Accelerating Predictive AI

DD-AIM has developed a patented innovative design for a digital circuit (chip) targeted at the next emerging trend in practical applications of artificial intelligence/machine-learning - PREDICTIVE AI at massive scale: thousands of simultaneous models and millions of inference runs.

Our chip is focused on the inference side of the deep learning/big data revolution -- collections of models all working together to monitor, evaluate, and forecast ("nowcast") real-world systems in real-time, generating money-saving, possibly life-saving alerts.

The chip, while packaged in an ASIC ("Application Specific Integrated Circuit" - considered by the industry as a non-modifiable component), can self-learn, self-optimize, and self-correct hardware or model errors through novel memory management and dynamic computational techniques, while all the time communicating with on-prem or cloud-based servers to upload or download AI-driven model improvements and/or respond to data input drift and distribution changes, doing in situ retraining as necessary.

The ability to scale big-time actually unlocks innovative AI/ML techniques that can crack previously unapproachable problems.

In addition, the fundamental architecture of the chip has been dramatically simplified to bring manufacturing and deployment costs way down, focusing especially on very low energy consumption (along with small physical size/weight and low heat generation -- what the experts call SWaP-C² ("Size Weight and Power - Cost/Cooling") which is a major concern of the entire AI ecosystem.

We are actively pursuing our go-to-market strategies

Defense

Suites of cognitive sensors have become the mainstay of electronic warfare and signals intelligence operations, but machine learning hardware has not kept pace with computational demands. Our chip fixes that bottleneck, enabling real-time processing of signal data.

Healthcare

Continual patient status monitoring is the new standard-of-care, but too few institutions have this fully automated. Our chip solves this, requiring human intervention only to respond to critical alerts. Integration with EHR systems will be straightforward.

Finance

Using our chip, quant and algo trading firms can dramatically improve, flex, and scale up their current AI/ML models to profit from overlooked alpha. The technology enables faster backtesting, real-time analysis, and deployment of sophisticated trading strategies previously impractical.

Retail

In typical applications, 200,000 SKUs and 2,000 stores must be analyzed, but these volumes can only be handled by today's AI/ML systems at aggregate levels. The problem is that aggregation negatively impacts accuracy. Our technology allows each SKU/store combination to be handled independently.

There will emerge an Industry Leader for Predictive AI Inference Accelerators

Can Be That Leader

We invented the chip by marrying four disparate disciplines. We have on our team:

An expert engineer who was a key developer for the original message routing software initiative at ARPANET (the precursor to today's Internet).
A pioneer in data collection, data transport, data security, and data governance at scale for global deployment in real-time mission-critical systems. Engineering & Applied Sciences graduate of Harvard.
A renowned inventor of a fundamental procedure in multivariate statistics, winner of the Theory and Methods Award from the American Statistical Association, Ph.D. in Statistics, Yale
A UNIX expert well-known for the original programming of commercially released time-series forecasting and state-change prediction algorithms still in use today by central banks worldwide. Winner of the Technometrics Wilcoxon Prize, Ph.D. in Statistics from Princeton.