IARPA in the News


Depending upon your perspective Artificial Intelligence is stuck in the doldrums. Its long touted promise has yet to materialize and instead produced boom-bust cycles of grand expectations followed by disappointing results. Maybe the problem isn’t the algorithms but training data sets. This is the latest message from IARPA which has issued a request for information (RFI) for “Novel Training Datasets and Environments to Advance Artificial Intelligence.”


About 5 years ago, neuroscientist Tony Zador saw a slide at a scientific meeting that changed the course of his career. It showed a slice of mouse brain tissue containing a bright rainbow of neurons....Zador was struck by an idea: If he could replace the half-dozen distinct colors with a label consisting of, say, 30 random nucleotides—the building blocks of RNA and DNA—he could give unique barcodes to an almost infinite number of neurons.... The U.S. government is placing a large bet on Zador's method. As part of a project...under the Machine Intelligence from Cortical Networks, or MICrONS, program, sponsored by the Intelligence Advanced Research Projects Activity (IARPA).


In a new request for information, the Intelligence Advanced Research Projects Activity -- part of the Office of the Director of National Intelligence -- wants ideas for data sets, virtual environments and other training resources that could help artificial intelligence algorithms evolve.

The Tartan

Carnegie Mellon researcher Tai-Sing Lee, a professor in the Computer Science Department and the Center for the Neural Basis of Cognition (CNBC), will attempt to reverse-engineer the brain in order to try and reveal its learning methods and apply them to advancing machine learning algorithms....This research is made possible through funding from the Intelligence Advanced Research Projects Activity (IARPA) through its Machine Intelligence from Cortical Networks (MICrONS) research plan.


This month it was announced that CSAIL researchers Nir Shavit and Charles Leiserson will be participating in a cross-institutional consortium project at Harvard focused on brain-mapping. Merging the disciplines of data science and neuroscience, the Machine Intelligence from Cortical Networks (MICrONS) project aims to restructure machine learning through reverse-engineering the algorithms of the brain.

The Next Platform

Whether in the brain or in code, neural networks are shaping up to be one of the most critical areas of research in both neuroscience and computer science. An increasing amount of attention, funding, and development has been pushed toward technologies...Accordingly, the Intelligence Advanced Research Projects Activity (IARPA) in the U.S. is getting behind an effort spearheaded by Tai Sing Lee, a computer science professor at Carnegie Mellon University’s Center for the Neural Basis of Cognition, and researchers at Johns Hopkins University, among others, to make new connections between the brain’s neural function and how those same processes might map to neural networks and other computational frameworks.


Researchers are working to reverse-engineer how the brain’s visual system processes information in hopes of advancing machine learning algorithms and computer vision....The five-year, $12 million research project funded by the Intelligence Advanced Research Projects Activity are will be led by Tai Sing Lee, professor in the computer science department at Carnegie Mellon University and the Center for the Neural Basis of Cognition.