Why machine learning will decide which IoT 'things' survive

No billion-dollar machine could replace a doctor. But a $25 machine can tell you when you need one. In 1996, the ER at Cook County Hospital of Chicago used an algorithm to determine when a patient with chest pain was in danger of having a heart attack and was thus worth one of its scarce hospital beds. Using a systematic, flowchart-based approach of basic tests, the algorithm proved not only to be quick and efficient, but accurate: It sorted 70 percent more patients into the low-risk category, but caught a higher percentage of heart attacks (95 percent) than human doctors (75-89 percent). And this was before any deep computing was involved. Now consider that there are around 6.4 billion IoT devices in use this year -- nearly one for every living human.