From The Wall Street Journal:
Artificial intelligence, long a subject of fanciful forecasts, is starting to enter the corporate world in a much bigger way, as costs decline and the need increases to identify patterns within ever-growing troves of business data.
Once a mainstay of startups and big-tech firms such as International Business Machines Corp. and Alphabet Inc., technologies such as machine learning are taking a larger role inside corporate giants including American International Group and Fannie Mae, which are deploying AI to automate and augment tasks previously done by humans alone.
Chief information officers say the technology helps them complete routine tasks faster and often without human help, saving money while freeing their employees to focus on value-added activities.
But as the technology becomes both less expensive and smarter, and more advanced technologies continue to emerge, companies will extend AI use beyond routine jobs to aid in decision making and spot trends and patterns that wouldn’t be evident to the sharpest data scientist.
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Less expensive, more abundant data storage, increased processing power and advances in deep-learning technology could lower the cost of artificial intelligence and make it possible for machines to learn with minimal programming from humans.
One common deep-learning tool, the neural network, uses layers of interconnected nodes to roughly mimic the operations of the human brain.
Nova Spivack, founder of AI startup Bottlenose, said the latest versions of deep learning employ hundreds of layers of neural networks. That power can be used in areas such as weak-signal detection, or the ability to spot trends more quickly.
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AIG said it recently deployed five “virtual engineers” inside its IT infrastructure that work 24 hours a day collecting and analyzing system performance data and spotting network device outages. They work alongside human engineers to learn patterns in the network data and eventually act on their own to solve technical problems.
A network device outage, for example, typically would go to a queue and take human engineers about 3½ hours to address, an AIG spokeswoman said. Using the virtual assistants, nicknamed “co-bots,” there is no queue and most incidents can be fixed within 10 minutes, she said. If a machine can’t solve a problem on its own, it is kicked back to a human engineer.
Link to the rest at The Wall Street Journal (Link may expire)