As AI and machine learning systems advance, real-world applications are exposing limitations such as the inability to adapt to situations beyond the narrow tasks those systems were trained to perform. Indeed, some observers note that AI researchers still do not understand the mechanisms by which automated systems learn. As AI researchers grapple with these unknowns, the Defense Advanced Research Projects Agency (DARPA) launched a program last year aimed at advancing "lifelong machine learning." This week, the research agency announced funding for three university research teams that will tackle various components of the adaptability problem. Those efforts augment initial research at Columbia University focused on reproducing neural networks.

Amazon.com, Inc. (NASDAQ:AMZN) completed a discrete acquisition, last fall, when it took over Sunnyvale California-based artificial-intelligence (AI) startup Orbeus Inc. Bloomberg cites sources that claim that Amazon has absorbed almost all of Orbeus' workforce in its own teams though the financial terms of the acquisition deal remain undisclosed. Orbeus is known for applying machine-learning tools on image processing. Prior to its takeover by Amazon, Orbeus had an AI tool under development that could use neural networks to identify, and categorize the content in various images. Its customers were mostly developers, who could purchase its image-processing application programming interface (API) called, ReKognition. The startup also designed an Android and iOS app called, PhotoTime which helps tag photos instantly.