Artificial Intelligence (AI) is no longer a nebulous concept that lies over the horizon. The fourth industrial revolution, powered by AI, is already here and these advanced systems are helping us scale human knowledge and expertise. AI represents a significant economic opportunity for the United Kingdom. In fact, recent research from IBM and the Confederation of British Industry (CBI) found that around 20% of British firms have already deployed practical applications of AI. To gain a greater understanding of the potential impact of AI and what the future could hold, the UK House of Lords recently issued a call for views from interested parties.
The wait is over, Artificial Intelligence is here. If your company isn't doing it, start looking for a new job. Obsolescence, decline, and/or bankruptcy are around the corner. Take for example drinks giant Coca-Cola, which used the mighty power of Artificial Intelligence to come up with a new flavor, Cherry Sprite, based on the mixes we puny humans selected from their make-your-own "Freestyle" machines. Greg Chambers, Coca-Cola's head of digital innovation summed up their AI-powered strategy at a conference recently: It's hard to argue with that.
In a blog post today, Intel (NASDAQ:INTC) CEO Brian Krzanich announced the Nervana Neural Network Processor (NNP). The Intel Nervana NNP promises to revolutionize AI computing across myriad industries. Using Intel Nervana technology, companies will be able to develop entirely new classes of AI applications that maximize the amount of data processed and enable customers to find greater insights – transforming their businesses... We have multiple generations of Intel Nervana NNP products in the pipeline that will deliver higher performance and enable new levels of scalability for AI models. This puts us on track to exceed the goal we set last year of achieving 100 times greater AI performance by 2020.
"PREDICTION IS VERY difficult, especially if it's about the future," said Physics Nobel Laureate Niels Bohr. Bohr was presumably talking about the vagaries of quantum mechanical subatomic life, but the statement holds true at other scales too. Predicting the future is tough, and any good scientist knows enough to hedge his or her bets. That's what error bars are all about. It's why science usually proceeds methodically: hypotheses are formulated, experiments conducted, observations collated, and data evaluated.
An unfortunate fact about humanity is that people lie. While this is a chronic issue for human relations, it's one that may be less of an issue for marketers of the future, thanks to non-human intervention. For most of marketing history, the best way to find out if consumers liked a proposed product was to ask them what they thought about it. But in focus groups especially, people tend to stretch the truth, undermining the value of the entire study. In recent years, AI has offered a huge boost to neuromarketing -- the science of reading consumers' minds to gauge their reactions to marketing stimuli.
There will be many people who will say it does exist and has working technologies, hardware and software. It is an interesting error in thinking to focus on closed system devices/products as to what Ubiquity (IoT3) is. Devices are used to get across the point of various types of connections and networks being accessed. But more importantly in a full implementation of the concept of Ubiquity (often described as the IoT) devices may not even be owned anymore. The ownership of devices ceases to be important if you can own your digital identity, can verify it and establish your own ecosystem of assets in Blockchain.
A broad array of new digital tools and trends can help you re-imagine the customer journey. "Digital transformation" is a slippery term for marketers and other senior executives. It is so often used that many are vague about its actual meaning. There is a common misconception that companies must rush to refashion themselves as "digital first". After all, customers around the world increasingly live online.
Paypal has a deep learning system that filters out deceptive merchants and cracks down on sales of illegal products. Citibank's Citi Ventures arm recently invested in Feedzai, a machine learning company that identifies and prevents fraudulent transactions before they're completed. A few investment firms, including Aidyia Limited of Hong Kong, have launched funds managed entirely by AI. San Francisco startup Sentient Technologies, which develops AI software, created its own hedge fund based on its deep learning technologies. Swiss AI startup NNSAISENSE and Acatis Investments, a German fund manager, recently launched "Quantenstein," a deep learning software platform that helps investors choose the best stocks and build portfolios.
Every year, companies spend 1.3 trillion dollars on 265 billion customer service calls. That's five bucks a call. On average, the cost to find and hire a call center agent costs $4000 (not including salary), with an additional $4,800 for training -- and with frustrated agents tending to drop like flies in the face of an often brutally stressful job, these costs mount up. AI, or what IBM calls cognitive computing, is changing that. Autodesk began piloting the IBM Watson Conversation Service in June 2016 as a virtual agent called OTTO, later enhancing it and renaming it AVA (Autodesk Virtual Agent) in February 2017.
Historically, when new technologies become easier to use, they transform industries. That's what's happening with artificial intelligence and big data; as the barriers to implementation disappear (cost, computing power, etc.), more and more industries will put the technologies into use, and more and more startups will appear with new ideas of how to disrupt the status quo with these technologies. By my predictions, the AI revolution isn't coming, it's already here, and we'll see it first in a few key sectors. Most people agree that healthcare is broken, and many startups believe that the biggest answer is putting the power back in the hands of the patient. We're all carrying the equivalent of Star Trek's tricorder around in our pockets (or an early version, at any rate) and smartphones and other smart devices will continue to advance and integrate with AI and big data to allow individuals to self-diagnose.