The National Defense Authorization Act report includes aspects on the Armed Forces Act and the provisions for artificial intelligence. “The complexity of 21st-century warfare requires that our armed forces be both technically skilled and proficient with their weapons,” U.S. Sen. Rob Portman said. New steps being taken by the Joint Artificial Intelligence Center and Defense Department are paving the way for more AI integration in the military.
Computer scientist Frederick Hayes-Roth has stated that our minds are very difficult to replicate and they constantly evolve and change. This requires scientists and engineers to work with multiple variables at once that are constantly changing. This also means that algorithms are often only able to perform a certain function, and it is difficult to make them do multiple things with the same programming and software.
Source: https://www.scientificamerican.com/article/will-artificial-intelligence-ever-live-up-to-its-hype/
GE Healthcare’s AI software platform can provide healthcare workers with applications to test their ideas and theories before implementing them. Data can also be used in clinical trials and to improve the outcomes. Edison Marketplace, a key component of GE Healthcare’s AI software platform, will now allow hospitals to test out their AI tools before purchasing them as well.
Source: https://hitinfrastructure.com/news/ge-healthcare-lets-hospitals-test-artificial-intelligence-tools
Psychologist Omri Gillath and his team of researchers from University of Kansas have published a new paper with findings that explore people’s trust in artificial intelligence and relationships. The research shows that people who are more anxious or worried about their relationships are more likely to have distrust in AI. Those who have enhanced attachment security are more likely to trust AI. These findings help drive the idea that you can predict someone’s trust levels towards other scenarios if they have concerns about their relationships.
As artificial intelligence continues to advance, there are emerging areas within AI and machine learning that are most likely to take off. One of these is neural network compression, where AI could run algorithms directly on a specific device instead of having to send data to a server, which increases the chance of a data breach. Generative AI is another segment that could explode in the next decade. Currently, machine learning models study existing data, whereas in the future AI could create its own novel content.
