Intelligent Gamechangers … AI is driving radical business innovation … AliveCor to Barbie, Darktrace to Infervision, Microsoft and nuTonomy
September 17, 2018
Almost every industry and realm of life is set to be transformed by it, with the estimation that by 2020, 95 per cent of all customer interactions will be carried out by some form of AI. When it comes to business innovation, it is one of the most exciting technologies available, with PwC estimating that it could add $15.7 trillion to the global economy by 2030.
“Everything invented in the past 150 years will be reinvented using AI within the next 15 years,” predicts San Francisco-based Randy Dean, chief business officer at Launchpad.AI.
It is already having a transformative effect in a number of industries. In sales AI can help strengthen pitches by detecting and reacting to consumer emotions. Japanese investment bank, Daiwa Securities, found that customer purchase rate increased by 2.7 times after they implemented AI technology.
In the healthcare and pharmaceutical sectors, AI tools have been built which can sort and accumulate medical knowledge and data on a scale humans could only dream of. At one end of the spectrum sit dosage error deduction and virtual nursing assistants, at the other: genome sequencing. AI has brought the time and cost of sequencing someone’s genome, which is the unique arrangement of their DNA, down to 24 hours and just $1,000 respectively.
Whilst Apple Watch 4 has focused on its new ability to create cardiograms, AliveCor developed the first smartphone-connected electrocardiogram, or EKG, called Kardia, which detects abnormal heart rhythms on a phone in much the same way that an EKG in a hospital records the electrical activity of the heart. This means that patients can check their heart health regularly and find out within 30 seconds whether their results are normal or they should seek medical attention. That’s particularly important for millions of Americans at risk for arrhythmias, which may be symptomless and can result in potentially fatal outcomes like heart failure and stroke. By the end of 2017, AliveCor had helped customers record more than 20 million EKGs. Now it’s focused on rolling out further heart-monitoring technologies. “At core,” says CEO Vic Gundotra, “we are an AI company disguised as a medical device company.” AliveCor’s new KardiaBand EKG reader is the first FDA-approved medical-grade accessory for the Apple Watch, and the company also recently released machine-learning software called SmartRhythm, which continuously analyzes data from the watch’s built-in heart-rate sensor and accelerometer to spot unexpected patterns. In addition, AliveCor has partnered with Columbia and other top medical schools on clinical trials to see if its devices can identify even more lifesaving signals in the EKG, including early warning signs of long QT syndrome, a leading cause of sudden death in younger people.
Amex anticipating fraud
American Express processes $1 trillion in transaction and has 110 million AmEx cards in operation. They rely heavily on data analytics and machine learning algorithms to help detect fraud in near real time, therefore saving millions in losses. Additionally, AmEx is leveraging its data flows to develop apps that can connect a cardholder with products or services and special offers. They are also giving merchants online business trend analysis and industry peer benchmarking.
Burberry gets personal
When you first think of Burberry, you likely consider its luxury fashion and not first consider them a digital business. However, they have been busy reinventing themselves and use big data and AI to combat counterfeit products and improve sales and customer relationships. The company’s strategy for increasing sales is to nurture deep, personal connections with its customers. As part of that, they have reward and loyalty programs that create data to help them personalize the shopping experience for each customer. In fact, they are making the shopping experience at their brick-and-mortar stores just as innovative as an online experience.
Darktrace’s immune system
We’re all ultra conscious about the vulnerability of our devices and systems to cyber attack. Darktrace’s Enterprise Immune System (EIS) slows attacks on computing systems by emulating the way humans fend off viruses: The AI-enabled platform embeds in a network, learns what behaviors are normal, and flags anomalies. It became more formidable last April with the launch of Antigena, which automatically stops or slows compromised networks and devices. “Our system is self-running,” says CEO Nicole Eagan, “so [customers] don’t have to touch anything.” When the WannaCry ransomware proliferated last May, Antigena disrupted it in less than 30 seconds. More than 4,000 networks (including the city of Las Vegas) rely on EIS, worth some $300 million in contracts.
