39 | Top AI Wins: Key Business Use Cases from Hundreds of Companies, shared by Demetrius Brinkmann, CEO of the ML-Ops community

30:24So you can put a dollar value. But to know that, you need to wait sometimes for it to see. So the leading indicators can be, are people using it? How often they're using it? What results are they getting from it? Are they then going back to what they did before or not? Like you can put other KPIs in place to see that the solution that you have, that you're testing is actually yielding a result that has a business impact. Because otherwise, oh yeah, it's really cool. And we just spent two months on it, but either nobody's using it or they're using it, but it's taking us the same exact amount of time that it took us to do the thing that we did before.

31:02It's just more cool than you just wasted two months of salaries and computing power and so on. So I agree with you 100%. I think at the end of the day, people have to remember that this is a business decision that has to be tied to a business strategy and a process and KPIs to measure that this is actually moving forward. Despite the fact there's a very serious FOMO right now, oh my God, everybody's implementing AI and I have to do it as well. And despite the fact that it's really cool. So I love that. That's where one thing that I will say is the companies that I've seen doing this well, it's not necessarily that the feature comes from the machine learning engineer or the software engineer.

31:41It's more a product engineer or product manager that understands the product, understands the capabilities of the product, and then can understand what the user is looking for and have that empathy of where the users are getting stuck right now. And if this product engineer understands what AI can do in a real tangible, like feet on the ground way, not like Twitter demos of this is auto GPT is now going to create these agents, which will be able to go out and do anything on the internet. And that just is not the case for 99 % of the people that have used these agent tools because it's very difficult and we can get into that if you want.

32:27But I think the product owners and product engineers who understand AI, but they are very heavily based in their, they have their product sense. Those are the ones that say, oh, maybe we can add an API call here and we can just magically add this feature of natural language processing and then boom, we can do it. And they understand that there are certain metrics that they need to tie things to. And they can, I am thinking about a specific instance when I talked with this guy, Philip from Honeycomb, and he spoke about how their complicated product, which is monitoring and observability platform, to break that down, it's are my servers up and running, basically, in a very simple way.

33:17And are we doing what we say we should be doing and if we're not is our product failing and why and then we can debug why it's failing and so honeycomb helps you do that and philip talked about how there's certain things that he wants he sees success when someone has accomplished uh three tasks in the first 30 days of testing out this product. And so he noticed that when they added AI capabilities, those three things were like 85 % more likely to be used. And so then, boom, they said, you know what? However much we're spending on API calls to open AI, if we just get one converting customer, it makes it all worth it.

34:12So he was very clear on what the metrics were that he was trying to change and how the money that they're spending on the API calls using the AI actually is net positive. Yeah, I definitely agree. I think it's first and foremost, a business problem. And then the second thing, and I agree with that as well, it's a product question. And even if it's not a product, like if not a SaaS company trying to implement it, then look at the processes that you're doing in-house, look at the processes you're doing with your clients and look how they are being improved. How much time is it saving? How much more money it's generating?

34:48Like whatever the case may be, it has to be tied to a business KPI that you can actually measure to see whether that's worthwhile. And as we mentioned, you can start small. You can start implementing what we said earlier, one of those open source, not open source, sorry, one of those SaaS solutions that you can connect to data takes a non-techie person less than a day to get started to play with it. It's literally going in, setting up your logins to the different things you wanted to have access to and defining some parameters of what you wanted to do. And you can test whether it's working or not.

35:22It's that simple. And so within a investment of 20 to$50 a month, which in a business perspective is free, you can test the concept, right? And if it's working and then you're saying, oh, I wish we could do this. Now you can start continuing down the rabbit hole and going further and deeper understanding that's going to require more resources and more time, but will yield more accurate, more consistent, better connected, like whatever you want to challenge in that particular thing results for you. So great conversation. I think this was awesome. I know there was one more use case you wanted to mention as far as coding, and I'm very curious about that.

36:02And I wanted to touch a little bit about it because I don't know if all the listeners care about coding, but I think more and more companies, even if they're not a software company, have people who are writing code to support things that they're doing. And I think understanding what are the capabilities today with writing code with AI could be another very interesting point things to touch on. Yeah. And you've seen lots of these coding co-pilots come up. It's not just Microsoft co-pilot that's out there. I was actually talking to a founder yesterday that has this tool Codium and they've got a lot of users.

