Artificial intelligence (AI) has long been a staple of science fiction, but the truth is that we’re not so far away from some of the scenarios we have so far seen only in movies and on television. Many people already interact with AI on a daily basis, whether it’s working with personal assistants on our smartphones, getting help from online support chat bots, or talking to “smart” devices in our homes and cars. But what is AI exactly, and how will it shape our future?

At a recent Royal Society Science Matters event in London, Professor Brian Cox hosted a panel of five experts to discuss various AI topics, including applying AI technologies to drive medical advances through gene modelling, using machine learning to manage swarms of microbots, and investigating the ethical questions raised by the creation and use of artificial intelligence. There was a lot of interesting debate, starting with the definition of the term “artificial intelligence” itself—but the panel agreed on a few key findings:

AI is already here

AI has arrived, but what we see today is primarily “Artificial Narrow Intelligence” (ANI), in which machine learning is applied within a specific narrow context with defined boundaries. Good examples of ANI include speech recognition technology or connected cars. The truth is, we are still a ways away from true AI, which is able to function effectively without a defined context—the way the human brain does naturally.

AI is better than humans

A stark statement, but true all the same. For years, human beings have applied tools and technology to help do their work. From the invention of the wheel all the way through the Industrial Revolution to the dawn of the Computer Age, humans have been able to exceed their limitations with the help of technology. Applying AI to specific problems could allow us to make huge advances in medicine, science, technology, and the environment that might otherwise either be impossible or at the very least take decades or even centuries to achieve.

AI really is going to take people’s jobs

Another stark statement, but this is just the natural evolution of technology. Throughout history, automation has almost always resulted in the need for less manual labour. However, as jobs disappear from one industry, new jobs often appear in others, and in general overall personal wealth and quality of life have grown alongside these kinds of changes. The challenge moving forward is to ensure that this new wealth is distributed fairly and does not result in the creation of an elite class that leaves the majority of people behind.

Why AI is exploding right now

But perhaps the most significant area of agreement among the panelists concerned the three factors most responsible for the growth in the development of AI and machine learning we are experiencing right now:

  1. Data. AI and machine learning rely on enormous amounts of high-quality data from which to observe trends and behaviour patterns, as well as being able to quickly adapt to improve the accuracy of the conclusions derived from the analysis of that data. Today we generate vast amounts of data, and both the quantity and quality of that data continues to grow.
  1. Compute resources. In the past, developing and running machine learning algorithms required access to a limited number of super-computer resources. Today, however, massive advances in processing power and the explosion of cloud-based computing offers easier access to the sort of extensible compute resources once available only to a select few.
  1. Algorithms. The two factors above have enabled organisations to exploit AI’s potential by developing new algorithms to target specific domains and drive specific outcomes. These outcomes may be those that we will see in our daily lives, like driverless cars or automated drone deliveries. However, a significant amount of AI will work behind the scenes, enabling the delivery of experiences, services, and security.

AI behind the scenes

So how might we see AI changing our lives in the near term? Of course we will see more new applications of ANI in the consumer market like the ones showcased at this year’s CES show in Las Vegas. But for every product, service, or offering delivered to the consumer, there is a huge amount of supporting technology that is constantly changing and evolving on the backend.

Managing that complexity, scale, performance, and availability is a huge challenge, and one in which AI/machine learning has a significant role to play. It is no longer possible for individuals to handle the volume and variability of raw data being produced by today’s modern systems, nor is it possible to predict all potential scenarios that may impact a company’s ability to deliver services to its customers. This is another area where AI can make a significant contribution.

At our recent FutureStack 2016 conference in San Francisco, New Relic CEO Lew Cirne offered a technical preview of our new Project Seymour. We believe Project Seymour could form the basis of a game-changing new AI platform. Seymour uses machine learning to help guide our customers to the most interesting, most relevant, and most actionable bits of their own data so they can see their digital businesses even more clearly.

With the introduction of Project Seymour on top of our Digital Intelligence Platform, New Relic hopes to apply effective AI to the business of managing your digital business. Artificial Intelligence has the potential to change all our lives and the world we live in. But for right now, it’s busy behind the scenes driving exceptional customer experiences, satisfaction, loyalty, and revenue.

We expect to preview Project Seymour to a handful of New Relic customers. If you’re interested in participating in this technology preview to give us feedback, please sign up here.


Neil MacGowan as our Director of Digital Intelligence brings his extensive experience from the LOB through to the ISV, to help customers discover and realise the full potential value of technology to their business. Most recently Neil has been helping customers to transform their IT organisations and businesses through the application of analytics, machine learning, and AI systems within the Service Management space with organisations such as Mercury/HP, Netuitive, and ServiceNow. View posts by .

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