The OpenAI Team Finally Reveals The BEST OpenAI o1 Use Cases

So in a private webinar today, OpenAI decided to release a short video in which they describe the best use cases for O1. They break down the limitations of the model and how you can use this to your best advantage. In the description, there's going to be timestamps so you can flick through the best use cases, but hopefully this video is of some value.

Today, teams use ChatGPT for several valuable use cases, from content generation to data analysis. During this research preview, we've learned from our customers that in the O series it adds the most value value in three areas strategy, research and coding. Let's talk about what this looks like. Starting with strategy, OpenAI01 Preview can break down complex problems into steps, consider different solutions, and walk users through its process. This makes a strong ideation partner on strategy development in business, operations, engineering, and more. We'll walk through a market expansion scenario in a live demo. Secondly, OWIN Mini is especially helpful with coding tasks, from writing code to other adjacent tasks. For engineering teams, the reason why the model is better at writing code is because it thinks before responding so it can plan out the structure of the code. I'll walk through an example of developing a front end application from the ground up. Finally, let's talk about research. Both O Preview and OWIN Mini show a summary of its chain of thought. This can be especially helpful in the research context, where researchers can verify its process and consider other paths it didn't pursue. We've learned about some strong use cases from experts in the STEM field, for example experts in genetics using reasoning to get you to useful information more quickly. Instead of coming through large amounts of medical articles, they simply asked ChatGPT specific questions related to genetic cases in order to get to possible causes faster in their field. It's impossible to be an expert in every gene and to keep all that information straight, which is where AI can help. Given I'm not an expert in these fields, I will focus my demo today on some research in the field where I'm slightly more familiar. So let's hop into ChatGPT Enterprise to walk through each demo, starting with strategy first. Along the way, I'll touch on a few things that our customers have found helpful that may help you too. Please bear in mind as I demo these as I'm using a live demo environment, so also know that because I'm using my demo environment, some things make it look a little bit different than yours and that's okay.

Let's dive in for the first examples that they talk about is of course strategy. I think this is one of the most important things in business because anyone can work hard, but your strategy is what's going to set you apart from your competition and allow you to win. And even if you don't have a business, you, you can certainly use this strategy to improve your personal life and achieve your personal goals.

So in our first example, I want to start with a strategy example. In this scenario, I want you to imagine that I've been tasked with coming up with an office expansion plan for my company to figure out where we should build our new office and in what market. In order to tackle something like this, it obviously requires a lot of real world knowledge, which is why I'm going to be using ChatGPT01 Preview as my model of choice for this prompt. Now, in order to get to my answer, I've given O1 preview a little bit of context. You can see here the type of business that I work for. Where do we already have some offices where what seems to be one of the favorites so far and some direction on some of the things that I want to make sure that it addresses. But I'm also leaving it fairly open ended in case there are things that I might have missed. And to be honest, a question or a task like this often has so many things to consider that O1 preview becomes a wonderful partner to help you consider different aspects of that challenge. So when I submit this to ChatGPT, one of the first things that you'll notice is that it kicks off its thinking and reasoning process. And if I expand this, you'll see each of the steps that it's taking in its chain of thought to start to come up with a plan for me to use for my office expansion. And so you'll notice gives me very robust set of details around the market potential of Paris, but it also calls out alternate cities, places like Berlin. Maybe we'll come back to that in just a moment. And some of the other things that I specifically ask for, things like market entry strategy, how to build a brand cache as a thought leader, very helpful stuff. Even calling out specific customers in market that I can go to. But one of the things I really love about this that I mentioned before is that it gives me additional areas to consider like acquiring talent in that market or building partnerships and alliances, even getting to things like financial planning and risk analysis. This becomes easily an area where I can think that there's many things I might not have considered and use O1 Preview to help me dig in further. So let's actually take this and do something that I've seen a lot of customers use this for, which is actually go going a little bit deeper. So let's dig into dig into Berlin as an option and just like before, it will kick off its own thinking and reasoning process and go through all sides of that potential challenge or option. Now I'll go into my next example.

The so if you are coding with O1, you always want to make sure that you're coding with O1 mini as that is the current model that is best optimized for actual coding use cases in this video you're going to see how they use O1 mini to actually some comprehensive coding.

I'll go into my next example where I want to switch gears into something where we Specifically optimize the O1 series for and that's on coding. Now you notice in this I've switched over to the O1 mini model and we've optimized the O1 mini to handle challenges around coding extremely fast and give a robust amount of detail. I really like this as a partner in coming up with addressing coding challenges and adjacent tasks because it gives me a really detailed step by step walkthrough so I understand each of the pieces along the way. And so in this scenario I want you to imagine that I've been tasked with coming up with a new web application from scratch with a couple of parameters, a node, JS backend and a react front end. And I may be familiar with some of the concepts, but I haven't done this in a while and I have a quick turnaround. So I'm going to use ChatGPT to help me come up with the plan for this. And so when I submit this one, one of the first things that you'll probably notice is that still does that same thinking, but the speed at which it performs its reasoning and consideration is much, much faster thought for a couple of seconds and that doesn't mean it detracts from the amount of detail. Quite on the contrary, we actually have a very robust set of information or walkthrough on each of the phases to actually bring this project to life. Project overview to actually getting the front end set up and running the application. And again going back to this, I've used this in my own personal usage. I've watched customers use this. This has been an amazing helper in trying to understand each of the steps that I'm going through, all of the packages that I need to install, how do I make sure that I have each of the file structures correct correctly set up? I'M literally in many cases copying and pasting some of this into my, into my own environment. But I think the most important thing here at this phase is that I'm getting a really good understanding of what is happening at each step. And as I keep scrolling, you can see it's quite a robust amount of information. I think the only other thing I'd want to highlight here is that again, if you start to dig into other areas, like let's connect this to an Azure database, it's going to be a really great partner in even taking that new challenge and adding it and sinking it into the current. The initial prompt that we had next.

