In the realm of data analysis and business intelligence, AnswerRocket has been at the forefront of innovation for over a decade. Founded in 2013 with a vision to provide an intelligent agent to assist business users, AnswerRocket has continually evolved its capabilities. In a recent interview, Pete Reilly, CRO, and Mike Finley, CTO, highlight the transformative impact of GPT (Generative Pre-trained Transformer). GPT has propelled AnswerRocket closer to our goal of developing an intelligent AI assistant that collaborates with users, providing meaningful insights and driving decision-making processes. By harnessing the power of natural language search, automation of analysis, and advanced narrative generation, we’re revolutionizing how business users access and comprehend complex data.
Watch the video below or read the transcript to learn more.
How has GPT enabled AnswerRocket to create an AI assistant for data analysis?
Pete: Look, we started with a pretty lofty vision that we wanted to be able to provide this thing that’s an intelligent agent to help business users with data analysis. And we started the company in 2013 with basically natural language search. We moved into automation of analysis, incorporating data science and machine learning. We moved into generating stories to go along with that, to help business users understand what was going on under the covers. And so what GPT has done for us is a few things. One is it’s made it even easier to understand what it is that the user is asking for and how we can quickly solve the problem for them. It’s making the narrative that we build even richer, more meaningful and understandable by the business user. What I would say is it’s opened up the door to really, first of all, bring us much closer to that vision of this intelligent agent number one, because of the user experience. But number two, what it’s done is it’s really opened our eyes to oh, this is how we’re going to unlock. 20% of the data that companies have is in these structured databases, 80% are in these unstructured sources. And so what large language models are really good at is understanding these unstructured text oriented documents, emails, PDFs and so on. And so what that does for us is it opens up our ability to provide a much more robust analysis to the users much more broadly than we can do just out of what data happens to be cleansed in a structured database. And so it significantly enhances our ability to provide a much more meaningful insight that business can act on to drive their business forward.
How does GPT serve as a bridge between users and their data?
Mike: AnswerRocket has the ability to gather all of the right data to produce an answer and the business user has in mind a question that they want answered. GPT bridges the gap between those two. It allows the understanding of the question that the user has in mind and it allows the retrieval of the information that AnswerRocket can provide. So it’s that perfect bridge and it serves both to help AnswerRocket understand that business user, but then it also helps the business user to in turn understand AnswerRocket back. That combination is really what makes something that might have been a dashboard retrieval in the past become a conversation in the future. It’s what really transforms, let’s call it an extraction with analysis and maybe a report into an engagement with an analyst, with an agent that’s working on your behalf. Ultimate vision for AI assistance. So fundamentally we would like for the AI to feel like a collaborator, like somebody else on the team who can be sent away to do a task, research, summarize, make conclusions, build a presentation and return that back for evaluation. So essentially every human employee becomes an executive and that executive is managing a resource which is a set of AI agents that’s the vision where we think it’s going, then that happens. Of course, as the models get larger. GPT-4 is an example. It’s able to take in more data, simultaneously begin to more closely approximate the decisions people would make. Also, as the models get trained on deeper concepts in business, they become more able to provide a level of expertise that they don’t have. Now, let’s face it, these models have expertise around crafting language, around understanding history, the topics that they would find if they were searching through the training data that were provided, which is off the Internet and contracts and a few other things. As these models get trained more specifically on problems within businesses, we’ll see them go from passing the SAT to passing, let’s say, a very sophisticated test that a business might give to an executive who is a category manager or who is somebody who manages pricing, somebody who’s in charge of purchasing, right? So these agents can become much more like a partner to those people and less like a simple tool that’s used to refer to facts.
Are we finally getting our own J.A.R.V.I.S.?
Pete: If you remember the Tony Stark movies, he has this assistant, J.A.R.V.I.S., that helps him do all sorts of things, right? If you asked me a year ago how far away from having that, I would have said probably something like 20 years. And I don’t know where it is now, but I can tell you it feels a whole lot closer than it did at that time. And that’s really what I think at the end, we sort of aspire to is that level of capability, that level of intelligent agent that’s helping people at whatever level they are in the company, whether they’re just managing Google Ads or whether they’re running entire sets of operational components of the business that they have that level of assistance that’s really knowledgeable about their business can help them map out scenarios and can help them really start to think about making recommendations about what should be done. I think we’re much closer to that than ever before.
Conclusion:
Through the incorporation of GPT and advanced language models, AnswerRocket has embarked on a transformative journey, creating an intelligent agent that understands users’ needs and effortlessly retrieves essential information. With an eye towards the future, AnswerRocket envisions a world where AI is not just a tool but a collaborative AI assistant for every business executive, providing comprehensive analyses, strategic recommendations, and expert-level insights.
To learn more about what AnswerRocket is doing in the analytics space with generative AI, visit AnswerRocket.com/Max.
