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ExplainableAI

Traditional machine learning models like deep neural networks can be highly complex and operate as “black boxes,” making understanding the factors and reasoning contributing to their predictions challenging. Mosaic Data Science uses tools and techniques to make the decision-making process of AI systems transparent, understandable, and accountable to users, developers, regulators, and other stakeholders.

Case Studies

Explainable AI for Lunar Operations to Build Trust in Autonomous NASA Rover Exploration

Mosaic developed Explainable AI in Lunar Operations to support lunar rovers using imagery data from hardware to assist NASA rovers in assessing the traversability of a given region of terrain, supporting increasingly autonomous operations.

By Sel Gerosa, 2 monthsJuly 27, 2023 ago
Case Studies

Reducing Jet Fuel Emissions with Operational Artificial Intelligence

Mosaic helped a commercial airline integrate custom machine learning to predict departure runway and taxi-out time, cut operational costs, and improve the customer experience, aiding in reducing fuel emissions with AI.

By Sel Gerosa, 7 monthsMarch 14, 2023 ago
Case Studies

AI-Enabled Voice Search Assistant for Operating Manuals

Mosaic built a custom voice search solution using deep learning and state-of-the-art language models to intelligently parse complex mechanical operation manuals and return the desired search results

By Sel Gerosa, 8 monthsFebruary 10, 2023 ago
Case Studies

Using Predictive Analytics to Develop DNA-Based Pet Disease Risk Models

Mosaic has been working with a leading pet Biotech company on integrating machine learning into the organization’s products, giving pet owners more visibility into the quality of life their pets have by identifying genetic traits that may impact their health or behavior.

By Sel Gerosa, 9 monthsJanuary 10, 2023 ago
blue data pipeline image
White Papers

Production Machine Learning Auditing using MLOps

Successfully developing machine learning tools to provide value in a business environment requires much more than algorithmic knowledge and tuning. Machine learning cannot provide value in a vacuum.

By Drew Clancy, 3 yearsNovember 5, 2020 ago
Blogs

MLOps Tools, Tips, & Tricks: MLflow Model Registry

MLflow is open-source software initially developed by DataBricks for managing the “machine learning lifecycle.” It makes the model artifacts and their environment specifications more readily available when assembling ML model applications or for other purposes such as collaborating with teammates

By Drew Clancy, 3 yearsOctober 16, 2020 ago
White Papers

An AI Approach for Consumer Lending Approval & Pricing

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.

By Drew Clancy, 3 yearsOctober 16, 2020 ago
audit technology eyeglass
Blogs

Algorithm Quality Assurance via Auditing & MLops

Algorithms can be trained to mimic human behavior, but what happens when the human developing the algorithm inadvertently allows bias into the training process?

By Drew Clancy, 3 yearsMay 27, 2020 ago
predictive pharma analytics pill image
Case Studies

Predictive Modeling for Clinical Trial Recruitment

For many pharmaceutical firms, trial recruitment forecasting plays a role in trial recruitment planning. However, these forecasts may be generated with relatively simplistic approaches based on only a small subset of available internal & external data.

By Drew Clancy, 4 yearsJanuary 20, 2020 ago
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