At JPMorgan Chase & Co., a learning machine is parsing financial deals that once kept legal teams busy for thousands of hours. The program, called COIN, for Contract Intelligence, does the mind-numbing job of interpreting commercial-loan agreements that, until the project went online in June, consumed 360,000 hours of work each year by lawyers and loan officers. The software reviews documents in seconds, is less error-prone and never asks for vacation. Attendees discuss software on Feb. 27, the eve of JPMorgan's Investor Day. While the financial industry has long touted its technological innovations, a new era of automation is now in overdrive as cheap computing power converges with fears of losing customers to startups.

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I imagine if we were sitting in a room decades ago as farmers, we would rightfully be worried about our future employment. However, as the world evolved, new jobs were created in industries we never would have fathomed would exist. Brent Schutte is the chief investment strategist of Northwestern Mutual Wealth Management Company. Today Americans seem to be at odds with themselves when it comes to their feelings on economic growth. People are worried about a future lack of economic growth due to a less productive workforce.

Applied machine learning

Telecommunications firm Verizon has acquired Skyward, a drone operations management company. Skyward develops software for drone operators to manage flight tracking and logging, maintenance scheduling, and contract management. The drone startup will join Verizon's Internet of Things portfolio. Kenya's government has implemented regulations for commercial drone use. The Kenya Civil Aviation Authority will begin allowing businesses to import and use drones for a range of operations.

During a typical day, we use a variety of applications that, by virtue of their artificial intelligence, automatically understand our speech and provide near-real-time feedback to support decision-making. But is machine learning, one of a number of AI techniques, ready for clinical applications, specifically to accelerate drug development and/or reduce development costs? Machine learning encompasses a variety of algorithmic techniques that clinical drug developers can use to identify and infer patterns to support enhanced/automated decision-making. One such technique is Natural Language Processing, which can be used to "read" scientific text and infer its semantic context in order to search and find information more easily. The main benefit of machine learning and natural language processing is that they can be used to either augment or replace the error-prone manual analysis work performed by people, and they can scale infinitely as the volume and variety of data grow.

Baidu's SVAIL used the ring allreduce algorithm to train state of the art speech recognition models, and now it hopes that others will take advantage of the group's implementation to do even more interesting things. The group released its ring allreduce implementation as both a standalone C library as well as a patch for TensorFlow.

Are you chatting with a human or a bot? Chatbots increasingly make it hard to tell. Chatbots are getting a lot of attention in retail these days. At the NRF Big Show in January, several vendors, startups and established alike, featured chatbots in their booths at the show. They could do everything from interact with you about new products and what you liked about them, to help you figure out the opening hours of your local store.

Artificial intelligence (AI) is here and it is getting smarter all the time. For many, mention of AI immediately conjures up images of The Terminator. At the very least it makes many think of robots and machines disrupting the workforce and replacing jobs. While the latter may not be completely out of the realm of possibility, datapine is leaving that side of AI to Silicon Valley and John Connor. Instead we are excitedly monitoring and utilizing artificial intelligence in business intelligence.

Artificial intelligence (AI) has the power to change how our workforce operates, and if you want your business to stay competitive, you need to get ahead of the AI revolution. Don't let yourself feel daunted by it as a buzzword. At my current company, we've seen firsthand the renaissance of AI, neural networking, big data and machine learning over the past five years. Not only do we provide automation and analytics for clients, we've now started to incorporate AI into our product development and operational automation. A study by McKinsey found that 45% of all on-the-job activities could be automated by deploying AI. Google's Jeff Dean estimates about 10% of its engineers know machine learning, and he'd like that number to be 100%.