36:42They've got like over 400 ,000 users and they're doing, they built their own LLM. It's not, again, this is like, they're playing on hard mode. They said, okay, we can't differentiate ourselves by just building exactly what Copilot has because Copilot is always going to be a winner there since Microsoft invested 10 billion into OpenAI. What can we do that will differentiate ourselves? It comes down to we're going to build everything from scratch. So they had the expertise. They were a bunch of guys that came from the autonomous vehicle realm. they were working at neuro I think it was and so then they said all right let's go and let's build it and they built it and came out with it and they said that because of their expertise in the company that they were doing before this they understood how to be able to serve so many people at such high scale and so quickly and so now when you're using that tool or if you're using copilot or if you're using there's a few other ones that i should probably mention there's one called cody from the i think it's source graph and then there is another one from i think it's called bito b-i-t-o and all of these folks have their hubs copilot right that's another one that's yeah that's like the classic one i think that everybody has probably at least heard of a little it and so these are quite useful and i know replit also has one it's like ghost coder or star coder i can't remember if i get it mixed up because hugging face has an open source model that's one of those two maybe it's star coder so don't quote me on the title on that but replit is like a github and it has i think all the coding tools are going to have some of this built in because it just makes sense that it's very useful it ups the productivity of your developers now i will say this though again it's like it's easy to say that things are going to be totally different everything's changed and now we have copilot it's going to make any bad engineer an incredible engineer but what we've seen is that you still have to know what you're doing surprise you can't replace experience and understanding of code base only 100 with a coding copilot because even if you don't know how to code, then you don't know if the code that it spits out is correct or it's the best way to do that or why it could be problematic down the line.

39:35And that ends up getting you into trouble. And I think another thing, so just to clarify this for people, these coding co-pilots, what they do is they spit out code and they know how to do it in multiple coding languages by now. and for multiple use cases. And they're very good at saving time for stuff that is just tedious work. Like I need to write this thing that does that thing and it's whatever, a hundred lines of code and it will spit it out for you based on the parameters you told it. And it saves you writing a hundred lines of code. The thing is, as you get further from the code and more up into understanding what the system that you're trying to build needs to do from an architecture perspective, from an efficiency perspective, from the hardware that it's using.

40:21There's so many other layers other than the hundred lines of code you needed to write that you need to understand in order to make your code the most efficient for that particular setup. And that's where these things are not very good because they're not engineering the system yet, I should say. But as of now, they're very good at writing these short code snippets. If how to explain it to them and if you know how to test that it's actually doing what it's doing, it could make people, and you may have numbers, I don't know from an efficiency perspective, how much more efficient it makes people who actually have played with it and used it.

40:56But I'm sure it's tens of percents, right? Better. For sure. Yeah. And so I don't have an exact number on that, but I do, I will say that it makes you much faster at doing those tedious things. It also can be problematic because you accept the autocomplete. And then later on, you're like, why is this not working like it used to? And you realize that, oh, it's because I accepted that autocomplete. And I will say too, though, that like Codium, I dug in when I talked to the founder yesterday and was asking him about that. And he understands those downfalls. And he is making a point of trying to take as much context as possible from your code base before giving you a suggestion on where we're going.

41:47So it's not just like it has no context and it doesn't understand what you've been writing, what your system looks like, what hardware constraints you have, et cetera, et cetera. And so in that regard, I do see it getting better really quickly. I feel like it is an amazing tool and it is one of those use cases, again, that is a shining star. Like the chat with your data and the coding use cases are very clear that LLMs are very good at this. And with coding, it's even better because you can potentially test your code after you accept that autocomplete and you can see, does the code still run? And so it's very black and white.

42:30It's not like I'm testing out if this copy, like copy is very much subjective, right? If it's marketing copy that you're putting on a web page, you can't really put that through a yes or no. Does the code still run type thing? But when it comes to code, you can. So I see a very long future in this. I wonder, I don't think it's going to be like what we saw in the GPT-4 demo day where they were like, oh, I just drew this picture and now it spit out this full blown web page. I don't see that happening. yet, but hopefully it will because I would love that. I think that would be really cool. Yeah, very interesting.

43:13I think a quick thing on the coding stuff, it's important for people to understand. And by the way, for everything, not just for coding. The AI that exists today is the worst AI we'll ever have. We're in version 0.1 of all of that. Even the stuff that is quote quote unquote, mature, is in the very, very early infancy stages of it. So everything that we're saying is true today may be somewhat wrong in a month and may be completely wrong in six months, meaning the ability of these things to make progress very fast is nothing that we've seen before. But as of now, this is an amazing time saver for writing pieces of code that you need.

