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.
Mosaic Data Science is excited to announce its participation in the upcoming two-day webinar series titled “Future of Healthcare: Navigating AI Integration in Medical Devices,” hosted by the Focused Ultrasound Foundation.
Mosaic Data Science is proud to announce its participation in the U.S. AI Safety Institute Consortium (AISIC) through our collaboration with EBG Advisors, the consulting arm of national law firm Epstein Becker Green.
The “Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence” Executive Order underscores the need for responsible AI use to mitigate potential risks in the face of recent rapid advances in artificial intelligence, such as the launch of ChatGPT and other generative AI tools that have accelerated a global movement to regulate U.S. tech giants. Mosaic Data Science’s GenAI Readiness Assessment was specifically designed with the latest LLM hype in mind, packaging our expertise in using these models into a robust evaluation of use cases that can benefit from ethical AI implementation.
Mosaic Data Science and Epstein Baker Green discuss the importance of developing ethical algorithms that comply with anti-discrimination laws.
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.
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.
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
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.
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.
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