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All of our workloads at Ultimate.ai are containerized and we run them on top of our swarm clusters which are hosted on Google Cloud. Our CI/CD pipelines run on bitbucket. We use ELK stack for logging and grafana/moira for monitoring and alerts. We are now actively migrating to kubernetes.
AI
AI research uses a wide variety of different technologies, libraries and models to find the best solution for our business problems. The core tech stack is the same as in machine learning (Tensorflow, Python data science stack) and a lot of the code base used for our experiments is the actual production code for consistency and easier hand off from research to product.
The researchers are not limited in what technologies and solutions they use and explore but instead we are more interested in the results and getting our hypotheses tested in a quick fashion. Researchers make the calls about the technologies independently but also discuss the decisions with other members of the research team and with machine learning engineers to ensure continuity in research and compatibility and feasibility of production implementation.