On June
11, the Intelligence Advanced Research Projects Activity (IARPA) posted a request
for information for seeking data sources for technology performance prediction.
Responses are due by 4:00 p.m. Eastern on August 6.
IARPA is
exploring methods to predict the future performance of critical technologies.
Making and evaluating such predictions will require historical data on
technologies’ performance over time, ideally over the span of decades (e.g.,
the TOP500 dataset illustrating computation performance improvements).
IARPA requests information on:
– Datasets that document the historical performance of technologies. Datasets must have historical coverage of at least a decade and, most importantly, have accurate information on when the technology was first developed. For data about products, first development of the technology means “first offered for sale”. For data about pre-commercial or non-commercial technologies, date of journal publication or other public disclosure will be defined as first development. A temporal resolution of at least 1 year is needed for any data occurring after 1900; earlier data may have coarser temporal resolution.
– Performance metrics for technologies. These must be objective, quantitative, and recoverable from the historical record. Many performance metrics will likely be multi-dimensional and represent tradeoffs in some aspect of the technology (e.g., FLOPs per Watt).
IARPA is interested in all areas of technology, but
particularly the areas of:
·
Artificial Intelligence
·
Collection & Sensing
·
Communication
·
Computing
·
Cybersecurity
·
Energy & Power
· Human
Performance Modification
·
Materials
·
Quantum Sciences
· Space Sciences
Full information is available here.
Source: FedBizOpps
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