Finding different, and more effective, approaches to developing artificial intelligence is clearly a large topic of interest to many researchers. Recently an international team led by Professor Khaled Nabil Salama of King Abdullah University of Science and Technology Sensors Lab, Saudi Arabia and Gert Cauwenberghs, professor of bioengineering and co-director of the Institute for Neural Computation at the University of California, San Diego had their research on "Inherently stochastic spiking neurons for probabilistic neural computation" presented at the 7th International IEEE EMBS Neural Engineering Conference (NER'15), Montpellier, France, and is detailed in "Memristors Empower Spiking Neurons with Stochasticity" in the June 2015 special issue of the IEEE Journal on Emerging and Selected Topics in Circuits and Systems on Solid-state Memristive Devices and Systems (DOI 10.1109/JETCAS.2015.2435512).
The research published explores the difficulty of building rational agents to solve different AI search, optimization, and inference problems, and especially in high-level cognitive tasks, such as natural language understanding, which do not have precise formalizations. It then goes on to provide potential solutions to this problem using the brain as a model and the technology of memristors and stochasticity as a potential solution.
Congratulations Maruan and Rawan!