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AI driving 'unprecedented' M&A growth

16 May 2019

Breakthroughs in artificial intelligence are causing ‘unprecedented’ growth for mergers and acquisitions, as companies grapple for their share of an AI market that will be worth $190 billion by 2025.

Analyst firm Hampleton Partners says the first quarter of 2019 has seen some record-breaking M&A transaction volumes – something that will set the pace for the rest of the year.

AI has graduated from the experimental phase of the innovation lifecycle into the developmental phase, as it is applied in almost all industries and verticals.

“With the growth and competitiveness of many industries now dependent on the development of these AI technologies, strategic investors across all sectors and continents are stepping up their acquisitions and investments,” says Hampleton partners sector principal Heiko Garrelfs.

There are several areas where AI is making the most impact: Machine data analysis, edge AI, computer vision, language analysis, and conversational AI.

Below are insights from Hampleton Partners about each area.

Machine data analysis and edge AI

Machine data analysis has recently shown an inclination towards Edge AI – i.e. running AI algorithms on edge devices such as smartphones or cars, rather than communicating with a central cloud or server – which allows devices to safeguard privacy, avoiding the purported insecurity of cloud-based data systems.

Edge computing also allows devices to process information locally and respond more quickly, which is vital for the development of Internet of Things (IoT) and autonomous vehicle technology, where immediate response is a necessity.

Computer vision

Computer vision experienced a stellar half-year in 2H 2018, mainly owing to growth in hot trends such as facial recognition, check-out-free retail or motion analysis, all of which enable the collection of more insights and provide information for future market opportunities.

Facial recognition is becoming a dominant form of biometric authentication, with early commercial applications in security, retail, payments and consumer electronics – Apple’s latest smartphone technology for Face ID logins and payments being one of the commercially popular use-cases. Retailers are also adopting the technology to recognise returning customers – a strategy used to offer special discounts as part of loyalty programmes.

Furthermore, as increasingly smart city infrastructure adopts security cameras, video analytics can be widely applied using facial recognition to detect and track offenders or suspects in public spaces.

Language analysis and conversational AI

Global tech companies east and west have focused heavily on Conversational AI. Google’s integration of Duplex – its new AI-driven automated reservation-making system – into the Pixel 3 smartphone, transformed the Google handheld device into an AI powerhouse.

However, Apple’s Siri has lagged far behind Amazon’s Alexa and Google’s Assistant in terms of voice recognition ability and development. It was no surprise, therefore, that in February 2019 Apple acquired PullString, a speech recognition software development SaaS which enables businesses to build interrelated applications for IoT devices.

Many companies believe the problem is not the speech recognition technology itself, but the lack of focus and reasoning within these systems. As a result, intent detection – i.e. the ability to determine from context what the user wants – has become the new research focus area for speech recognition start-ups who are willing to challenge the hegemons and fill in the gaps in big tech AI.

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