43:52Like you're saying, there's already steps in the direction like, oh, I need to understand the broader system and the broader code and the way this particular person writes and sets up his code and comments and so on. So I want to make it fit that. And so it will move in the direction where we'll be able to create more and more software. And the beauty of that, going back to the applicability of this to anyone, and that's true for all the AI stuff, it's the democratization of things. So far, let's say you wanted to start writing code within your company, regardless of what you do, you either needed to find a third-party company or hire six, seven, eight people to get the job done.

44:33And within a year from now, you might be able to get away with hiring one guy because with these tools, he'll be able to create a lot more stuff, a lot faster to do all the things that the other four people were supposed to do. And yes, that requires a slightly different set of skills. But I think, again, developers, probably more than any other profession in history, have learned to adapt to new languages and new development platforms and new integration capabilities and new database types because it's constantly changing. And so I think we'll see a whole new era of new kinds of developers who will know how to use all these tools in order to do stuff that a year ago would have been considered magic.

45:17Yeah. So I have two things to mention about that one is i contemplate a lot about where we are on the s curve are we at the bottom of that s curve and we're about to just see like vertical growth for the next six 12 months or maybe six years who knows or are we at the top where we're just like logarithmically for the next 10 years is going to slowly be getting better, like with the iPhones, where nothing really changes from one model to the next. But if you look back from the one that I have now to the one that we had when it first came out 10, 15 years ago, there's a big difference, right? I am not sure.

46:02I have no idea where we are on that, nor do I think anybody can with confidence predict where we are in that. And even if they tell you that they can, I would be skeptical. because maybe we've hit a plateau, or maybe we're at the bottom, and we're about to get another huge breakthrough, right? And so one thing that I think I've heard people talk about is how can I prepare, especially like a business owner, how do I prepare if in six months, all of the stuff that I'm working on right now becomes irrelevant? Or like you were saying, I go out and I hire seven software developers and then in six months I only need one and why don't I just wait six months and get that one that one is not guaranteed and I would probably err on the side of you're probably not going to have one anytime soon but the thing that I think the the wisdom that I've gotten from talking to people is that you want to optimize your system for what is possible now and then And whenever that gigantic breakthrough comes out, whenever it is, you can upgrade.

47:14But you don't need to try to do these like Herculean efforts to try and get that extra 1%. Unless your meta and billions are made with that extra 1%, then it's obvious. All right. Yeah. Throw as much money as you can at it. because just even like a 0.004 % of ads optimization is going to net you a whole lot of cash. But for the most of us, it's that Herculean effort to try and get that extra 1%. You don't necessarily need to do right now because in six months or in 12 months, we're probably going to be 20, 30, 40 % better than we are today. And so that 1 % isn't going to really mean much, right?

48:02So that's how I've started looking at it. I don't necessarily want to say, oh, what is that going to look like as far as how many software developers I need to hire? I will just say, yeah, let's try and optimize for the tech that we have now today and not get FOMO that in six months after I have this six month project. And finally, in six months, I put my baby out into the world. Then there's a whole new technological breakthrough and it renders whatever you created obsolete. So I wouldn't worry too much about that. I love this comment and I want to generalize it for a second. And it's true, not just in coding, right?

48:46It's true in this machine learning world that we're in or AI world that we're in. And there's always, there's literally hundreds of tools coming out every single day. It's a chase that a business cannot do because you got to start doing stuff. And so when I work with companies, it's always a mix of two things. And one thing is figuring it out. What are the low an AI tool, one or another can really yield immediate business results, either more money, more clients, savings, whatever, whatever optimization of business processes that you can do. And then you can win right now. Like it doesn't matter if there's a better tool in six months, because right now you just saved yourself 200 hours a month, or you just have 10 % more clients every month with the same resources you have right now.

49:37So this is number one. And number And two is really the other end of the spectrum where, okay, let's look at the business strategy as a whole. Will our clients need the same things they need right now, two years from now, because AI is coming in? Do we need to make changes in how our business is structured, the type of clients we're going after? The more strategic thinking, knowing that this is going to get better and better, either quickly or slowly, it is going to get better. And so now through that lens, let's look at our business as a whole from a strategic perspective. And then if you combine these two things, you don't really care about the fact that six months later, there's going to be another big thing.

50:19And the other thing that I tell people is figure out how to use AI. Don't figure out how to use this tool. Figure out how to use AI for this use case. because then if six months from now, there's a better tool for this use case, you already know how to implement it, how to use it. The team is more comfortable doing it and you can upgrade relatively easy versus, oh, I just spent six months in how to use this tool and now there's a new tool. And so always think about it from the use case business perspective and not through the tools lens. And then the next step will be a lot easier because now you know how to solve for the use case with AI in general and not just with this particular tool that you fell in love with.

