2018 in review: Building the technological foundation for mainstream AI applications

By | December 30, 2018

2018 was also a milestone year in AI as the technology community writ large developed a more complete, nuanced understanding of its benefits and limitations while innovations laid the foundation for future applications. From part 2 of my Diginomica year in review.

Brain in an open storage jar © ktsdesign - Fotolia.comPart one of my year-in-review, centered on 2018 developments in enterprise cloud, notably how mainstream adoption of cloud infrastructure has shifted the emphasis from kicking the tires to the operational complexities of integrating cloud services with existing IT systems and networks. In part two, the focus is on how AI-related technologies are migrating from research labs and niche scenarios to broader applications in healthcare, the enterprise and even IT itself.

Disentangling hype from reality shows that most ‘AI’ looks more like statistics than intelligence

The renaissance of AI, rescued from the ash heap of symbolic reasoning and expert systems by the rise of recursive deep learning algorithms, has fueled no end of hyperbolic predictions and dystopian narratives. Much of the exaggeration stems from the moniker itself, since despite the many impressive achievements of today’s incarnation of AI, it bears a closer resemblance to advanced statistics than it does cognitive intelligence. As I discussed in this article, there’s a growing backlash and active debate among academics as to whether machine and deep learning are ‘intelligent’ at all or merely clever ways of analyzing the massive troves of data now available:

Medicine proves to be a rich target for AI-enhancement

The biggest advances in millennial-generation AI have come via deep learning: recursive algorithms modeled after human neural networks that are particularly adept at pattern matching and image analysis. Although early deep learning demonstrations typically involved tagging simple objects from the type of quotidian photos that get shared on social media, more significant uses come from the fields of physical surveillance, aerial and satellite mapping and medical imaging.

Read more at the link below.

Content retrieved from: https://diginomica.com/2018/12/20/2018-when-vendors-built-the-foundat

ions-for-ai-applications-while-enterprises-looked-for-useful-applications/.

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