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Home Industry Verticals Manufacturing

Lux Research lists 5 technologies for Electronics and IT

FutureCIO Editors by FutureCIO Editors
March 8, 2021
Photo by Pixabay from Pexels

Photo by Pixabay from Pexels

What technologies this year will have the greatest potential to transform the world over the next decade?

That was the question posited to Lux Research analysts as the starting point to identify the 12 technologies to watch in 2021 as detailed in the Foresight 2021: Top Emerging Technologies to Watch.

“Digital transformation as a concept has reached a point where developers and end users have to look past the hype and find real ROI from deployment of digital technologies,” explains Kevin See, Ph.D., vice president of Research at Lux Research.

“The central theme of these technologies is extracting value from data – whether layering AI on sensor outputs, analysing digital biomarkers to detect conditions, or using edge computing to extract insight locally in close to real time. These technologies are primed to impact every industry, from healthcare to manufacturing and beyond.”

This year, the analyst also ranked the top five technologies across five key industries: chemicals and materials, automotive, food and agriculture, electronics and IT, and energy.

For the electronics and IT space, the technologies to watch include:

AI-Enabled Sensors – Merging hardware and software to collect and validate critical data will be a major part of use cases from consumer wearables to medical devices to industrial IoT.

Digital Biomarkers – Using data analytics to detect disease through changes in streams of data analytics is a potent path for electronics companies to grab a piece of the healthcare pie.

Natural Language Processing – Natural language processing (NLP) allows electronics and IT players to extend into new services and industry segments, either by using it to leverage their own data or by providing it as a service.

Edge Computing – Limitations in bandwidth and latency are pushing critical computation away from the cloud and out to the edge, with rapidly improving hardware and software enablers.

Synthetic Data – AI needs vast amounts of training data, and when real data is scarce, synthetic data can be a solution. It also boosts data diversity and privacy.

Related:  Gartner predicts 40% of GenAI solutions will be multimodal by 2027
Tags: AI-enabled sensorsdigital biomarkersdigital transformationedge computingelectronics and ITIoTLux Researchnatural language processingsynthetic data
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