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April 01, 2021
Welcome to our blog! We are excited to share what we are working on and what we are thinking about. As a theoretical research team at an industry leading software company, we get to look at solutions and approaches that are not only new to us, but also new to data science in general.
Because the CallMiner Research Lab has a wide field of vision, we find some very cool and interesting stuff. Not everything we will share here has a direct path to product, and some of it will not be what a user sees directly, but that won’t stop us from sharing. Browse, pick what interests you, and thanks for looking.
We are probably all familiar with the term R&D. The CallMiner Research Lab represents the research in research and development for our company. That is not to say we are the only group doing research at CallMiner, and certainly not doing all the development work for the software. That is what a software company calls “operations,” and it is what the entire company does.
R&D at CallMiner is comprised of long-term and near-term research conducted by the AI Research team, and a second team that turns near-term into a reality through prototypes our Operations can see in action. That team is called Research Engineering.
It is most accurate to think of the CallMiner Research Lab as two parts that form a whole. The AI Research team consists of mathematicians, linguists, neuroscientists, physicists, and programmers working together to add cutting edge science into CallMiner's platform. This team is focused on the art and discovery of the possible relating to artificial intelligence and human conversations. The scope is very broad, and there are very few constraints.
We are researching six months to two or more years in the future. Each data scientist and research engineer on the team is working on research based in client use cases, as well as free research on the latest advances in our field. Our role is to figure out how machines can achieve outcomes that have yet to be discovered or used on conversational data. While very broad, this unconstrained approach is quite successful, assuming someone can turn it into reality.
Enter Research Engineering. This team takes a theoretical concept that is proven to work by AI Research and turns it into something more real. Something grounded in reality, which Product and Operations can work from, Research Engineering is responsible for supporting AI Research’s connection to both the architecture of the CallMiner Eureka platform, and the data of our industry, along with illustrating the value of a new technique or algorithm in a real-life situation or prototype.
In addition, Research Engineering also conducts technical research. Focusing on finding new or improved third-party technologies that may move us forward by adopting them into our ecosystem. The team serves as the handoff point between the theoretical value of a solution from the AI team and the practical application of the solution into CallMiner Eureka by the Product team.
In many cases, we put our heads together to gain perspective on issues. In particular, this is the case when we think about the ethical implications of the work that we produce. While we cannot know how a user base will ultimately use our tools, we can make sure that we are using diverse training data that represents real world populations, allowing for transparency in our models, and fleshing out any potential places for biases or unfairness in our models.
While we cannot be perfect every time, we know that AI ethics is a group effort from idea conception to product release, and the ethical considerations we take help make our product better.
The CallMiner Research Lab is all about diversity. We focus on a diverse team not only in background, but also in education and approach. Each person on the team adds a unique perspective and skillset, supplementing each other's gaps, building strength through the diversity. The Lab is supported by an array of skilled humans in the whole of the company such as DBAs, IT support staff, Client Success Directors as well as machines including but not limited to, powerful GPU’s, a massive SQL architecture, DataRobot for AI Automation, python/anaconda for development.
This is important as this team trains and teaches machines to solve problems. Diversity and inclusion with the right technology is a weapon against ineffective solution wrought with bias or poor designs.
Our diversity is also reflected in the thought pieces here in this blog, not only in voice, but in approach to the problems that the CallMiner Research Lab is solving. We hope you enjoy our thoughts and following along with the research that will continue to drive our product forward.
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