Artificial intelligence is most often seen as a consumer-driven innovation. AI-powered home assistants are available through numerous platforms and are designed to make life efficient. However as more businesses are struggling to make sense of their data, artificial intelligence is prepping to take on a new role in the office. From bots to analysis, AI for business is gaining accelerator funding.
Marketing, sales and customer service are the areas most likely to see a rise in AI powered bots. Already, customers interact with AI powered customer service, but start-ups are now developing virtual agents that can replace live-chat agents and others. These bots aren’t entirely innovative in the sense that they merely extend the kind of artificial intelligence consumers use at home into their daily interactions with other services. But start-ups, like Clair, test consumer products and ads without having to engage with consumers at all. This establishes Clair as a true AI tool for business. Scribe, another recently seeded startup, uses AI to identify new leads. The tech can potentially replace sales reps, or at least take over one area of their job.
Analysts predict that AI-powered technologies are likely to pivot in the upcoming months. The current use of bots, for instance, might be one stepping stone toward other technologies that will be used in other settings. So instead of customer service, marketing and sales bots, organizations might start applying these tools in numerous ways and settings. The most recent commercials from IBM come to mind. In the ads, Watson helps basketball coaches run predictive analytics on player performance; Watson assists IT professionals faced with security issues and finally, Watson shortens the time it takes to complete tedious tasks. Watson may speak like a bot, but it doesn’t think like one.
Considering AI’s potential in an enterprise setting, it is no surprise that accelerators are backing AI business technologies. Bots might seem small right now, but they aren’t the end of the line.
Bipolar disorder affects at least six million Americans each year, or roughly 4 percent of U.S. adults. Treatment typically involves some combination of mood-stabilizing or anti-psychotic medications and psychotherapy. However, recent discoveries in the field of artificial intelligence may prove revolutionary for individuals suffering from this condition.
Artificial intelligence, commonly known as “AI,” refers to intelligence exhibited by computerized machines. The idea revolves around a perceived need to create machines that can perform tasks previously limited to humans, such as those that involve decision-making. Essentially, the more technologically advanced we become, the more important it is to ensure that we can minimize human error.
One area where AI has shown great promise is in military applications. In air-to-air combat simulations, it has been known to outmaneuver even highly-skilled Air Force pilots. This same technology has now demonstrated a similar ability to predict how patients with bipolar disorder might respond to lithium treatment. Accurate predictions are difficult because of frequent fluctuations between periods of mania and depression. These fluctuations necessitate changes in treatment approaches, as they occur.
A new study conducted by the University of Cincinnati College of Medicine has shown that using AI can dramatically improve treatment effectiveness and efficiency. Various models have been employed by UC to predict how a particular patient might respond to lithium. The best of these models was known to be accurate 75 percent of the time. By comparison, the model employing AI was found to be accurate 100 percent of the time. Furthermore, it was 92 percent accurate in predicting when a patient’s manic symptoms were likely to decrease.
Artificial intelligence programs arrive at their conclusions based on generalizations, rather than specific definitions. They continuously refine their answers in a manner analogous to Darwin’s natural selection. Essentially, AI provides a way for doctors to use “fuzzy logic” to help them battle a notoriously difficult medical problem.
While it might seem as though air combat and medicine have little in common, they both involve an orderly process to arrive at the best possible decisions. While these new algorithms are clearly not sentient beings, as might be imagined in the world of science fiction, they are valuable tools that can be adapted to suit a large number of different applications.