51:02Actually, that's a great point because we've been talking a lot about large language models, which are based around language. But there's two other sectors, I think, of AI that have had incredible progress over the last year and a half. One being voice. So either it is us talking and then that being transcribed into text, or it is us writing text or potentially a large language model writing text and then it being put in our voices because it has enough of that training data so the voice like audio is incredible i'm not the biggest fan of like music made by ai i know that's been happening i'm actually i'm a musician at heart and i just haven't gotten it i do understand that is incredible what's happening there, but I'm not going to be making any AI generated songs anytime soon.

52:00That's personal opinion, but that is out there too. And then, but the second area besides audio and voice is photographs or not photographs, images and generating images from text is absolutely mind-blowing. The rate at how good that got, how quickly that got, and especially if you're looking at something like a mid-journey, that is just almost everything you can prompt it by telling it looks great when it comes out, especially if you're looking at some of these newer versions of mid-journey. So it goes back to what you were saying. I just wanted to bring it back to this idea of know where these different capabilities lie and how you can augment your own workflow with these capabilities or your company's workflow so maybe that's you can go and find a tool that can create 20 different logo versions if you're a design shop and then you have the professionals do the last finishing touches on it maybe or I know there's a ton of other use cases that you can do in this area.

53:19My friend actually has this company called Storia, and he is focusing on creating how when you create a movie, like the directors have their storyboards first of the shots that they want to get. So he is helping directors create storyboards with these AI generated images. And again, now Adobe Premiere last week in their big conference, they're doing this on the fly based on the script. Like they're creating those storyboards and they can even then render a video of how the storyboard will actually look like once you shoot it. and just to get things going to in the direction you're going in X number of months into the future, I don't know if that's six or 12 or 18, but somewhere in that range, you'll be able to actually render a high-end quality video, which means you may not need to shoot the video.

54:18You will just have it out of the stuff that you've already created. Listen, I think this summary is a great summary, right? It says that find the use cases, find the places where it's the most useful, start using it, learn how to use it, and then adapt as it's moving forward. This was an amazing conversation. We touched on a lot of really important stuff that is relevant to probably any person in business, but definitely any decision maker. If people want to learn more from you, follow you, connect with you, work with you, what are the best ways to do that? I'm probably most active on LinkedIn these days.

54:54So it's just LinkedIn slash DP Brink M. And I do a bit of trash talking on there, the whole AI ecosystem too. So hopefully it's fun for people to follow. Awesome. Dimitrius, thank you so much. Great conversation. Lots of value. I appreciate you and I appreciate you taking the time and sharing with us. Yeah, man, it's been great. Thank you for having me. This is awesome. What a fascinating conversation with Dimitrius. I must admit, I'm not surprised with the use cases that rose to the top, but maybe it's a chicken and the egg thing. We know them because a lot of people are doing them, or maybe it's the other way around.

55:33But definitely creating chatbots that can connect to as much data within the company as possible, initially for internal uses, and then for customers as well, is going to be a focus for probably many, many different companies in 2024. And now let's jump to the crazy news that we had this week. As I mentioned, I'm going to start releasing Friday news edition of this podcast, but there's a few really big ones this week that if you haven't heard of yet, you probably want to hear right now. So the biggest news in the AI world, maybe ever since the launch of ChatGPT, was that Sam Altman, who is the CEO of OpenAI, which is the company that has created and gave us ChatGPT, was fired on November 17 in what seemed to be like a coup very well executed by people at OpenAI's board.

56:32Immediately after firing Sam, they spoke to Brockman, who was the president and the chairman of the board, and they demoted him as well, basically revoking his seat at the board and obviously his chairman position, allowing him to only keep the president title. He immediately resigned after that move and the move of firing Sam Altman. And the board have announced that Mira Morati, who is one of the founders and the CTO, will act as interim CEO until they find a new one. This news was obviously really shocking because Sam Altman is the person that led the company into the launch of Chachupiti and from anonymity to maybe the most spoken name in the tech world today, a company that has created a whole new era in technology that was able to keep ahead of Google and Microsoft and Amazon and IBM and Facebook and everyone and still leads the generative AI race today.

57:31Why was he fired? Still not completely clear, but I want to explain something. OpenAI was founded as a non-profit company. And at a certain point, when they understood that the nonprofit company cannot raise enough money, they've created a for-profit company under the nonprofit company. Why does that matter? Because the board that makes decisions for OpenAI is still a nonprofit board with no representations to the big investors. At the top of them is Microsoft, which has committed$13 billion with a B to open AI. Presumably, Ilya Satsky, who is also one of the founders and one of the board members, was not happy about the speed that the for-profit company was running when the nonprofit company was established in order to create safe AI for everyone.

