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.

The illnesses a person experiences in their lifetime are to a large extent determined by genetics. But today, the predictive power of gene sequencing technology is becoming invaluable in preempting disease. MGI Tech's mission is to benefit mankind through genomic technologies. The BGI subsidiary focuses on developing instruments and equipment for the medical and health sectors, providing a range of real-time, full-scenario, and full-life-cycle digital devices. However, the resulting rise in data requires the right digital infrastructure to make these services a reality.

Huawei's SoftCOM AI solution introduces AI to All Cloud Networks. Designed to create self-driving network architecture, SoftCOM AI is a transformative solution that can help operators compete with OTT companies by using predictive AI to minimize network faults. Telecom services are divided into three tiers: device, network and IT infrastructure, and upper-layer applications. However, in today's telecom's landscape, cross-sector competition is threatening telco revenue models. Thanks to dramatic increases in network speeds, IT and Internet companies are offering cloud services in traditional telco territory: backbone networks, some MANs, IT infrastructure, and IT applications.

The financial services industry is feeling the impact of the digital revolution. Maintaining growth and profitability is an enormous challenge for banks as they need to keep tinkering with the customer experience, not only to provide financial services for their customers, but also to stay more relevant in customer's lives and keep their attention. Digital platforms are fueling the on-demand economy by matching supply and demand in an accessible, low-cost way. Uber, Amazon, and Alibaba show the disruptive power of these "share" technology platforms, where buyer-seller interaction is high, a diverse range of goods are on offer, and the marginal cost of rolling out a new product or service is approaching zero. Fintechs are disrupting the industry by both cooperating and competing with banks for customer attention and thus their wallets.

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.

Hal, Ex-Machina, the Terminator and Matrix movies, and I, Robot all trade on the beloved sci-fi meme of robotized AI and the public's collective psyche when it all goes wrong: fascination and fear. After all, if machines become faster, stronger, and brighter than humanity, why wouldn't they turn on their soft, meaty, and dim creators for either enslavement or a full-on purge?

Information overload is a fact of modern life, creating a tyranny of choice often resulting in analysis paralysis. Too many options makes it difficult to understand any one option deeply enough to make an informed decision. That's a problem, because the whole point of Ubiquitous Computing – a term coined by Xerox PARC in the 80s to represent a dream of the time – was to make our lives and businesses better and more efficient. Thankfully, amid the enormity of data lies the means to manage it. Our computing infrastructure has now reached a level of data and connectivity where it's possible for computers to recognize patterns and prioritize options, so it's easier for humans to make informed decisions.

Hal, the Terminator and Matrix movies, Ex-Machina, and I, Robot all trade on the beloved sci-fi meme of robotized AI and the public's collective psyche when it all goes wrong: fascination and fear. After all, if machines become faster, stronger, and brighter than humanity, why wouldn't they turn on their soft, meaty, and dim creators for either enslavement or a full-on purge? Let's face it – machines are getting smarter. AlphaGo's victory over Lee Sedol at Go came 10 years earlier than predicted, before in fact humanity had worked out the exact number of possible legal Go positions (a number the size of 10170 was completed on January 20, 2016, if you're interested). In 2014, a chatbot glorying in the name of Eugene Goodstead passed the Turing Test by fooling 33 percent of judges into believing it was a 13-year-old Ukrainian boy.