If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Damage due to earthquakes poses a threat to humans worldwide. To estimate the hazard, scientists use historical earthquake data and ground motion recorded by seismometers at different locations. However, the current approaches are mostly empirical and may not capture the full range of ground shaking in future large earthquakes due to a lack of historical geological data. This leads to significant uncertainties in hazard estimates. Not only that, due to the lack of sufficient historical data, scientists mostly rely on simulated data, which is computationally expensive.
The very large majority of open-source MT efforts fail because they do not consistently produce output that is equal to, or better than, any easily accessed public MT solution or because they cannot be deployed effectively. This is not to say that this is not possible, but the investments and long-term commitment required for success are often underestimated or simply not properly understood. A case can always be made for private systems that offer greater control and security, even if they are generally less accurate than public MT options. However, in the localization industry we see that if "free" MT solutions that are superior to an LSP-built system are available, translators will use them. We also find that for the few self-developed MT systems that do produce useful output quality, integration issues are often an impediment to deployment at enterprise scale and robustness.
At Accelirate, an automation startup, few newcomers to the IT staff claim to be experts in critical areas like robotic process automation (RPA) or machine learning, but everyone has the chance to become one. The Edison, N.J.-based company, which was launched last year to assist companies on the automation track, is now up to 120 employees, 90% residing in IT, and it has debuted on Computerworld's annual Best Places to Work in IT list as the No. 11 small organization. Since RPA and related technologies are treading new ground, Accelirate found itself facing a dearth of expert talent, which could put a damper on its plan for fast-paced growth. The solution: building an in-house, three-month training program that gets all new IT hires, both first-time job holders and seasoned veterans, quickly up to speed. "Not too many people have prior experience with the platforms or technologies we were working with -- finding someone who'd done RPA before was few and far between," says Ahmed Zaidi, Accelirate's chief automation officer.
Big data, analytics, and machine learning are starting to feel like anonymous business words, but they're not just overused abstract concepts--those buzzwords represent huge changes in much of the technology we deal with in our daily lives. Some of those changes have been for the better, making our interaction with machines and information more natural and more powerful. Others have helped companies tap into consumers' relationships, behaviors, locations and innermost thoughts in powerful and often disturbing ways. And the technologies have left a mark on everything from our highways to our homes. It's no surprise that the concept of "information about everything" is being aggressively applied to manufacturing contexts.