By Moshe Kranc,CTO, Ness Digital Engineering
Unless you’ve been stranded on Mars for the past year, it’s impossible to miss the hype surrounding the hottest new technologies: Artificial Intelligence (AI), Internet of Things (IoT) and blockchain. Companies are releasing new products based on them, investors seem to be in a feeding frenzy to invest in them, and the press can’t heap enough praise on them. In the midst of all the hype, it’s hard to objectively assess the long-term impact of any of these technologies. One useful way to sift through the hype is to focus on use cases: what real world problems can a given technology solve better than any other existing alternative? Let’s apply this methodology to the hottest technologies:
The idea of blockchain is to eliminate centralized ledgers and replace them with distributed ledgers, where any fact can be proven because “everybody knows.” There are many use cases involving a central ledger where a blockchain distributed ledger has been considered. For example:
• Supply chain management for a supermarket
• Tracking test results for drugs that must be tested by a number of distinct entities
• Tracking ownership of diamonds and other rare gems
• Managing ticket sales for a concert
But, it requires a very special set of circumstances for blockchain to be the right solution: The domain must have a central authority that can force all parties to use the distributed ledger, the requirements for total number of transactions processed per second must be low, and there must be a compelling reason not to implement a centralized ledger, e.g., lack of continuous data communications among involved parties. There are such use cases in the world, but they represent a significant subset of the use cases in which blockchain pilots are being developed.
That’s why so few blockchain pilots actually get deployed into production. In far too many cases, blockchain has become a technology in search of a problem with promises that the big breakthrough for blockchain is just around the corner. Blockchain has valuable uses, but it is not the panacea it is being hyped to be.
Artificial Intelligence is not just hype – it’s real, and it has matured to the point where it can bring tangible benefit to the enterprise in 2018. Some examples of how the enterprise can benefit from AI:
• Data cleansing: Tools like Paxata and Tamr use AI to automatically cleanse Big Data with humans required only to handle “gray areas.”
• Customer interaction: Chatbots can be deployed that engage in a dialogue with the customer and provide good answers to most questions, and defer to humans to answer more complex questions. The interface to these chatbots can be via typed text or via bi-directional speech.
• Churn analysis: AI can identify behavior patterns that are leading indicators of customer churn and provide a retention plan that is personalized to each wavering customer.
There seems to be justification for the hype surrounding AI because we are only at the beginning of:
• Technological capabilities: The technology actually works and still has a lot of room for growth, with researchers announcing new techniques and capabilities seemingly on a daily basis.
• Use cases: Every day seems to bring a new announcement of another use case for which AI is being deployed, e.g., for piloting drone aircraft, analyzing soil to help farmers choose the best fertilizer mix, analyzing x-rays to help radiologists work more accurately.
Expect to see the use cases for AI continue to proliferate.
Internet of Things
IoT has been unfairly maligned as a trend that never happened, despite the fact that we are surrounded by successful examples:
• Wearable sensors like Fitbit that collect and analyze biometric data
• Navigation systems like Waze that discover traffic jams based on users’ movements
• Smart home meters like Nest that can dramatically reduce utility costs
• Automobile sensors like MobileEye that warn drivers of approaching hazards
Perhaps the disappointment surrounding IoT is due to the fact that its most dramatic use cases have not yet achieved critical mass, e.g.:
• Smart stores where checkout counters are no longer necessary – sensors can determine what you have put in your shopping basket and charge you automatically as you leave the store.
• Smart cars that drive themselves and require little to no maintenance because problems can be detected and often corrected remotely.
• Smart cities that can use sensors to provide public services that are coordinated and optimized, such as where to find open parking spaces in city lots.
These are grandiose use cases, and some of them will no doubt fail. But, that does not diminish the relevance or reality of IoT. In fact, the same is true of blockchain and AI too. All have their place, and they will succeed in the cases where they provide better solutions to problems than alternative technologies can provide today.