The Future is Computational and Other Lessons from Wolfram Language

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Mountain peaks surrounding Los Angeles was the first directive input to the system. Within milliseconds, a list of names popped up.

Ok, now display that information on a map. A split second later, there it was. A few more clicks and the image transforms into a topographical rendering. Now we can generate the same information for any location around the world instantly.

This was but one simple example that computational scientist Stephen Wolfram presented in a live demonstration of his groundbreaking, knowledge-based computer programming language during the Collision tech conference held in New Orleans in May. The eponymous language can symbolically manipulate neural networks, basically, a computer modeled after the brain and nervous system.

Artificial intelligence has long since proven itself a reality, but more recently, we’ve been on the brink of tangible, real-life use cases and even mass consumer deployments. As a highly functional source of AI, Wolfram Language seems light years ahead of what I thought I knew as machine learning with Amazon’s Alexa and IBM Watson. The above example from the demo at Collision was just one of various incredibly simple, often silly functions that managed to yield amazing results instantaneously.

Wolfram describes it as, “the world’s most productive programming language.” His goal has been to design the highest level of building blocks for software development, making it easy to create really powerful programs, “so people can go from ideas to deployed products as quickly and easily as possible,” he said.

What has been a 30-year work in progress has produced a vast stack of technology and content, “that I think just completely changes how we should think about programming.”

While there’s much to be fascinated about with Wolfram Language, I’ll point out that in its latest release, 11.1, industrial-scale audio processing was added, providing fully integrated audio support capable of advanced programmatic processing and analysis. Effectively, it opens the possibility for cloud- or server-based audio processing. Reading between the lines—it stands as one more indication that hardware is no longer the centerpiece of audiovisual systems.

As we converge on our annual industry meeting of the minds in Orlando this month, let that ring in your ears as you peruse the latest innovations and consider new ways to bring services into your portfolio and create value for clients. In further breaking down the barriers between man and machine, the need to—literally and figuratively—think outside of the box is key to the next generation of systems integration in a computationally informed world.

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