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Marco_Casalaina
In mid-September 2024, OpenAI introduced a groundbreaking family of models known as o1, often referred to as "Ph.D. models" due to their advanced capabilities. Now accessible through Azure OpenAI Service, o1 represents a significant leap in artificial intelligence, particularly in reasoning and problem-solving tasks. We've seen the o1 models solve problems like counting the number of R's in the word "strawberry" and logic problems - but what does this mean for businesses?
One of the most remarkable features of o1 is its ability to do math and perform complex data analysis. Unlike previous models, o1 can calculate aggregate statistics, detect correlations across multiple datasets, and provide deep insights that were previously unattainable. To test its mettle, I decided to run the largest of the o1 models, o1-preview, through its paces, using datasets similar to those it might see in business scenarios. Note that the data used here is entirely synthetic, but it is patterned after real datasets that business might
use.
First, I tried a retail scenario. I took some example sales and staffing data, the kind a real store might have over a month and fed it into o1. I wanted to see if it could help figure out what's driving sales and how staffing levels impact performance. Well, o1 didn't disappoint. It crunched the numbers and pointed out that our sales were lower on weekends compared to other days. The funny thing is, the data didn't label which days were weekends, but o1 figured it out anyway. It found the correlations between the sales and staffing datasets, even though the only obvious commonality between them was the time period they covered. It suggested that maybe having fewer staff scheduled over the weekend would lead to lower sales, and even recommended upping the weekend staff or adding self-checkout kiosks. It felt like having a seasoned retail analyst giving me personalized advice.
Next up, I wanted to see how o1 handled financial data. I used a fictional company's financial statements - structured just like real income statements, balance sheets, and cash flow statements - and asked o1 to create a sell-side research report. The results were impressive. It put together a detailed report, complete with an investment thesis and justification. It calculated growth rates, analyzed profit margins, and looked into financial ratios like price-to-earnings ratios. It justified its price target with solid analysis. Clearly, financial analysts can use this tool to make their jobs easier.
Then I decided to try something in the entertainment sector. I gave o1 some sample ticketing data from a fictional event - just like the kind of data a real concert might generate. I wanted to find out who spent the most on tickets, and who bought the highest quantity. o1 not only identified the top spenders but also analyzed their buying habits and provided suggestions on how to encourage more high-volume ticket sales in the future. It was pretty cool to see how it turned raw numbers into real marketing insights. Even though I was using fictional datasets, o1 showed me its potential to make a real impact on businesses. It can help make better decisions by uncovering deeper insights, save time by handling complex tasks, spark innovation with its creative thinking, and help understand customers better to improve engagement.
Lastly, just for fun, I tested o1's coding abilities. I asked o1 to create a simple HTML page with a playable Space Invaders game written entirely in JavaScript. To my surprise, it generated all the code I needed. When I ran it in my browser, there was the game, fully functional and ready to play. It worked on the first try! It was like magic, and I didn't have to write a single line of code myself.
o1 has proven to be remarkably good at these sorts of technical tasks, but it turns out that its reasoning ability also extends to the creative realm. In fact, I fed it the transcript of the YouTube video I had created and prompted it to write this blog post (at least all the paragraphs above this one) - and it did! It took me four more little prompts to adjust the output to the tone I was looking for, but in just a few minutes, I had what I needed. So, as writing this blog post is one of my own business activities, the o1 model has now made a genuine impact on my business.
Why not get started?
Continue reading...
One of the most remarkable features of o1 is its ability to do math and perform complex data analysis. Unlike previous models, o1 can calculate aggregate statistics, detect correlations across multiple datasets, and provide deep insights that were previously unattainable. To test its mettle, I decided to run the largest of the o1 models, o1-preview, through its paces, using datasets similar to those it might see in business scenarios. Note that the data used here is entirely synthetic, but it is patterned after real datasets that business might
use.
First, I tried a retail scenario. I took some example sales and staffing data, the kind a real store might have over a month and fed it into o1. I wanted to see if it could help figure out what's driving sales and how staffing levels impact performance. Well, o1 didn't disappoint. It crunched the numbers and pointed out that our sales were lower on weekends compared to other days. The funny thing is, the data didn't label which days were weekends, but o1 figured it out anyway. It found the correlations between the sales and staffing datasets, even though the only obvious commonality between them was the time period they covered. It suggested that maybe having fewer staff scheduled over the weekend would lead to lower sales, and even recommended upping the weekend staff or adding self-checkout kiosks. It felt like having a seasoned retail analyst giving me personalized advice.
Next up, I wanted to see how o1 handled financial data. I used a fictional company's financial statements - structured just like real income statements, balance sheets, and cash flow statements - and asked o1 to create a sell-side research report. The results were impressive. It put together a detailed report, complete with an investment thesis and justification. It calculated growth rates, analyzed profit margins, and looked into financial ratios like price-to-earnings ratios. It justified its price target with solid analysis. Clearly, financial analysts can use this tool to make their jobs easier.
Then I decided to try something in the entertainment sector. I gave o1 some sample ticketing data from a fictional event - just like the kind of data a real concert might generate. I wanted to find out who spent the most on tickets, and who bought the highest quantity. o1 not only identified the top spenders but also analyzed their buying habits and provided suggestions on how to encourage more high-volume ticket sales in the future. It was pretty cool to see how it turned raw numbers into real marketing insights. Even though I was using fictional datasets, o1 showed me its potential to make a real impact on businesses. It can help make better decisions by uncovering deeper insights, save time by handling complex tasks, spark innovation with its creative thinking, and help understand customers better to improve engagement.
Lastly, just for fun, I tested o1's coding abilities. I asked o1 to create a simple HTML page with a playable Space Invaders game written entirely in JavaScript. To my surprise, it generated all the code I needed. When I ran it in my browser, there was the game, fully functional and ready to play. It worked on the first try! It was like magic, and I didn't have to write a single line of code myself.
o1 has proven to be remarkably good at these sorts of technical tasks, but it turns out that its reasoning ability also extends to the creative realm. In fact, I fed it the transcript of the YouTube video I had created and prompted it to write this blog post (at least all the paragraphs above this one) - and it did! It took me four more little prompts to adjust the output to the tone I was looking for, but in just a few minutes, I had what I needed. So, as writing this blog post is one of my own business activities, the o1 model has now made a genuine impact on my business.
Why not get started?
- Read the blog about o1 on Azure OpenAI Service
- Begin customizing your own agents with o1 using Azure AI Studio
- Review the Azure OpenAI Assistants quick-start documentation
Continue reading...