THE RISE OF ARTIFICIAL intelligence has inspired both fascination and fear of the world to come. Some tech prophets envision a "singularity," in which advances in AI trigger drastic technological growth, while others imagine that autonomous machines will someday turn on their creators and destroy us. But when you're engaged in the science of machine intelligence, you understand that this is a false set of choices shaped by a misleading phrase. The term "artificial intelligence" was coined in 1955 to convey the concept of general intelligence: the notion that all human cognition stems from one or more underlying algorithms, and that by programming computers to think in the same way, we could create autonomous systems modeled on the human brain. At the same time, other researchers were taking a different approach.

IBM Chief Executive Officer Ginni Rometty sees proprietary data combined with artificial intelligence technology as the competitive advantage for companies going forward. When International Business Machines Corp. works with clients, it trains a unique version of its artificial intelligence technology, Watson, using proprietary data, and that information creates individual business insights that stay with the customer, Rometty said. That's how Watson is different from its competitors that offer similar services around data analytics and machine learning, she said Wednesday in a speech at the company's World of Watson event in Las Vegas. "We made an important architectural decision -- for all our clients, all their data, it's their accumulated knowledge," she said. Rometty said clients have praised IBM's approach.

Artificial intelligence is learning to take on an increasing number of sophisticated tasks. Google Deepmind's AI is now able to imitate human speech, and just this past August IBM's Watson successfully diagnosed a rare case of leukemia. Rather than viewing these advances as threats to job security, we can look at them as opportunities for AI to fill in critical gaps in existing service providers, such as mental healthcare professionals. In the US alone, nearly eight percent of the population suffers from depression (that's about one in every 13 American adults), and yet about 45 percent of this population does not seek professional care due to the costs. There are many barriers to getting quality mental healthcare, from searching for a provider who's within your insurance network to screening multiple potential therapists in order to find someone you feel comfortable speaking with.

IBM's Watson supercomputing AI, which previously beat human competitors at Jeopardy and even edited its own magazine, is set to impart some of its wisdom to another automated system: Slack's chatbot. It's all part of IBM's new Watson Virtual Agent effort, which allows Watson's intelligence to be imparted to all sorts of human interface scenarios. While the idea of having conversations with artificial intelligence might seem like a gateway to a Skynet future, chatbots are seen as a massive growth industry in the coming years. Watson is ahead of the curve in this area, so applying its level of conversational ability to something like Slack makes a lot of sense. As it stands, Slack's helper bot is rather simplistic.

Apple has revealed its completely redesigned MacBook Pro, the computer that it hopes can put an end to worries that about its future. The company unveiled the laptop as part of an event at its California headquarters. It also showed off a new TV app – but didn't update any of its desktop computers, as many had hoped, and showed off no new categories of products. The new computer is thinner, lighter and differently shaped from the old MacBook Pro. But the main change is the new screen that's built into the keyboard.

For example, AI and automation allow insurers to cut down on claim processing and underwriting times significantly and reap sizable cost savings. Tasks that once took months to finish are now accurately completed in the matter of minutes, opening the gate for insurers to focus on more complex and creative projects. Machine learning can help insurers and agents underwrite risk more effectively, using the large troves of customer data it has collected.

The robots that think: China's most advanced assistants go on show Artificially intelligent robots can now understand the way humans think. Pictured above, a child shouts at the companion robot'Canbot,' also on display at the World Robot Conference Above, a woman demonstrates the ability of Baxter, an industrial robot from U.S. company Rethink Robotics, to follow her hand movements Dubbed the'robot goddess', Jia Jia is being taught deep learning abilities, including understanding human language, and detecting facial expressions. When asked by an audience-member'What kind of skills do you have?', Jia Jia replied: 'I can talk with you. I can identify gender and age of people standing front of me, and I can detect your facial expressions' The humanoid robot is programmed to recognise human and machine interaction, with autonomous position navigation and services based on cloud technology.

Robots, self-driving cars, drones, bots and many IoT devices are becoming smarter with Machine Learning. She brings twenty years of digital transformation experience from building organizations, shaping new technology ecosystems and mentoring leaders at eBay, PayPal, Harcourt, and GTE. She is an advisor for Barcelona Technology School and select startups. She has an MBA from Boston University. Register for @[email protected] 'FREE' Before Friday!

When it comes to enterprise customer care, machine learning enables virtual assistant solutions to automate tasks that used to require a live agent: password resets, address and complex information collection, even sales support. Integrating machine learning into enterprise customer care opens doors to more flexible automated solutions. With the growing challenges and volume of customer interactions that most companies must handle, that flexibility, efficiency, and accuracy is exactly what's needed. By incorporating natural language processing, many of today's automated customer care solutions can more accurately understand what callers are saying.

The newest generation of machine learning-enabled applications is transforming how companies are using technology to get closer to customers, giving people more time for innovation so they can create even more valuable products and services. Consider Internet cafes that fill seats with streamlined ease using chat bots as digital concierges. Or supermarket shelves that let sales reps at consumer packaged goods (CPG) companies see exactly what's selling (or not) in real time -- no physical sensors needed. These are just a couple of the exciting machine learning demo spotlights in my video interview interview at SAP TechEd Las Vegas with Karsten Schmidt and James Rapp, both of the SAP Innovation Center in Silicon Valley. As I listened to Schmidt describe how customers, developers and others are interacting with HanaHaus 24/7 using chat bots to reserve space more efficiently, I was struck by how much this innovation redefines community.