Of course, is the world of research. Now, research might be quite difficult considering the fact that this model doesn't really have access to the Internet. It has quite the limited context window. But you have to remember that it has an extensive knowledge base and extraordinarily good reasoning capabilities. With that in mind, you can reason through certain problems to reach a decent conclusion that you may not have reached yourself. And they show this example in this video.

Okay, great. So in this third example, we're going to go over into the world of research. Now, in the presentation I mentioned I'm not an expert in genetics, so I won't be using that example for today. I don't have my PhD, but what I like to believe is that I'm a very attentive dog dad. And part of being an attentive dog dad is that I've been trying to research and understand the best way to give him a long lasting life. And that's usually through creating an optimal food. And so not being an expert in research, I can still use ChatGPT01 Preview to get insights on how I can learn more about ways to get him an optimal food and also consider areas that I didn't, didn't think about necessarily before. But I think one of the key things I'd love that I've found that recently researchers have used this for that I'd love you to walk away with is that it's really helping you automate a lot of the more long, long form or laborious tasks that are in the world of research. Not necessarily coming up with novel AI innovations or new inventions, but it'll help you work through that and give you areas to explore new concepts. And so I know some things here. I've given it some prompts of how I want, the goals that I want. I know a couple of things like omega 3 fatty acids are important, but I am open to other considerations. And again, helping me through some of those more monotonous tasks of creating research plans. And who knows, if I come up with something great, maybe it'll even give me insight into how I actually can make this into a product and bring it to other people. And so when I submit this, it, much like in the strategy example, take in a wealth of real world information, combine it with our capabilities around science to come up with a very thoughtful plan to then give me a step by step guide on how I can create that optimal dog food. Now, again, going back to before, I knew some things like omega 3 fatty acids were helpful, but this was immediately opened my eyes to things like the balance of the ratio for omega 6 fatty acids. I also started to think of using taurine prebiotics and probiotics. Interesting. I take those, maybe my dog should too. So in the area of research where I can go and explore those. But I also like that it pulled open each of the different phases of potentially bringing this to a real different a real product, including things like testing and validation, regulatory compliance. All right, maybe coming up with my own dog food line is not in the cards, but at least I have a path to go get a better dog food for my my good pup.

So here's where we have them actually talk about the use of O1 for mathematics. Now, they apply this to a specific scenario that is one for finance. But there's a clear disclaimer. O1 is not meant to be used for financial advice. And in my honest, extensive testing, while this model does a rigorous and comprehensive job of finances, it's not the model you can really use for any financial advice.

Okay. And so one final example that I wanted to use that we didn't talk about too much in the presentation, but I feel like it's helpful is around the world of mathematics. Now, for those of you that are familiar with ChatGPT or just LLMs in general, they've typically struggled with mathematics in the past. Things like counting the number of Rs in the word strawberry has been very challenging. Not the case anymore with the R01 series. Now in this example, I want to show you an example of how we're improving upon that and how we've actually optimized again O1 mini for tasks that are related to mathematics. And I'm going to be using a covered call option. Now, just one quick disclaimer. We don't intend for ChatGPT to be a replacement for a financial expert. Um, we also don't intend for this to be your guidance in the stock market, but hopefully it can. This can be illustrative of how we would perform some of these calculations. And the thing that I want you to make sure that you take away from this is you don't have to be a stock market expert to understand this, but knowing that you can still use ChatGPT for any style of prompt, no matter what your workflow is, even if it includes mathematics, and still feel like it's going to be very accurate in its response. And so for this one, I'm looking for a way to maximize my profit. And again, because we're using the O1 mini model optimized for math, it's going to reason through those different challenges quite quickly and come up with an accurate answer on how what my total maximum profit is. Now, for anybody in the industry probably looking at this and like that's not too challenging. Again, it's making improvements on math, which is a great step in the right direction. But I also encourage you to add your own variables. I've talked to other financial services experts and one of the things that they've been most impressed by is adding in additional variables for things like financial budgeting or in their role, specific related tasks. So take a look, see what you think, and let us know how we can make it even better. So let's go check back in on that first prompt where we asked about Berlin, because I have one last little Easter egg I want to show you. And if I click over here, it's obviously given me a very detailed analysis of Berlin over Paris, the different risks that we can encounter. So I'm pretty happy with what it's done. And what I actually want to do now is I actually want to turn this into something that I can share with my team. And so I'm actually going to use ChatGPT to toggle over to one of my other models, GPT4.0. With Canvas, I'm going to say, hey, let's create a canvas with a drafted email, including an executive brief, executive summary about Paris and Berlin as options for market expansion. And when I submit this, this will open up our prompt into Canvas to then create a format that works extremely well for using AI as my companion or my assistant in drafting my final propos I can go through here. I can make modifications, I can make edits to get to a finished, polished product that I'm really proud of sharing with my team and hopefully making it really easy for us to move into that new market. So let's jump back to the presentation. So those were a few examples of how the O1 series can be applied to a variety of use cases. I want to take a moment to highlight a specific customer, the Boston Consulting Group, who uses the O1 series across their teams to streamline their processes. For example, with the O series, ChatGPT Enterprise helps create logical, step by step plans for solving problems. It generates detailed views of market trends, requiring fewer iterations to get to the right level of detail, and shortens the amount of time to spend on desk research. And finally, they found that the O1 mini model accelerates the process of debugging code compared to all previous models. And these are just a sample of BCG's usage of the O1 series. We're looking forward to learning new ways that these models can be helpful in a work context.