News

Refine Results

(Filters Applied) Clear All
From left to right are Melva James, Stephanie Carnell, Jonathan Su, and Neela Kaushik, the team developing Adaptable Interpretable Machine Learning (AIM) at Lincoln Laboratory. Photo: Glen Cooper

Replacing black box machine learning with interpretable models

September 4, 2018
TbD-net solves the visual reasoning problem by breaking it down to a chain of subtasks. The answer to each subtask is shown in heat maps highlighting the objects of interest. This process allows analysts to see the network's “thought process.”

A new artificial intelligence system solves problems through human-like reasoning

September 4, 2018
Mike DiLiberto leanes next to the MicroMAS-2A cubesat.

MicroMAS CubeSat technology provides a fresh approach to weather forecasting

August 13, 2018
Pictured is the undersea vehicle emitting a beam.

Lincoln Laboratory advances undersea optical communications

August 1, 2018
The Wide-Area Infrared System for Persistent Surveillance was named one of the R&D 100 Award winners. This interior view of the system shows its lens and the folding mirrors.
Awards

Lincoln Laboratory receives six 2017 R&D 100 Awards

December 6, 2017
During the two-day hackathon, staff were challenged to quickly train and test machine learning algorithms to detect fake media content. Photo: Nicole Fandel

Using machine learning to detect fake news

October 3, 2017
Microfluidic devices for performing various assays were created with the tools in Lincoln Laboratory's Technology Office Innovation Laboratory.

Makerspaces could enable widespread adoption of microfluidics

April 18, 2017
71-77 of 77