Traditional lending practices are a prime candidate for machine learning improvements. Lenders can make more accurate and faster decisions by shifting decision-making from analysis of individuals to analysis of trends and patterns.
Natural language models have come a long way in the past couple of years. With the advent of the deep learning Transformer architecture, it became possible to generate text that could, plausibly, be passed off as written by a human.
Mosaic built an automated cooking prediction & optimizer using deep reinforcement learning to improve short term cooking operations.
Weather has a high impact on operations in many industries, and therefore is of great value to integrate into strategic decision making. Mosaic has roots in aviation research & development, giving us deep expertise in combining weather data streams with planning applications to facilitate efficient resource allocation.
Global external shocks are going to continue to happen, that is a fact of operating a business in today’s environment. As companies embrace data science in their decision-making processes, they are better positioned to deal with these disruptions, allowing them to manage a risk-optimized supply chain.
Designing and deploying computer vision is a powerful technology that humans can employ to improve their decision making. The only limits to these technologies lie within our ability to think of problems for them to solve.
Gameplay data are a trove of information about how athletes are acting and reacting in real situations, and there are real benefits to be gained by mining this information at every level, from the athlete to the entire team. In the modern age, the team that can measure and understand itself through its own data will have the competitive edge.