you know, the blockchain and that's also happened for AI, that happened for Metaverse. So anytime when there is a very strong message from the investor from the ecosystem that this is a hot area where that's more investment is going to go there and you will see a lot of startup, a lot of innovators will go into that and I never think that we have too many innovators and but it doesn't mean that all of them will be successful because you know, there are data, data, you know, in the market as common sense, 99 of the startup will fail. So yeah, you want to be that 1%, you don't want to be that, you know, 99%. So then if or not, you know, the market will not have a problem in the sense that you know a lot more join, you know, to join this, this big trend of, you know, AI innovation. But I think for you, if you are startup, if you are entrepreneur or think about it and you have to really just answer a few basic questions. Number one is that you know, do I solve a right problem? Number two, does this problem have market fitness? Number three and do I have customers who are willing to pay no matter it's 2B 2C 2G there are somebody who want to pay for my service for my solution. Number four, do I have a pricing model and which really supporting that customer to leveraging my service? If you have all answers, go for it.

Wow, that was just a master class there from Shaoxin. Just if you were struggling to keep up with his points there, don't worry, we're going to recap it all in the newsletter that we're going to send out after this. But we have a great question here from May Britt in the comments. So as a reminder, if you are listening, make sure to get your question in about how your startup or startups in general can use AI. So May Britt's question here is what are your thoughts on startups that don't have an AI focus yet? We kind of touched on this, but instead should they work on a tech product and just focus on the AI element later or do they not even need to have their eyes on an AI element?

Yeah, my answer is you're right and you don't need to. So if, if you work on a tech product now and which means that you already answered that Those four questions, there was a product problem, there was market fitness, there was the customer, you know, you have a good pricing model and then you know, no matter is AI metaverse or another emerging technology that for you becoming noise. Right. And of course that's, you know, when, when you continue to improve your product. And naturally you may see AI can improve your product, meaning that, you know, a lot of time that's AI can reduce the cost for you to just launch a product. AI can help you to just reduce cost and time of your go to market strategy. And AI can help you also to potentially create a new type of product solving adjacent problem to the core problem that you're trying to solve and then that also have a new market which you can tap into. So those are additional problems, additional opportunities. But again if you are a startup, have a problem, have a problem, have a product already ready and only because that there is a hype in AI that you started to think about whether I should expand and all that, that becoming distraction rather than an opportunity.

Yeah, yeah, that's such an interesting way to reframe the thought and the conversation around should my startup use AI or not. And you mentioned go to market, which I should put this out there to our viewers and our listeners as well. So you also served as the global head of innovation and go to market with Amazon Web Services, given that experience too, I guess what are some takeaways from your time there that you can share with a startup founder right now and maybe they're struggling to say, okay, which direction should I take my startup? You know, with that go to market background, how would you advise them?

Yeah, and the number one message is really around customer obsession. Your customers are smarter than you and your customer will guide you and where to invest, what to invest and also what product they need. And so to try to understand better of your customer and to just bring the right product to them and also understand their behavior and also understand the core challenge for them to adopt your products. I think those are really key that everything what you are working on in terms of go to market is around your customer. So you need to have proposition what value can bring to your customer and communicate that value proposition through your market, through your marketing and to your customers. Number three is always bring your customer into your product design and product implementation roadmap, where that's have them to give you feedback in terms of whether you have the good feature, your feature really just, you know, solve their problem. How easy to use does it, you know, require one click, two click, multiple click and Your customer want one click or multiple click. And so whatever your customer need or want, that's where you know, you need to just invest more of your time, your resources to improve.

Oh, you know, one, one thing you mentioned there, which when you said it, I'm jotting myself down notes as well. Right. So you said being obsess with the customers and not just, you know, whether they're spending their money or not, but you know, you said bringing them in, you know, to the process, it just, you know, it reminded me I've used, you know, personally probably 700 pieces of software. And I remember early on there's this company called Lemlist, you know, and I was chatting with their founder, it was 2am local time and he was asking me about the question. And you know, now they're obviously, you know, unicorn status. But we have another, another great question here from Ben. So Ben is asking what about startups using AI as a tool to help them find new market segments, design products, images, videos, developing pitch decks.