58:25And he was apparently feeling that's not what the for-profit company is doing anymore. And the alleged reason why he was fired, and now I'm quoting, is that he was not consistently candid in his communications with the board, hindering the ability to exercise its responsibilities. So that opened Pandora's box. Everybody was starting rumors on what he's going to do next. Is Brockman leaving with him? Are they going to start a new company together? Hundreds of employees shared their disapproval off the move and even threatened that they would leave with him if he leaves. And the whole company has about 700 employees.

59:03So if hundreds of employees actually end up leaving, that leaves OpenAI with, well, not enough employees to run the company. So I don't really know what's going to happen, but the latest news from today, Monday morning, is that Sam Altman and Brockman are joining Microsoft, that is the biggest backer of OpenAI, and that also Mira Morati is not going to be entering CEO. So who's going to be the entering CEO of OpenAI? The company that launched ChatUPT, one of the most successful products in history. So the person is Emmett Shear, that you probably don't know the name, but Emmett Shear was the CEO at Twitch, an incredibly successful streaming business that is owned by Amazon.

59:47So he's stepping in to the very big shoes of Sam Altman. Sam and Brockman are moving to Microsoft to run what they call a new company or a new division within Microsoft, which is obviously going to be the one implementing the AI tools for Microsoft across probably everything that they do. As I said earlier, they've bet$13 billion on this, and they're literally changing the entire Microsoft strategy around AI. So for them, I think it's actually a very big win to bring Sam and Greg Brockman over. How's the saga going to end? Nobody knows. This is the Monday update. As I mentioned, I will update you further this Friday.

1:00:26But before these nuclear news happened, a lot of other interesting stuff happened this week. The world's first AI-powered humanoid robot became CEO of a rum company called Dictador this week. The robot was built by a company called Handsome Robotics, who has built these kind of robots for several years now. And while there's a lot of moves to making different robots make different activities, being a CEO of a company is something I did not anticipate to happen that quickly. How exactly is it going to work? How does he do all the human aspects of being a CEO, like hiring, inspiring, and leading employees?

1:01:10I don't know. And I don't know if anybody knows, but that will be very interesting to follow. Another big news from OpenAI themselves is, as we mentioned last week, they've launched GPTs and they've launched GPT-4 Turbo with a lot of new capabilities. And that dramatically increased the demand for ChatGPT. So OpenAI had to pause new subscriptions and upgrades to GPT+. So if you had one, meaning the paid version of it, you could keep on using it with some issues as far as access and availability that I at least experienced. And I know a lot of other people who did. But if you did not or still do not have one, you cannot upgrade to the paid version currently because they have bandwidth issues.

1:01:52So this is before they've let their CEO and probably some leading engineers walk away. They were experiencing peak demand for their product and service. At the same time, their backer and close-ups partner, Microsoft, has held their Ignite event, and they've made some huge AI announcements. The biggest one is probably the launch of Copilot Studio, which is a no-code automation system that runs within the Microsoft environment that allows anyone with the right privileges within the system to create new advanced chatbots that can connect to multiple sources of information from within the organization and outside the organization as well.

1:02:35and deploy those within the business to allow people within the company to ask questions that connects the dots across multiple aspects of the business. This is obviously an extremely powerful capability that will become available to Microsoft co-pilot users. If you connect all the announcements together, you learn that everything in Microsoft is going to be called a co-pilot for something, which will be the theme across everything that they're going to deploy with AI, both on the end user level, as well as on the enterprise level. Another big announcement from Microsoft was that they're adding multiple models to Azure as models that people can use with their data.

1:03:18These models include Mistral and Jace and Lama and NVIDIA, Nemotron and Stubble Diffusion and Clip and Whisper version three and Bleep and Sam. So some of these I've never even heard before, but they're going to become available to people who want to use these models with their data that is stored on Microsoft Azure. We've seen similar moves from Amazon and from Google, allowing multiple models to run within their hosting environments in order to allow maximum flexibilities to the companies who are hosting the data with their platform or that wants to host their data with their platform. There's some other news from this past week that I'm not going to share.

1:03:58And as I mentioned, I'm going to start recording Friday episodes with more news in a much shorter format. If you enjoy this episode, please give us a five-star review on your platform. It allows us to get to more people and bring bigger guests so you can learn more stuff so everybody wins. And until next time, have an amazing week.

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