Automatically Curated Data Improves Training of Machine Learning Models to Produce Better Results

Today, Machine Learning (ML) and Deep Learning (DL) enable organizations to solve problems and perform tasks that, in the past, they haven’t been able to perform easily. ML/DL models learn what to do from operational data, with surprising accuracy, to help us make better decisions. But, there’s a catch. These models need a lot [...]

2021-05-31T20:05:41+00:00July 8th, 2020|Categories: Blog|Tags: |

Rite-Solutions and the University of Rhode Island Awarded Second Innovation Voucher from Rhode Island Commerce Corporation

Middletown, RI (September 16, 2019) – Rite-Solutions, Inc. is pleased to announce that it has been awarded a second Innovation Voucher by Rhode Island Commerce Corporation (RICC) as part of the Rhode Island Innovation Initiative program. The program helps businesses tap into the native R&D capacity here in the Ocean State. Rhode Island enterprises with [...]

2021-05-31T20:08:46+00:00September 16th, 2019|Categories: News|Tags: |

A Case for AI-Enabled Submarine Command-Level Decision Support System

I have long been a proponent of the use of artificial intelligence (AI) and deep machine learning (DML) to assist commanding officers (CO) with making faster, better decisions and to maximize the capabilities of today’s complex warfare systems. Due to the complex nature of today’s fighter aircraft, the Air Force already employs the use [...]

2021-05-31T20:10:04+00:00July 24th, 2019|Categories: Blog|Tags: |

Artificial Intelligence, Machine Learning: Innovation Imperatives for the Navy

Recently, the Defense Advanced Research Projects Agency (DARPA) released a very interesting Broad Agency Announcement (BAA) in which they challenged respondents to play the role of an adversary to the U.S. and describe what disruptive technologies they would employ against our nation. One area that has recently captured my attention is the use of [...]

2021-05-31T21:51:47+00:00February 24th, 2017|Categories: Blog|Tags: , , , |
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