2017 predictions: Smartphones will have machine-learning capabilities
Deloitte Global predicts that more than 300 million smartphones, or more than one-fifth of units sold in 2017, will have machine-learning capabilities within the device in the next 12 months. Deloitte Global’s 16th edition of the “Technology, Media & Telecommunications (TMT) Predictions,” showcases how mobile devices will be able to perform machine-learning tasks even without connectivity, which will significantly alter how humans interact with technology across every industry, market and society.
However, over time machine learning on-the-go will not just be limited to smartphones. These capabilities are likely to be found in tens of millions (or more) of drones, tablets, cars, virtual or augmented reality devices, medical tools, Internet of Things (IoT) devices and unforeseen new technologies.
“Machine learning is fascinating as it will revolutionize how we conduct simple tasks like translating content, but it also has major security and health consequences that can improve societies around the world,” says Paul Sallomi, Deloitte Global TMT Industry leader. “For example, mobile machine learning is a strong entry point to improve responses to disaster relief, help save lives with autonomous vehicles, and even turn the tide against the growing wave of cyberattacks.”
Another innovation with the power to transform the world is autonomous braking. Deloitte Global predicts that in 2022, in the United States alone, fatalities from motor vehicle accidents will have fallen by 6,000, a 16 percent decline in 2017. The greatest factor in this decline will likely be automatic emergency braking (AEB) technologies. Deloitte Global expects that AEB will be so widely adopted, affordable and successful at helping to save lives that it may even slow down the movement towards full self-driving cars.
It’s not just about developing new technology, but how this technology is procured that is set to transform how we live and work. Deloitte Global predicts that by the end of 2018, spending on IT-as-a-Service for data centers, software and services will reach nearly $550 billion worldwide, up from $361 billion in 2016. Although flexible consumption-based business models will not be ubiquitous by 2018, at more than a third of all IT spending (35 percent), they’re expected to exceed half a trillion dollars and grow rapidly. This shift will begin to transform how the IT industry markets, sells and buys technology across businesses worldwide.
“In 2017, technology, media and telecommunications are set to become even more mobile. Combined with smarter and faster capabilities, these innovations will force businesses, governments and consumers alike to evolve how they operate and create opportunities for widespread transformation across industries,” Sallomi adds.
For more details, see: www.deloitte.com/predictions.
- 33July/August 2015 How neuro-dynamic programming enables smart machines to think ahead. By Scott Zoldi The media and watercooler chatter alike increasingly focus on how advances in machine learning and artificial intelligence (AI) are boosting the ability of predictive analytics to benefit businesses’ bottom lines. Some of that talk ponders the…
- 32From dark analytics to mixed reality, machine intelligence and blockchain, Deloitte’s annual Technology Trends report analyzes the trends that could disrupt businesses in the next 18-24 months. CIOs who can harness the possibilities of these technologies will be better positioned to shape the future of their business.
- 32FEATURES Fulfilling the promise of analytics By Chris Mazzei Strategy, leadership and consumption: The keys to getting the most from big data and analytics focus on the human element. How to get the most out of data lakes By Sean Martin A handful of requisite business skills that facilitate self-service…
- 31May/June 2012 Statistical modelers urged to embrace machine learning, open-source tools for the road ahead. By Sameer Chopra My thesis below addresses the following points: While statistical modeling is not going away, analytics groups are advised to leverage machine-learning approaches as well. While traditional statistical modeling software packages are not…