Mosaic is thrilled to announce the selection of a NASA SBIR Phase II research project. In Phase II, Mosaic will continue work to improve Unmanned Aircraft System (UAS) and National Airspace System (NAS) safety. Risks posed by sUAS to manned aircraft continue to increase as sUAS operations expand. To improve Read more…
Mosaic is thrilled to announce the selection of a NASA SBIR Phase II proposal. We will continue our work on the Cloud FMS project, read more about Phase I here. We propose to build a Cloud-Based Flight Management System (FMS), whereby safety-critical functions residing on the flight deck are separated Read more…
We decided to approach this problem as a similarity learning modeling effort. We used convolutional neural networks to train a model that takes an image or video as input and outputs a vector representation of the input, such that similar inputs will be close to each other in the vector space. The vector learning is driven by a triplet loss function.
Having an autonomous artificial intelligence (AI) system that can monitor individuals via facial mood recognition, vocal tonality analysis, proximity to one another, performance, biosensors, surveys, and more, and predict conflict before it is problematic could improve a unit’s cohesion and performance in missions both in space and in isolated environments on Earth.
This white paper explores how traditional models of the value of information (VoI) can be extended effectively to account for uncertainties presently inherent in gathering and analyzing big data. To illustrate the challenge, we explore the VoI an automobile manufacturer may derive by engineering a telematics system into its vehicles.
Mosaic is developing a machine learning based tool that assists corporate travel manages and business travelers in making the safest travel decisions possible.
Working in conjunction with subject matter experts, data scientists can swiftly apply statistical tools and uncover emerging trends. This is extremely valuable for companies trying to operate in a disruption. Not only will executives have an accurate representation of their present situation, but new products & services can be devised from these insights.
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 machine vision is a powerful technology that humans can employ to improve their decision making. These deep learning and AI techniques are not easily developed, and trained data scientists need to be involved in the translation of analytics to business insights.