Will the Democratization of Technology Accelerate Progress in AI? – InformationWeek

If you were to poll the computing industry today for most hyped technology of our times, I posit that artificial intelligence would easily top the list.

And with good reasonthe last decade of progress in AI has been exciting for sure. But the impact of that innovation follows the William Gibson principle: The future is already here, its just not evenly distributed.

Whats particularly funny about AI is that people think that AI success should be evenly distributed. If Tesla can autopilot your car and Google Photos can match your elderly parents faces to their baby photos, why cant your company increase revenue and decrease cost via AI? Heck, AI cant even figure out how to load your pile of spreadsheets into a data warehouse!

So, whats causing the disconnect between AI innovation and impact? The issue is twofold. First -- all computing challenges are not the same. While some exciting topics like computer vision have made enormous leaps in recent years, most of the classically painful business data processing problems are still well beyond the capabilities of todays state-of-the-art AI. Second -- the engineering tools and practices for successful AI and machine learning are still in their infancy.

Todays Big Tech shops are largely solving their data and AI problems by hiring armies of expert software engineers to hand-stitch together data pipelines with bits of AI. This is exacerbated by the disparate state of open-source tooling. Unless your company can recruit lots of Silicon Valley-quality software developers, youre out of luck. To democratize the progress in AI, we need to do a couple key things:

Todays Big Tech shops are largely solving their data and AI problems by hiring armies of expert software engineers to hand-stitch together data pipelines with bits of AI. This is exacerbated by the state of open-source tooling. Unless your company can recruit lots of Silicon Valley-quality software developers, youre out of luck.

Thats why going forward, I see three key trends that will play an important role in democratizing AI:

The next year promises to be a very confusing time for AI, especially in fields like MLOps where the stack hasnt begun to shake out. Be sure to keep an eye on human-AI interfaces that facilitate augmented intelligence using low-code and no-code tools. While tech news stories about AI accomplishments will continue to tantalize you with possibilities, understand that the practical uses of AI in business will remain rare.

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Will the Democratization of Technology Accelerate Progress in AI? - InformationWeek