DD-AIM has developed a groundbreaking architecture that leverages a proprietary, patent-pending innovation to accelerate AI model inference running with unparalleled efficiency on novel hardware. This technological breakthrough enables computational speeds and reduced power requirements that vastly exceed current industry benchmarks, optimizing the real-world execution of AI/ML algorithms. 

Designed for high-frequency time-based predictive analytics using mixed numeric and text data inputs, our chip is poised to transform quant trading, industrial automation monitoring, global-scale ecommerce click analytics, and real-time event participant reaction observation.  Remarkably, we support self-optimization, in-situ re-training, new model downloads, and dynamic computational graphs on our ASIC (heretofore thought to be impossible) via our new on-chip data transfer technology.

The individual chips are so inexpensive to manufacture, plus so low in both energy consumption and heat generation, that a single SoC supporting thousands of ML ensemble constituents, along with sophisticated stacking-style data fusion, is now an economic reality. This type of deployment unlocks unprecedented predictive accuracy. with multiple variations of neural network deep-learning collectives and decision tree forests; these AI advances are well-understood in the lab, but with our invention they are now accessible to the practical business community.