Right.

So you know, your ChatGPT type products but then you know, you also have products that can help, you know, people code better, you know, copilot, you know, all of those tools. So yeah, what's, what's your take on Ben's, Ben's question here?

Yeah, that's this question related to the last question you ask. Do we have too many. Right. And so interestingly, for all the area that Ben asks, there are basically a lot of startups and who are working on the similar problem. And then there, that's, I think your differentiation strategy becoming very important. If say my AI tool can help you to write a social media post, your AI tool can also do the same. Then now the customer have a choice to make. Why do I use this one, not that one Similar thing, for example, design products and leveraging video and image to just create new insights and all that, you basically have tons of tools and are trying to solve the similar problem. So then if you are a customer, you have a choice. Then if you are a startup founder and in addition to the differentiation strategy that you have, and the second piece of that is how to bring that differentiation strategy message to your customer. Make sure your customer understand that for this tool this is different from the other tools who are trying to solve the same problem you have and then why this is better, then create the right channel and then to bring that message to your customers and also again, bring your customer testimonies and using your customers to educate other customers and in that way that your customers finally understand that even they have more tools in the future then they still have loyalty to yours and then stay with you. Wow.

If you're listening and you're in startups, you just got a masterclass. Wow, I can't thank you enough. I guess. Before we wrap up, do you have any last advice or just last thoughts on where AI is trending in the startup industry that people can really just take and use and feel more confident in building their startup?

Yeah, definitely. Number one thing I think is really is the responsible development and use of AI. And sadly that's, you know, a lot of innovators care about AI and a lot of large enterprise, even you know, government care about AI. But you know, AI has, is a double sword where that, you know, you have the, the benefit of improved productivity but you may also create a bias, you may create, you know, the, the, you know, impact to gender inclusion. You create tense and hallucination and you may also have a lot of other ethical related issues and then regulators around the world trying to just create new laws, regulations for AI regulation. So if from the beginning that you didn't pay attention to that piece, then you just think that I can build a product I can offer to the market and then no matter what how your AI model is trained, what data you used and you cannot verify that you didn't do harm to the society and then later you will enter into trouble, no matter is the fines or litigation or your customer will leave you. So those are the things that you need to really from beginning and then when you are innovating, trying to innovate in a responsible way, get yourself informed, make sure that the ethical concerns are being addressed and that I think is very important. And the second piece, go back to your customer and trying to really think on behalf of your customer. At this point, AI can do a lot for the customer and what are the biggest problems that they face and connect that with your strengths, your resources, you know, why I'm, you know, at the best position to solve that problem for my customer. That itself is, you know, the number two most important question. The third one is that AI cannot solve all problem and you have to look into, you know, AI, IoT, metaverse, blockchain, other emerging technology and also other, you know, already mainstream the technology to combine all technology together and then by the end of day, technology is not an end goal, AI is not end goal. And your problem, the customer problem is the end goal and bring the right technology mix together to solve problem for your customer. I think that will be essential. Wow.

After each one of these responses I just say, wow. And I'm jotting down notes. So you shared so much today that can really help startups not just understand AI, but how they can actually innovate and grow with it. Shachin, thank you again so much for joining the Everyday AI Show. We appreciate it.

Thank you very much for holding us and thank you for everyone listening to us.

All right, just as a reminder, there was a lot in this conversation. Don't worry, we're going to recap it all. So make sure that you check out the newsletter. If you're not subscribed, go to your everydayai.com Sign up for that daily newsletter. We put it out about two or three hours after the podcast, so we're going to be sharing a lot about what you heard today. But also we're going to be sharing a little bit hopefully about the Chicago AI conference that Shashan's working on as well. You know we're a Chicago based show. I know we have a lot of Chicago listeners, so make sure to check that out as well. All right, so that's it. We hope that you can join us tomorrow. We're going to be talking about our favorite ChatGPT plugin. So hope to see you back tomorrow and every day with Everyday AI.

Thanks. Thank you.

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