Introducing Artifacia Research

Hi there. When we started Artifacia this year with singular focus on cracking visual search we didn’t know how far we would go and how much time it would take for us to arrive at the best possible solution for this problem. We believed the problem was long unsolved and our personal experiences somehow brought us together to take a shot at it.

The company we built around solving the problem was named Artifacia. Over time, we realized that the understanding of the problem is way more important than the solution itself. The visual search platform we created evolved into a leading visual intelligence platform based on feedback from our early adopters. As we dived deeper, we came across valuable insights about search, mobile and user experience while interacting with our end users and customers and realised that there was a lot we could do. We started seeing use cases beyond the obvious for our technology platform and thought we could play a much bigger role in society as a company investing in HCI (human computer interaction) technologies. However, as an early stage startup we also needed to be very focused and not waste our limited resources in things that wouldn’t take us from A to B.

I personally have had a strong belief in the long term importance of research in technology companies. Maybe this stems from my background in Physics and how an observation and experiment driven approach leads to great discoveries. Even when we had very limited resources with us and there were uncertainties about our product market fit, I asked the team to keep on investing some of their time on problems that interested them without worrying about immediate use cases. These were small side projects. It was all ad hoc but it worked well for us as we grew up as a company.

Now that we have a great bunch of people backing us, a fantastic set of customers working with us and an incredible technology team consisting of engineers and scientists, we wanted to structure the company in such a way that research and platform teams could be made loosely coupled entities for maximum throughput as an innovation driven company. We believe this approach will help us push the best of AI research into our products and keep them ahead in the market in terms of quality and innovation. Moreover, we wanted to emerge as a prominent research group in AI and contribute back to the community with open source code, tutorials and research papers.

At Artifacia Research, our areas of interests are going to be all major areas of research that are related to or build on top of Artificial Intelligence. Those include computer vision, machine learning, reinforcement learning and natural language processing for now, and embedded systems and robotics later. As for the underlying technology, we are currently investing our time and resources in deep learning networks such as convolutional neural networks, recurrent neural networks and memory networks. We see Artifacia Research emerging as a new destination for some of the topmost research engineers and scientists in Artificial Intelligence over the next couple of years.

Thanks for reading. And watch this space for a major announcement from us in the next couple of weeks.