Everyday AI Podcast – An AI and ChatGPT Podcast - EP 72: How Startups Can Adapt to AI Innovation

Episode Date: August 3, 2023

We dive into the world of startups and how they can adapt to the rapidly evolving landscape of AI innovation. Joining us is Xiaochen Zhang, President of FinTech4Good. We'll explore the challenges and considerations for founders when incorporating AI into their business offerings. From raising funds to customer involvement in product development, we cover it all.Newsletter: Sign-up for our free daily newsletterMore on this: Episode PageMore on this topic in today's newsletterJoin the discussion: Ask Xiaochen and Jordan questions about startups and AIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTimestamps:[00:00:17] Daily AI news[00:05:49] Fintech and AI[00:07:57] Startups benefiting AI market, but caution long-term[00:10:56] Double down investment for AI startups[00:14:15] Entrepreneurs sensitive to trends, need market fit.[00:19:36] Customer obsession: Listen, invest, improve, communicate, adapt.[00:24:46] Final takeawaysTopics Covered in This Episode:- Introduction to the prevalence of AI in various industries  - Mention of recent investments and developments in AI technology- Introduction of guest Xiaochen Zhang, with experience in fintech startups- Discussion of challenges and considerations for startup founders in relation to AI technology  - Questions raised about the difficulty of raising funds without incorporating AI  - Weighing the pros and cons of integrating AI into startup offerings- Personal experience with Lemalist emphasizing the importance of involving customers in development process- Question about startups using AI as a tool for tasks like finding new market segments and designing products- Mention of AI-powered products like ChatGPT and coding tools- Four key questions for successful tech products: problem, market fitness, customer, and pricing model- Role of AI in improving products, reducing costs, and shortening time to market- Possibility of creating new products to solve adjacent problems and tap into new markets- Caution against solely focusing on AI as a distraction for existing products and problems- Importance of responsible development and use of AI, considering ethics and potential harmKeywords:entrepreneurs, market trends, innovative, investors, ecosystem, area of investment, startups, innovators, successful, 1% that succeeds, solving the right problem, market demand, customers, pricing model, differentiation strategy, customer choice, unique value, customerSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

This is the Everyday AI Show, the everyday podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. Meet Firefly AI Assistant, now live in Adobe Firefly, the All In One Creative AI Studio. Just describe what you want to create and the assistant handles the rest, orchestrating multi-step workflows across Photoshop, Premiere Express, and more in one conversational interface. You direct the outcome. The assistant accelerates execution. 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 everyday AI.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 maker has brought

in a big investment. So the AI chip firm, Ten Storrent, has raised $100 million from Hyundai and Samsung. We obviously talked about Nvidia earlier in this week and talked about how important these GPU chips are, not just for startups and the AI industry, but even for how high. how we're now 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. You know, it's getting rid of the old traditional Google and bringing in kind of 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 Lama 2 may have a new open source competitor. All right. So we've talked about this on the show as well. Meta has released Lama 2, which is essentially an open source alternative for something like GPT,

or chat GPT. So, Meta made huge news when they announced that this was open source and Lama 2 was 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 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. Shao 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, geez. It's everywhere, 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 and 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 that's 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 that's you know because the full good part is really as important as the tag part where that's we hope that our startups are able to bring positive change to the world, including financial inclusion, poverty reduction, 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. You know, 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, you know, over the last year or so, you know, 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, you know, trying to incorporate AI into their product, their service, or their offering. So yeah, just talk about just a number of startups you're seeing. And if you're seeing any change or trends with how they're using AI. Sure. And the FinTech focus started, you know, in 2017, where that we've had a lot of focus on blockchain. And just recently, we included artificial intelligence as another core focus. Before, you know, on a weekly basis, or even on monthly basis, and we may just look at one or two AI startup, but the rest are really, you know, blockchain startup. But just from, you know,

chatyPD was introduced. And then the startup community entrepreneurs are really responding to the markets the fattest. You know, faster than capital, faster than corporate, faster than government. So then immediate many of the entrepreneurs started to really build a 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. You know, and do you, I'll ask this because, you know, there's a story a couple weeks ago that kind of made headlines.

It was a group of, you know, a group of former, you know, a group of former people that worked at companies like, like Mata, you know, big names. 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 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, you know, whether it is a good thing or bad thing,

you have to say that, you know, the good thing for whom? And, you know, for the markets in general, you know, if you look at the startup community, that's a good thing. Because in the sense that, you know, AI is still emerging, and this is really the beginning of leveraging general AI for, you know, solving, 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, you know, AI innovation can help you to be successful. That message itself is a very important for, you know, the sustainability or the growth, of the AI innovation market. And then if you just talk about the specific startup who receive that large amount of investment, I don't think that's a good thing in the long term.

And many times you see that those startups may, if they still don't have a product, and 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 hard 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're becoming a founder,

then you're becoming a large enterprise operator, a manager. And that is really not the skill set of a typical, you know, entrepreneur 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 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? Adobe just introduced an entirely new way to create, bringing the power and precision of its creative suite into one conversational experience.

