Glen Rabie is Co-Founder and CEO of Yellowfin, an Analytics and Business Intelligence company that helps businesses understand their data. Let's face it: The greatest value from collecting and analyzing data is not revealed by understanding what happened yesterday, but in deciding what to do tomorrow. That capability has been available for years -- if your business could spend enough time and money on the pursuit. Today, ultrapowerful predictive analytics is coming to a wider spectrum of enterprises than ever before. Driven by the open-source movement in response to the explosion of big data, midmarket companies and even SMBs now have access to the same AI-driven BI solutions that previously were largely available only to multinationals. AI and machine learning technologies are transforming BI and giving decision-makers "aha" moments like never before.

Tim Bandos from Digital Guardian says technology always requires human consciousness to strive forward. It has and will require human effort to counter cyberattacks and stop them. According to Tim, Experts and Analysts are the real heroes, and AI is just a sidekick. How are hackers using AI to attack cybersecurity? In some cyberattacks, hackers exploit the data which is used to train machine learning models.

Technology is forever developing and for the better. Life has been made simple by mobile cellphones and other useful devices that have been embedded in our daily lives. You can communicate with people who are oceans across real-time and even see their face. All these social technological developments have proved the efficacy of technology in the day and age that we live in. However, technology has not only developed our social life, but a wide variety of commercial sectors have submitted to use different technologies that are at their disposal.

Smartphones, smart speakers, smart cars, smart coffee makers...the list goes on. It seems like everything around us is coming to life and becoming intelligent. And though the sci-fi genre thrives on our ever-present fear of a hostile robot takeover, smart devices are anything but dystopian -- they're actually here to make our lives easier so we can spend more time on the important stuff instead of tedious busywork. Tech companies know that increased automation is the way of the future, just like it was when Ford pioneered the assembly line. Advanced technology like artificial intelligence (AI) and machine learning (ML) is fueling the most exciting innovations in recent history -- think self-driving cars, virtual and augmented reality, automated investing, improved medical imaging, and more.

Only a few years ago, business to business (B2B) technology companies would sell a solution to a customer, wait three to five years, then reapproach that same customer to offer a renewal or a completely new product. But these days, the initial purchase doesn't necessarily translate into a continuum of sales, and it doesn't hold the promise of customer retention like it once did. That's because today's customers have much higher expectations in order to remain loyal. Getting them to love your brand and love your products takes a customer-first mindset and a company-wide commitment to improve the customer experience. Companies that excel at customer experience are using artificial intelligence (AI) and machine learning heavily to produce immersive, authentic experiences across every customer touch point.

Over the last couple of months, a lot of discussions have been going on about Artificial Intelligence (AI). Besides the faceoff between Elon Musk and Mark Zuckerberg on Twitter, there have been numerous instances where discussions and debates on AI took center stage. Eminent personalities like Stephen Hawking, Bill Gates and Eric Schmidt have been involved in such debates. Recently, Google has announced their work with AI trying to create their language and about another AI teaching itself how to "walk." Understandably, there has been a lot of trepidation about the entry of AI into our daily lives.

With all the tools and channels available to help brands reach customers, it still seems like most brands out there are floundering in their efforts do so effectively. This is obvious to any customer who has purchased a product and then had ads for that already-purchased product follow them around the Web. Or has received identical copies of a promotional email at their work email address, personal email address, and former email address that forwards to that current account. Or any credit card owner who's been urged to apply for a credit card they already have, every time they visit an eCommerce site. It's a bit of a mess out there, with men being shown women's products; teens being marketed bespoke business attire; and on and on and on.

Verizon's FIOS fiber optic broadband keeps millions of US homes online. However, monitoring stability and reacting to faults and outages which affect customer experience takes huge amounts of resources. Until recently, Verizon primarily relied on customer feedback to understand when the speed and quality of its service was falling short of expectations. In recent years, however, following a large investment in analytics and AI-driven technology such as machine learning – in part subsumed through the company's 2017 acquisition of Yahoo! and it's research units – a different approach is bringing impressive results. Now it's predictive analytics algorithms monitor 3GB of data every second streaming from millions of network interfaces – from customers' routers to an array of sensors gathering temperature and weather data, and software which "listens in" on operational data, such as billing records.

Like Google, Baidu's core service is also search – Baidu is said to account for 75% of search traffic in its homeland. Here, it has rolled out machine learning algorithms for voice and image recognition, as well as natural language processing, to help it return smarter, more useful and more personalized results. Baidu also makes its technology available to third parties such as other companies which want to benefit from the AI revolution but don't have the resources to develop their own algorithms and applications. Much of its software and systems have been made open source and it also provides access to its technology on an "as-a-service" basis. Businesses and organizations can use Baidu's systems to host their own data and run their own analytics projects in the cloud, paying only for the storage and computing resources which they use.

Baidu is currently considered to be pack leader amongst the Chinese internet giants as they race to develop and deploy machine and deep learning technology. Much like their US-based counterparts such as Google and Amazon, self-teaching, neural net technology is being integrated into both their core services and used to innovate in new ways. Cutting edge artificial intelligence (AI) methods such as machine learning and deep learning are being used to reap huge benefits across industries as diverse as finance and healthcare. The basic idea is that once we teach computers to learn in the same way we do, they can absorb and process Big Data at a tremendous rate, soon becoming at least, if not more, reliable than humans when it comes to making decisions. The work of the Chinese giants – most prominently Baidu but also online retailer Ali Baba and chat provider Tencent - in the AI field has received relatively little coverage in western media compared to that afforded to the US giants.