Recent advancements in machine learning, deep learning and other variations of artificial intelligence have been impressive. Yet, when it fails (as we've seen in autonomous cars and Facebook's facial recognition software) we're not surprised. After all, computers are only as smart as their programmers, right? Unlike humans who fundamentally just "know" certain things, computers rely on levels of confidence. They are very seldom 100 percent sure of anything and sometimes they're just wrong. Knowing this, how do build systems that 'work' even though the underlying models may lack confidence?


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machine learning,deep learning,artifical intelligence,ai limitations,ai systems,pyro