Humanoid robots who are all named Pepper, are greeting shoppers in two Westfield malls in California. They will be at the malls during the holiday season and might go well beyond that, according to Steve Carlin, the vice president and general manager for Softbank Robotics America. The friendly robots welcome the shoppers to the mall, dance with them, or play games with them like card matching. The Pepper robots can also take selfies and teach six languages to anyone who's interested, as well as conduct a customer service survey. Pepper ready to welcome visitors (Image Credit: SFGate) There's no plan to replace human clerks with the robots, though.

A survey in 2013 by Vincent C. Müller and Nick Bostrom asked hundreds of scientists when they believe machines will achieve artificial general intelligence (AGI), meaning human-level intelligence. The median years for 10, 50, and 90 percent probability of reaching AGI were 2022, 2040, and 2075, respectively. But, there are still many challenges to reaching human-level intelligence. The first is domain limitation. Today's artificial intelligence primarily applies a mathematical approach that can solve a finite set of statements for a finite set of terms described under a finite set of rules.

Mobile internet applications are evolving rapidly. Cognitive computing technologies will inspire telecom service providers to profoundly change their business model in new creative ways. Deploying intelligent voice control apps on smartphones was just the beginning of this trend. As an example, mobile network operators are increasing their investment in big data analytics and machine learning technologies as they transform into digital application developers and cognitive service providers. With a long history of handling huge datasets, and with their path now led by the IT ecosystem, mobile operators will devote more than $50 billion to big data analytics and machine learning technologies through 2021, according to the latest global market study by ABI Research. "Machine learning-based predictive analytics are applicable to all aspects of the telecom business," said Joe Hoffman, vice president at ABI Research.

Customer: I want to know how to activate the voice mail service. Company: The voice mail service is already active on your SIM. Customer: How much does it cost? Company: The cost of the service, from your mobile phone in Italy is 12.40 cents per call. Here is an example for a conversation with a diligent customer service clerk at a telecommunications company.

Wireless carrier competition in the U.S. is white hot -- analysts increasingly see signs of wireless market saturation, meaning that growth is most likely going to come from competitors. Of the four major U.S. carriers, T-Mobile USA has led the way, slashing prices, killing the two-year contract and daring its competitors to follow suit. As competition intensifies, Finnish mobile technology provider Nokia believes customer service will emerge as an even more important key differentiator, and analytics and machine learning will take customer service to the next level in the U.S. and around the globe. In 2011, when AT&T announced its intention to acquire T-Mobile USA from Deutsche Telekom, it looked like the wireless market in the U.S. was well on its way to becoming a duopoly. Verizon Wireless and AT&T already held the lion's share of customers between them, and they both held licenses to the majority of wireless spectrum too.

We are on the verge of a very fast rate of technological change. If you think the Internet and mobile communications have changed the world, just wait. Coming years will be even more disruptive and amazing. When most people ponder technology they default to thoughts about compute power and its limitations. In 1965 Gordon Moore, the cofounder of Intel theorized that processing power should be capable of doubling every 18-24 months.

Network Mind facilitates the management of millions of network elements with millisecond response time and automatic adaptation and optimization based on service changes. Network Mind is therefore capable of helping telecom operators and enterprises achieve differentiated, self-adaptive control of complex services in ultra-large networks. The amount of network elements, data traffic, and types of service in communication networks is soaring as new technologies continue to emerge, including 5G, the Internet of Things, Software-Defined Networking, Augmented Reality, and Virtual Reality. This results in a level of network complexity that is impossible to manually control through defined rules. How automatic modeling can be used to realize intelligent network control and management is a major topic of study at many research institutions.

Google's Pixel is apparently a hit over at Verizon. That's a high number for a premium priced, first-time phone that isn't from Apple or Samsung. It indicates that the $15 million Google spent on advertising and $12 million from Verizon during a campaign from Oct. 27 to Nov. 2 is paying off. Google's ad campaign has played up the Pixel's photo prowess, while Verizon has regularly run an ad where a group on a train uses the Google Assistant (which has awakened my phone and Google Home more than once). However, the effort to lure Pixel owners over to T-Mobile may not be going so hot.

AI technologies have clear value paths in marketing, including sales and enhancing customer experience. When most companies think about artificial intelligence (AI)--and its many sub-categories, such as machine learning, natural language processing (NLP), or cognitive computing--they think about applications such as IBM's Watson technology being used to diagnose patients. What they often miss, according to Fern Halper, VP and senior research director of advanced analytics at TDWI, is that "marketing is often one of the first departments in an organization to use advanced analytics." In a recent webinar, Halper discussed the current potential and future pathways for marketing analytics with David Stodder, senior research director of business intelligence at TDWI, and Wilson Raj, the global director of customer intelligence with SAS. They all agreed that among all the different business departments, applying AI to marketing could provide the most immediate, recognizable return on investment .

Mobile internet applications are evolving rapidly. Cognitive computing technologies will inspire telecom service providers to profoundly change their business model in new creative ways. Deploying intelligent voice control apps on smartphones was just the beginning of this trend. As an example, mobile network operators are increasing their investment in big data analytics and machine learning technologies as they transform into digital application developers and cognitive service providers. With a long history of handling huge datasets, and with their path now led by the IT ecosystem, mobile operators will devote more than $50 billion to big data analytics and machine learning technologies through 2021, according to the latest global market study by ABI Research. "Machine learning-based predictive analytics are applicable to all aspects of the telecom business," said Joe Hoffman, vice president at ABI Research.