Just about everywhere you look, particularly in the past few years, you are bound to see an information technology expert touting the benefits of artificial intelligence and machine learning. Typically, those touted benefits are just years, or perhaps even months, away from becoming reality–the theory is sound, all we have to do is figure out how to make it work. Perhaps 2018 will be the year we see some practical, tangible, and measurable benefits from this technology.
IT industry leaders, like Microsoft, are promoting AI and machine learning as a technological combination that will eventually change the world, not only for business enterprises but for the medical industry too. In January 2018, Microsoft announced that it had partnered with Adaptive Biotechnologies in a plan to build a practical technology for mapping and decoding the human immune system. It would be a breakthrough in medicine–if they can make it work (sound familiar).
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Research at Adaptive Biotechnologies combines high-throughput sequencing and bioinformatics to create an accurate immunosequencing platform. The results generated by the platform can be applied to diagnose cancers and other diseases, which can then be treated via the human immune system.
The stated ambitious purpose of the Microsoft partnership will use AI and machine learning to:
“Create a universal blood test that reads a person’s immune system to detect a wide variety of diseases including infections, cancers, and autoimmune disorders in their earliest stage, when they can be most effectively diagnosed and treated.”
If successful, the blood test would be able to provide a complete and detailed insight into what a patient’s immune system is doing, diagnose conditions, and suggest necessary treatments. It would be a medical breakthrough that could increase early detection, accelerate treatment plan implementation, and ultimately save lives.
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While the idea certainly has merit and sounds wonderful in theory, there are some major hurdles to overcome–and some even greater uncertainty about whether the seemingly sound theory can be transformed in to a practical solution. So why is Microsoft taking part in such a difficult and risky endeavor? It’s all about the research.
In many ways, the development arc of AI is like the development arc of cloud computing. For many years, we were promised tremendous benefits from cloud computing only to be disappointed by a lack of practical applications. Then, almost overnight it seemed, cloud computing became standard operating procedure for enterprises the world over. It just took time for theory to become application.
AI and machine learning are currently in the “poised to transform life as we know it” stage. The only way to advance progress in this area is by trying it in practice, even if the attempt fails. While developing a universal diagnostic blood test is ambitious and risky, the benefits would be worth the invested resources and then some. And whether successful or not, the knowledge created by the endeavor could prove invaluable to Microsoft as it attempts to apply AI to its line of business enterprise products and services.
At some point, AI and machine learning will reach a threshold where their benefits become standard operating technology for business enterprises everywhere. IT departments, and the IT pros who manage them, need to stay ahead of the learning curve and be ready to deploy the next big AI thing or they will soon find their enterprise technology is falling behind and losing ground to the competition.
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