Artificial intelligence is certainly no longer considered science fiction--or a source of expensive R&D efforts with unmet potential--by major players in the technology sector.1 Instead, we are in the midst of a real-world paradigm shift: the final stages of a decades-long transition from the scientific discipline known as artificial intelligence (and its various sub-disciplines) into an array of applied cognitive technologies made more widely available through innovative enterprise architectures unique to the business culture of the technology sector. The technology sector's interest in these technologies (figure 1)2 has exploded in the last several years. Networking companies, semiconductor manufacturers, hardware companies, IT providers, software providers, Internet players--just about every technology subsector has seen a substantial upsurge of activity in this space. In fact, the race to invest in artificial intelligence has been described as "the latest Silicon Valley arms race."3 Since 2012, there have been 100 mergers and acquisitions (M&A) within the technology sector involving cognitive technology companies, products, and services.4 And this rush of M&A activity is not the only sign of the industry's interest. Many capabilities that were only just emerging a few years ago are now essentially mature and becoming "democratized" and more readily available for business applications. As a result, leading companies are using cognitive technologies to enhance their existing products and services, as well as to open up new markets. What is interesting is that the assertive actions of the sector's leaders do not mirror the wholesale adoption of these technologies across the industry.
Machine learning and artificial intelligence have arrived in the data center, changing the face of the hyperscale server farm as racks begin to fill with ASICs, GPUs, FPGAs and supercomputers. These technologies provide more computing horsepower to train machine learning systems, a process that involved enormous amounts of data-crunching. The end goal is to create smarter applications, and improve the services you already use every day. "Artificial intelligence is now powering things like your Facebook Newsfeed," said Jay Parikh, Global Head of Engineering and Infrastructure for Facebook. "It is helping us serve better ads.
After years in the labs, artificial intelligence (AI) is being unleashed at last. Google, Microsoft and Facebook have all made their own AI APIs open source in recent months, while IBM has opened Watson (pictured above) for business and Amazon has purchased AI startup Orbeus. These announcements have not drawn much media attention, but are hugely significant. "In the long run, I think we will evolve in computing from a mobile-first world to an AI-first world," says Google CEO Sundar Pichai. What does the appearance of AI bots and machine learning on the open market mean for business, IT, big data, and for sellers of physical hardware?
For the last five years, IBM has strived to reinvent itself as a cloud computing and cognitive platform company to support its large enterprise clients as they shift their operations online, including many in travel and transportation. With most large companies today evolving into digital companies, cloud computing is a booming marketplace for the big four industry providers: IBM, Microsoft, Google, and Amazon. Google, for example, stated that cloud could overtake advertising revenue in five years. Travel companies like Etihad and Lufthansa are helping drive IBM's cloud sales. The UAE carrier signed a 700 million IT deal with IBM last October, while Germany's national airline invested 1.25 billion in Big Blue in November 2014 to integrate cloud computing.
Artificial intelligence (AI) is rapidly transforming everything today, from daily lives to transportation to businesses. Humans have always found the concept of AI very enthralling as is evident from the number of hit sci-fi movies. Scientists and researchers have worked hard on making this technology a norm for the human beings. Enterprises are adopting AI and machine learning (ML) for various use cases, which has risen the demand for AI engines that can be used to develop intelligent applications and tools. Such apps and tools help them automate the repetitive, tedious and difficult tasks that can affect productivity and cost of operation.