Engineering machines that learn

Artificial intelligence (AI) is undeniably experiencing a new wave of attention, energy and sky-high expectations. This wave is driven by the abundance of data that’s being generated in our connected, digital society, and by the low-barrier availability of enormous computational resources. Among the various AI techniques, machine learning, in particular, has come to play a key role.

Machine learning allows us to solve complex problems, not by arduously writing new code, but by letting an existing algorithm learn new behavior from examples. We’re now witnessing breakthrough results in image recognition, speech processing, medical diagnostics, securities trading, autonomous driving, product design and manufacturing, and much more.

Does ML’s rapid ascent mean that software systems will no longer need to be programmed? Will we need data scientists instead of software developers? To those that have experienced software-related project delays, system outages and indefinitely incomplete feature sets, a world without programmers might seem attractive.