Using natural language processing, machine learning and advanced analytics, Hello Barbie listens and responds to a child. A microphone on Barbie’s necklace records what is said and transmits it to the servers at ToyTalk. There, the recording is analyzed to determine the appropriate response from 8,000 lines of dialogue. Servers transmit the correct response back to Barbie in under a second so she can respond to the child. Answers to questions such as what their favorite food is are stored so that it can be used in conversation later.
AI and deep learning is being put to use to save lives by Infervision. In China, where there aren’t enough radiologists to keep up with the demand of reviewing 1.4 billion CT scans each year to look for early signs of lung cancer. Radiologists need to review hundreds of scans each day which is not only tedious, but human fatigue can lead to errors. Infervision trained and taught algorithms to augment the work of radiologists to allow them to diagnose cancer more accurately and efficiently.
Central to everything Microsoft does is leveraging smart machines. Microsoft has Cortana, a virtual assistant; chatbots that run Skype and answer customer service queries or deliver info such as weather or travel updates and the company has rolled out intelligent features within its Office enterprise. Other companies can use the Microsoft AI Platform to create their own intelligent tools. In the future, Microsoft wants to see intelligent machines with generalized AI capabilities that allow them to complete any task.
Pinterest started as a fun way of sharing images, an online pin board of visual inspiration, founded in 2009 by Ben Silbermann, Evan Sharp, and Paul Sciarra. Covering everything from travel to home renovation projects, it is a unique social platform that gives its users a place to express what they want in the future. Every idea is represented by a “pin” that includes an image, a description, and a link back to the image’s source online where they can learn more about the idea. Pins can then be further organized into “boards,” which sort ideas based on categories. Every month, Pinterest processes hundreds of millions of image searches in its bid to help users find things they’re most interested in. It is increasingly turning to machine learning to surface content that resembles objects its users have already pinned—so if someone pins a picture of, say, a midcentury table, it will automatically recommend that they look at pictures of other furniture from the same era. In 2017, seven years after encouraging users to curate the internet with photos rather than hyperlinks, Silbermann and Sharp unveiled their next act: Pinterest Lens, which enables people to search for information and inspiration simply by aiming their phones’ cameras at objects around them. Advertisers are increasingly embracing Pinterest—2017 revenue was reportedly just shy of $500 million, up 64% from the previous year.
Big data analytics is helping Netflix predict what its customers will enjoy watching. They are also increasingly a content creator, not just a distributor, and use data to drive what content it will invest in creating. Due to the confidence they have in the data findings, they are willing to buck convention and commission multiple seasons of a new show rather than just a pilot episode.
NuTonomy’s driverless brain
Whilst Apple and Google, GM and Tesla have dominated the driverless car headlines, autonomy has been quietly making the most progress. Created by former MIT faculty, researchers, and graduates, self-driving car startup nuTonomy has been getting autonomous cars on roads from Boston to Singapore, where it has been providing autonomous taxis since 2016. NuTonomy has also partnered with Group PSA, owner of European car brand Peugeot SA, to bring self-driving SUVs to Singapore. In June 2017, nuTonomy teamed up with Lyft to figure out how autonomous vehicles work in practice, whether they’re put toward ride sharing or personal ownership. The two companies began rolling out the fruits of their labor in late 2017 with a self-driving car pilot in parts of Boston. NuTonomy’s high-profile successes caught the attention of car-part supplier Delphi Automotive, which acquired the startup in October 2017 for $450 million. The move beefs up Delphi’s self-driving car mission and gives nuTonomy more scale through Delphi’s resources and distribution.
Cars are increasingly connected and generate data that can be used in a number of ways. Volvo uses data to help predict when parts would fail or when vehicles need servicing, uphold its impressive safety record by monitoring vehicle performance during hazardous situations and to improve driver and passenger convenience. Volvo is also conducting its own research and development on autonomous vehicles.