While many lament the use of the term ‘artificial intelligence’ for machine learning or automation technology, it has become the catch-all name for an impending tide of disruption across industries.
Organisations including IBM and Microsoft have been spearheading progress in the space, with the two giants vying for dominance in terms of deep learning capabilities.
Organisations like Facebook are also pioneering AI research; this year Facebook researchers discovered its AIs communicating with one another and learning, resulting in a fascinating story that even had mainstream news consumers captivated.
Wreathed in hype, professionals foresee the technology being vital now and in the near future, particularly in spaces like cybersecurity. The security industry is largely unanimous in the opinion that automation technology is critical for taking on the ever increasing volume of threats, a problem exacerbated by the widening skills gap.
Security professionals are usually found positive that AI could make a real difference, but the hopeful notion is always mirrored by an ominous one, namely that hackers are going to be using it against us as well.
Although important, security does not account for the whole picture of AI in 2018, with a number of professionals expecting other disruptive progress for the technology next year. For example, it is expected that AI technology will make robots fit in with life more seamlessly, it will be more accessible from your mobile device, and some believe that doctors will soon be able to leverage the power of artificial intelligence.
AI in everyday life
Chris Nicholson, CEO and co-founder, Skymind.io, said: “Robots are going to get better at complex tasks that humans still take for granted, like walking around a room and over objects. They’ll get better at mastering boring, normal things. I’m looking forward to seeing progress in NLP tasks as well, since right now we’ve got a ways to go. We’re going to see more and more products that contain some form of AI enter our lives. Waymo’s level 4 autonomous vehicles are deployed on the road now. So all this stuff that’s been tested in the lab will become more common and available. It will touch more lives.”
AI on your phone
Robinson Piramuthu, chief scientist for computer vision, eBay, said: Vast applications on smartphones will run deep neural networks to enable AI. Friendly robots will start to emerge as more affordable and rise as the new platform at home. They will start to bridge vision, language and speech in such a way that the users will not be conscious about the difference between these communication modalities.”
AI assistants get smarter
Alejandro Troccoli, senior research scientist, NVIDIA, said: “Personal assistant AIs will keep getting smarter. As our personal assistants learn more about our daily routines, I can imagine the day I need not to worry about preparing dinner. My AI knows what I like, what I have in my pantry, which days of the week I like to cook at home, and makes sure that when I get back from work all my groceries are waiting at my doorstep, ready for me to prepare that delicious meal I had been craving.”
AI for doctors
Mark Michalski, executive director, Massachusetts General Hospital and Brigham and Women’s Center for Clinical Data Science, said: “2018 will be the year AI becomes real for medicine. We’re going to move from algorithms to products and think more about integration and validation, so that these solutions can move from concepts to real, tangible solutions for our doctors.”
“By the end of next year, I think around half of leading healthcare systems will have adopted some form of AI within their diagnostic groups. And while a lot of this adoption will happen first in the diagnostic medical specialties, we’re seeing solutions for population health, hospital operations and a broad set of clinical specialties quickly follow behind. In 2018, we’ll begin the adoption of a technology that may truly transform the way providers work, and the way patients experience healthcare, on a global scale.”
Greg Arnette, director of data protection platform strategy at Barracuda, said: “While advancements in technologies like AI and machine learning offer solutions to prevent security breaches, they are also tools hackers will increasingly leverage to devise more powerful and targeted attacks.”
Adam Hunt, Chief Data Scientist, RiskIQ, said: “Threat actors will increase their adoption of Adversarial Machine Learning to evade detection by infrequently trained machine learning models. Machine learning models will need to evolve quickly to keep up with these threats by incorporating instance based approaches.”
“The value of large data lakes will increase as security companies turn to machine learning based solutions. The most valuable of these datasets will be hand curated labelled dataset that can be used to train supervised machine learning models,”
Manohar Atreya, Vice President and Global Head ,Cloud, Infrastructure Management and Cyber Security Services, Infosys, said: “The advent of AI has made an impact on various fields including security. The enormous volumes of processed and unprocessed data moving across devices, networks and infrastructure will require AI to protect the environment.”
AI and analytics
Ronald Sens, Director EMEA Marketing, A10 Networks, said: “AI is everywhere. It’s in our homes with Amazon Echo. And in 2018, it’ll be embedded more tightly in IT analytics systems making IT proactive versus reactive… Through predictive analytics, IT and application owners will receive actionable information and recommendations. Add to that the ability to automate their response, and the power of AI becomes more relevant.”
“Analytics systems will have insight into the behaviour of the infrastructure, apps and clients. It will recognize anomalous performance or security behaviour and when an app or server is going to fail. Once that behaviour is noticed, automation can kick in to remediate the potential problem, i.e. firing up another server or load balancing the app. It’s like your infrastructure can say “Alexa, spin up another server.”
Travel AI explosion
Mike Croucher, Chief Architect for travel commerce platform Travelport, said: “Use of AI among travel firms will explode in 2018, further blurring the boundaries between tech companies and travel companies as they increasingly use AI driven by data and analytics to analyse the customer searches and tailor results based on supply and demand. Powered by platforms with built-in intelligence and learning, travel providers will have the capability to know prospective customers were discussing a flight to South America and proactively push offers.”
The intelligent cloud
Prakash Arunachalam, CIO at Servion Global Solutions, said: “AI technologies, especially machine learning and deep learning, will emerge rapidly to add more power to the cloud.”
“The amalgamation of cloud computing and machine learning will result in ‘the intelligent cloud’. Serving as a self-learning platform, it will be able to perform tasks more accurately and efficiently than ever before. This is likely to be the era of the next-generation cloud’ one that provides scalability at a low cost, for storing and processing large volumes of data.”
The intelligent enterprise
Comments from Mark Barrenechea, CEO of OpenText, said: “Equipped with AI and cognitive systems, big data analytics, and machine learning, the insights-driven intelligent enterprise will outpace its competition.
“Better data will mean better algorithms, and better algorithms will mean better data, and so on. We will become much more productive as we offload collecting and processing data to AI systems. The intelligent enterprise will leverage agile development to build apps in the cloud, automate processes and menial tasks to optimise efficiency, and explore data lakes for sophisticated insights and better decision making,” Barrenechea said.
Augmenting human decision-making
Mohit Joshi, President and Head of Banking, financial services and insurance, and healthcare and life sciences at Infosys, said: In 2018, I expect AI techniques to be applied to solve more of the complex engineering problems organisations face in design, testing, and certification of engineering products. By utilising knowledge management platforms to amplify and augment human decision-making, AI can take historical data to make sense of problems that otherwise may not have been solved with traditional engineering.
Meaningful user experiences
Ravi Maruyam, SVP Engineering and CTO, Couchbase: “While data integrity still varies within the enterprise, true implementation of AI is still a concept that will not come to fruition for a few years. However, we’ve seen early stages of machine learning applications in verticals such as advertising and retail. In the years ahead, we’ll see more industries, including industrial IoT, digital health and digital finance, begin taking advantage of machine learning within applications to provide more meaningful user experiences. Throughout this transformation, the database will play an instrumental role by accommodating rapidly-changing data at scale while keeping big data sets reliable and secure.”
Chetan Dube, President and CEO at IPSoft, said: “IoT, until this point, primarily has been about point to point connectivity. With AI as the glue from cognitive front end and extended automation executing through the supply chain we’ll see intelligent automation reach new levels. The car industry is accelerating fast down this path but expect hospitality, healthcare and retail to be closing in with solutions that really capitalize on this eco-system of AI innovation.”