Dynam.AI Brings Contextualized Machine Learning Capability To Industrial Sector


Dynam.AI, an artificial intelligence (AI) software development firm automating critical decision-making for the industrial sector, has announced a groundbreaking capability available to all clients: Context Augmented Machine Learning (CAML).

CAML leverages scientific “first principles” and the laws of physics, human behavior, and macroeconomic conditions to simulate the physical world for more realistic, trustworthy analytics. This allows industrial businesses to automate manual processes, improving their critical decision making and increasing ROI with fewer resources. Dynam.AI’s in-house development platform, using the patent-pending CAML method, has been proven to speed up AI model development for clients by up to 65%.

CAML combines existing data and models to expand features for analysis, introducing common-sense information that a human would innately use but a non-human algorithm would not, such as the laws of physics. It allows Dynam.AI to do two important things for clients: 1.) create richer data models for AI solutions that are smarter and better able to adapt to the real world, and 2.) solve data “cold cases” that traditional machine learning methods are unable to crack.

CAML aids developers and data scientists who are working on projects in object detection, medical imaging, sensor fusion, predictive diagnostics, satellite, and aerial imaging, thermography, anomaly detection, and much more. This capability has allowed Dynam.AI clients to solve long-standing problems with image and sensor data, developing solutions up to 65% faster.

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