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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, you know, example is that if you're working on a solid product, which has market fit now, and you should just not, you know, 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 directions. Because you're a startup, you don't have many resources.

And because you're a startup that's, you know, you have a lot of noise destruction. So the, you know, number one factor 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 around things send you know put your resource into wrong strategy and then your will phone 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 a 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 to try to accelerate their prototyping or product or strategy. So to make sure that when this is at an early stage and when the market is still hot, and especially it's easy for them to find co-founder. It's easier for them to find technical resources.

And also it's easier for them to find technical resources. And also it's easier for them. to tap into the bigger ecosystem who want to be part of the AI take. 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 a mistral AI.

That was 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, you know, saying, hey, we're going to offer all these, 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 then they are fatticed. And then they are also the most innovative in that sense. When there's a trend, you know, emerging and then there's market message that they receive, 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's a very strong, you know, message from the investor, from the ecosystem, that this is a hot area where that's, you know, 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. But it doesn't mean that all of them will be successful because, you know, there are 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 it will not, you know, the market will not have a problem in the sense that's, you know, a lot more join, you know, to join this big trend of, you know, AI innovation.

But I think for you, if your startup, if you are entrepreneurs, if you're 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 happen market fitness? Number three, and do I have, you know, 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 is supporting that customer to leveraging my service. If you have all answers, go for it. Wow. That was just a masterclass there from Shao Chen. 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 Maybrit in the comment. 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 Maybroth'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 you work out a tech product now, which means that you already answered those four questions. There was a problem. There was market fitness. There was a customer. You know, you have a good pricing model. And then, you know, no matter is AI matter or another emerging technology, that for you becoming noise, right? And of course that's, you know, when you continue to improve your product, and naturally you may see AI can improve your product, meaning that's, you know, a lot of time that's AI can reduce the cost for you to just launch a product.

And I 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 has a new market which you can tap into. So those are additional problems, additional, you know, opportunities. But again, if you are a startup, have a problem, have a product already ready, and only because that there is a hype in AI that, you know, you started to think about, you know, whether I should expand and all that, that becoming distraction rather than, you know, an opportunity.

Yeah. Yeah. That's such an interesting way to reframe the thought and the, conversation around, you know, should my startup use AI or not? And, you know, you mentioned go to market, which I should, you know, put this out there to, 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, right? Given, given that experience, too, you know, 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 we're, you know, 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, you know, the core challenge for them to adopt your products. I think those are really key. That's, you know, everything what's your, you know, working on, you know, in terms of go-to-market is around your customer. So you need to have, you know, proposition. what value can bring to your customer and communicate that value proposition through your market,

through your marketing, and to your customers. And 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 solve their problem. How easy to use it. That's it to, 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. Wow. You know, one thing you mentioned there, which when you said it, I'm jotting myself down notes as well, right? So you said being obsessed 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 Lemelist, you know, and I was chatting with their founder. It was 2 a.m. 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 chat, you pt type products, but then, you know, you also have products that can help, you know, people code better, you know, co-pilot, you know, all of those tools. So yeah, what's, what's your take on Ben's question here? Yeah, that's, this question related to the last question

you asking, do we have too many, right? And so interestingly, for all the area that's a band asked, there are basically a lot of startups and who are working on a similar problem. And then, you know, there that's, I think, your differentiation strategy becoming very important. You know, 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, right?

And why do I use this one? Not that one. And then so similar thing, you know, to, 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, If you are started founder, 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 these two, this is different from the other tools who are trying to solve the same problem you have, and then why this is better. and then create the right channel and then, you know, 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's, you know, your customers finally understand that, you know, even they have more tools in the future, then you still, they still have loyalty to yours and then stay with you. Wow. You know, if you're listening and you're in startups, you just got a masterclass. Wow. I can't, I can't thank you enough. You know, I guess, I guess before we wrap up, do you have any last advice or just last thoughts on, 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 the use of AI. And, you know, 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 is a double sword where that's, you know, you have the benefit of improved productivity. but you may also create a bias, you may create the impact to gender, inclusion, you create, you know, tant and a hallucination, and you may also have a lot of other ethical-related issues. And then regulators around the world trying to just, you know, create new laws, regulations, you know, for AI regulation.

So if from the beginning that, you know, 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 how your AM model is trained, what data you use, 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, you know, make sure that's, you know, 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, and, you know, and, you know, And, you know, 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 problems. And you have to look into, you know, AI, IoT, Metaverse, blockchain, other emerging technology, and also other, you know, already mainstreamed the technology to combine, you know, all technology together.

And then by the end of this, you know, technology is not an end goal. AI is not an 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, you know, be essential. Wow. After each one of these, you know, responses, I just say, wow, and I'm jotting down notes. So, you know, you shared so much today that can really help, you know, startups, not just

understand AI, but how they can actually innovate and grow with it. So, Shaachan, 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. And 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 Shawshan is 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 chat GPT plug. So hope to see you back tomorrow and every day with Everyday AI.

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Stand control with the ability to stand. step in and refine at any time. See it today at firefly.adobie.com. And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit Your EverydayaI.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next time.