By Keerthy Kusumam
September 2020 – January 2021
I interned at BlueSkeye AI, a company that delivers ethical AI for supporting mental health for the vulnerable population using facial and voice behaviour analysis. The long term vision of BlueSkeye AI is to ’Create AI you can trust for a better future, together.’ The goals of my PhD aligns perfectly well with that of BlueSkeye, where comprehending various facial behaviours to recognise markers of mood disorders forms a core part of the work. The company BlueSkeye AI is cofounded by my PhD supervisor Prof Michel Valstar and the teammates include several of my past PhD colleagues. The following pointers are my reflections on my four-month-long internship at BlueSkeye AI.
The joy of building things that work. The internship at BlueSkeye rekindled my enthusiasm to build systems that work in the real world, face real challenges, and create real impact. When I joined, BlueSkeye AI had a product that was going to be released to the market and what I had to build would then be integrated into this product. That made it extremely well-defined as a problem, where we were not trying to define a problem itself but rather engineer a solution that needs working on real-world data, leveraging the cutting-edge computer vision/machine learning research.
Real World Vs Research World. My emphasis on real-world data stems from my divided self where I am both a computer vision researcher as well as a roboticist. Before doing my PhD I spent nearly 4 years in a robotics research lab with an active collaboration culture – where everyone in an open-plan workspace contributes to projects irrespective of their original funding sources. This cultivated the exchange of ideas across disciplines – computer vision, cybernetics, robotics, reasoning, machine learning etc leading to very creative and interesting bodies of work. In robotics, computer vision is often a tool that it relies upon to make decisions, which means robustness and consistency precedes accuracy. In computer vision research, however, beating the state-of-the-art on benchmark datasets seems to be the key marker of success. I enjoy both these aspects and the internship opportunity at BlueSkeye AI gave me just that – a place to bring those together. I got to build a computer vision-based social gaze estimation system that works on a smartphone. The challenge was about finding the right balance between exploration and exploitation. Here I had to optimize for efficiency, usability, practicality, simplicity and data efficiency along with the standard performance metrics that I use in research.
The Team and Teamwork. My onboarding was seamless, owing to the hands-on approach adopted by the BlueSkeye AI’s leadership. I was also familiar with the team, so I was lucky to enjoy an incredibly friendly and supportive environment. The weekly meetings where everyone discussed progress or the issues they faced, posed as learning sessions for me. I understood the value of communication and brainstorming from the team as a whole, to keep up the momentum. I worked in sync with the lead machine learning engineer who set up several documents and code specifically for me, that removed my roadblocks to integrate the module into a mobile device. I also learned how managing tasks in a time-critical manner helps save time and resources for the company as well as yourself.
Importance of values. One should never compromise on their values while working for a company and it is important to work in a place where value
systems align. BlueSkeye AI’s five-year mission is: ’To create the most-used technology for ethical machine understanding of face and voice behaviour that enables citizens to be seen, heard, and understood.’ I was astonished by their sensitivity towards mental health research, strict adherence to ethical guidelines while handling data, being transparent to the data volunteers about their data and having numerous clinicians with great expertise on board. Being part of the company albeit during a short internship provided me with a sense of purpose and I felt attuned to my values.
This blog was originally posted at here .