While applications of deep learning have produced impressive empirical results, the theory behind it is still poorly developed. However, a team of researchers from Intel and the Hebrew University are saying that they have made an important breakthrough that allows for a better theoretical understanding of the capabilities of deep
AI is expected to create significant value for businesses in the coming years. Gartner predicts that by 2022, the value that AI contributes to companies will already total $3.9 trillion. Most of this estimated value is related to an increase in worker productivity. In addition to this, Micha Breakstone of
The US Department of Defense is making changes to its request for information on the Advanced Targeting and Lethality Automated System, or ATLAS, which states that the program aims to use Artificial Intelligence and Machine Learning to provide “ground combat vehicles with the capability to acquire, identify, and engage targets at least 3X
Recent surveys aiming to assess the current state of Artificial Intelligence (AI) point to four common trends. The first is that people’s attitudes toward AI are more positive than before, although skepticism remains when it comes to AI bias. For instance, 53% of respondents in a recent consumer survey by
Boeing has introduced the Boeing Airpower Teaming System, an unmanned aircraft that according to the manufacturer will provide “fighter-like performance,” and uses sensors and artificial intelligence (AI) to “fly independently or in support of manned aircraft,” while being able to “support intelligence, surveillance and reconnaissance missions and electronic warfare.” While
Given that we know AI and Machine Learning will be impactful in the enterprise, modern organizations would do well to develop an approach for securing their AI assets now.
The US Defense Advanced Research Projects Agency (DARPA) recently announced its Competency-Aware Machine Learning (CAML) program, which aims to “develop machine learning systems that continuously assess their own performance in time-critical, dynamic situations and communicate that information to human team-members in an easily understood format.” The idea behind this is
OODA Network Expert Michael Tanji provides insightful analysis of the most recent and significant cyber news.
OODA Loop is pleased to announce our latest members only series on Artificial Intelligence: OODA Research Report: When Artificial Intelligence Goes Wrong This report dives into what may well be one of the most significant limiting factors of the wide spread application of advanced AI applications in business and governments: the
Artificial intelligence (AI) research is rapidly bringing us closer to a new technological revolution. However, Computer Science professor Ben Shneiderman of the University of Maryland believes that in order to get the best out of this technology, researchers and engineers should be careful not to repeat the mistakes of legitimate scientists who got sidetracked