Artificial intelligence (AI) has moved from the realm of science fiction to a part of everyday corporate life.
AI is still a poorly understood field. It’s inherently complex and has been romanticized by the media. That’s partly by design: Staging matches against chess and Go champions raises awareness and, perhaps, money (especially if the AI platform wins).
As usual, however, the truth is a bit duller than the image. AI, and its various offshoots and subcategories, has great utilization for tasks that are extremely mundane and unexciting. It’s not at the point that it can take over the world. But it certainly can assess tons (literally) of data far more quickly and accurately than a human and make recommendations on what it has processed.
Part of the issue is its broadness. Vox takes a look at the levels of AI, and describes three categories: Weak AI, Strong AI and superintelligence. Weak AI (which is more formally called narrow artificial intelligence) has very limited focus and specializes in “non-sentient” operations. An example is Deep Blue, the computing platform that beat Garry Kasparov in chess in the 1990s. It won because it did one thing exceptionally well: Analyze potential chess moves quickly.
Strong AI gets into the category that raises fears and excitement:
It’s debatable whether strong AI could be called “conscious”; at the very least, it would demonstrate behaviors typically associated with consciousness — commonsense reasoning, natural language understanding, creativity, strategizing, and generally intelligent action.
The final category, artificial superintelligence, is the very scary one that supervillains seek to harness. It is intelligence that, in the words of Oxford’s Nick Bostrom, “radically outperforms the best human minds in every field, including scientific creativity, general wisdom and social skills.”
What Are Companies Using AI For?
Questions exist as AI increasingly moves to the mainstream: What, precisely, is it useful for? How must companies prepare for its implementation? Has development gotten to the point that organizations without expertise on staff can deploy AI themselves or is it necessary to bring in outside specialists to customize, install and operate the technology?
Will Ramey, the director of Developer Marketing for NVIDIA, wrote that some big companies have been fast and others slow to adopt AI. Size seems to be no determinant; small companies and startups are sometimes ahead in AI development and deployment. “Perhaps a more telling predictor of whether a company is likely to use AI is its industry affiliation, as we’ve noticed some industries are quicker to adopt than others,” Ramey wrote in response to emailed questions from IT Business Edge.
It is likely that usage patterns are driven by the nature of what tasks need to be performed. For instance, pharmaceutical companies are ahead in AI, Ramey wrote. That makes sense, since it is a highly complex area in which huge amounts of test results must be deeply studied. New information must be culled from them, including recognition of hidden patterns. He also pointed to automotive, financial services, health care, retail, manufacturing and telecommunications as early users of AI.
Companies don’t have to be in the cutting edge sectors to use AI, however. Shriram Ramanathan, a senior analyst for Lux Research, wrote that manufacturing has lagged, but that some companies in the segment have been aggressive. “For example, a traditional manufacturing company may be far ahead in AI adoption for sales/e-marketing functions, while it may still be lagging in incorporating AI into its traditional manufacturing or R&D divisions.”
It is important for organizations to plan their use of AI carefully. Says Ramey: It is a commitment and not for everyone. “It depends on the technological sophistication of the company. Firms with a strong in-house technology team may choose to implement their own AI capabilities. Others may engage with consultants to guide them through the process, or rely on vendors to provide implementation services or fully realized solutions.”
AI has a lot to offer for many companies if used correctly. “That’s why we’re seeing companies that do everything from brew beer, offer personal loans, drill oil wells, and more – over 19,000 organizations in the last two years have engaged with NVIDIA to apply deep learning to improve their products, services and business processes,” Ramey wrote.
AI developments are moving along quickly. In early March, IBM and Salesforce announced a global partnership that will join IBM Watson and Salesforce Einstein. The idea may be that two electronic heads are better than one, since both are AI platforms. The joint entity will be put to work in sales, service, marketing, commerce and other areas.
The bottom line is that AI is becoming simply another powerful tool. That’s the interesting and important thing in the big picture, though it is not as thrilling as an IT application that seeks to take over the world.
Carl Weinschenk covers telecom for IT Business Edge. He writes about wireless technology, disaster recovery/business continuity, cellular services, the Internet of Things, machine-to-machine communications and other emerging technologies and platforms. He also covers net neutrality and related regulatory issues. Weinschenk has written about the phone companies, cable operators and related companies for decades and is senior editor of Broadband Technology Report. He can be reached at cweinsch@optonline.net and via twitter at @DailyMusicBrk.
