In the lead-up to the presentation of the awAIre AI Startup of the Year Award at awAIre, we’re taking some time to get to know the leaders of each of the 5 Finalists. Today we are talking with Dr. Helen Gu, CEO, InsightFinder:
Hi Dr Helen, Tell us a bit about yourself – what led you to get involved in the AI market?
The journey began when I was a PhD student at the university, University of Illinois at Champaign and my advisor was Clara Nash, a researcher in the field of quality of service and multimedia. My PhD research was about a kind of distributed system I called the service overlay network. My first research paper was about using a network to predict bandwidth availability on a mobile device and also predict the user preference – using your network to predict what kind of multimedia content you want to see on your device. This was a kind of neural network – a topic that was not as hot as it is today. This was just because people didn’t believe that neural networks could produce accurately enough. Now, many things have changed, right?
I think our vision did not change, but you know, that a lot of environmental factors changed, and today we have much more powerful machines. We have tons of data. And also the other things along the way that inspire me to continue research in this area. But since the beginning, my passion has been about building reliable, distributed systems.
What is the company uniquely bringing to the AI market?
InsightFinder uses AI to detect anomalies, specifically in the ITOps space. The amount and variety of data we use is increasing substantially. At the same time, consumer and business expectations are that services are 100% dependable, or else they will go elsewhere. So InsightFinder provides the right AI solution to quickly and accurately predict and prevent IT incidents before they happen.
What other factors make the company compelling?
InsightFinder’s AI solution is based on nearly 15 years of academic research and applied across companies of various sizes and industries. The technology is dynamic and flexible to handle many sources of data, and also operates on distributed architecture, so can ingest volumes larger than any competitor in the space.
How has the company been involved in the development of context & AI?
InsightFinder relies upon streaming data to make accurate predictions and identify probable root causes. In addition, it uses minimal training data, and focuses on unsupervised machine learning. InsightFinder allows users to provide input based on the results they see, so it learns from both human and machine inputs.
How do you see the Context & AI market developing over the next few years?
Our data problems will become increasingly complex, and we will need to rely upon machine learning to process massive amounts of data for automation, insight, and prediction We’re just at the beginning of what we can do by combining human insight with automation, and both InsightFinder and my research are geared towards making advancements in this area.
Thanks Dr Helen, and best of luck with the Award !
Register FREE to see Helen pitch-off with the other finalised for the Award at AwAIre on June 22nd.