CUSTOMER


Your Roomba could be selling maps of your home to Google, Amazon, and Apple

Mashable

"There's an entire ecosystem of things and services that the smart home can deliver once you have a rich map of the home that the user has allowed to be shared," said Colin Angle, iRobot's CEO. If the idea of a device spying on your flooring plan -- along with other data about your home -- and then selling that info to companies to help them improve their targeted ads seems particularly creepy to you, that's because, well, it is creepy. The privacy policy indeed states iRobot could share the users' personal data with other companies owned by iRobot, third party vendors and affiliates, the government, and "any company transaction, such as a merger, sale of all or a portion of company assets or shares." However, this is not necessarily personal data as protected under data protection law.


Analyst Perspectives Special Report - View - tbri.com

#artificialintelligence

A confluence of factors make 2017 the year artificial intelligence (AI) will reach an inflection point in enterprise adoption. Enterprise IT customers remain more skeptical about the promise of AI than vendors, but most accept AI will factor into their business futures. As the technical feasibility and business utility of AI come more into focus, the stage is set for AI commercialization. However, a significant gap remains between customer expectations and reality that must be closed for the AI market to flourish.


The double-edged sword of Artificial Intelligence

#artificialintelligence

Industrial players like Boeing and Tesla are making big bets on A.I., so it is reasonable to expect that we should see big investments coming through financial services also. In LinkedIn's recent Financial Services Insights Survey, Fintech professionals (63%) and investment bankers (55%) were the most interested in machine learning and A.I.-based investing as key technologies worth watching.


Roomba maker may share maps of users' homes with Google, Amazon or Apple

The Guardian

The maker of the Roomba robotic vacuum, iRobot, has found itself embroiled in a privacy row after its chief executive suggested it may begin selling floor plans of customers' homes, derived from the movement data of their autonomous servants. However, this is not necessarily personal data as protected under data protection law. The company's terms of service appear to give the company the right to sell such data already, however. When signing up for the company's Home app, which connects to its smart robots, customers have to agree to a privacy policy that states that it can share personal information with subsidiaries, third party vendors, and the government, as well as in connection with "any company transaction" such as a merger or external investment.


How to Get Real-time Insight with Machine Learning and Centralized Data

#artificialintelligence

Firms are still wrestling with the challenge of making big data work for them, in use cases ranging from enterprise analytics, customer 360, and product personalization to revenue assurance and fraud detection. As a unified platform that can economically store unlimited data and enable diverse access to it at scale, the enterprise data hub is emerging as the architectural center of a modern data strategy. Facebook, Google, and LinkedIn have pioneered big data and machine-learning approaches to protecting their subscribers and gaining insight into vast amounts of data. They start by combining their data silos into one vast data lake that can be tapped – using a combination of big data, Hadoop, and machine learning – to provide real-time information about anomalous behavior as it happens.


Machine Learning 101 & Predictive Buyer Scoring: How to Personalize your UX for Conversion E-commerce Nation

#artificialintelligence

As the e-commerce industry continues on its path of innovation, AI has taken to the forefront of innovating the customer experience. What was once science fiction is now very much a reality- and online retailers are jumping on board and trying out new ways to implement this into their business models. This webinar, "Machine Learning 101 and Predictive Buyer Scoring: How to Personalize your UX for Conversion" will delve into these topics, teaching you how to use AI that learns about your customer's behavior from the time they land on your page. Our guests, Jerry Abiog and Suresh Mahadevan of DXi will give you insight into the world of AI and its implications for e-commerce UX personalization.


Machine Learning 101 & Predictive Buyer Scoring: How to Personalize your UX for Conversion E-commerce Nation

#artificialintelligence

As the e-commerce industry continues on its path of innovation, AI has taken to the forefront of innovating the customer experience. What was once science fiction is now very much a reality- and online retailers are jumping on board and trying out new ways to implement this into their business models. This webinar, "Machine Learning 101 and Predictive Buyer Scoring: How to Personalize your UX for Conversion" will delve into these topics, teaching you how to use AI that learns about your customer's behavior from the time they land on your page. Our guests, Jerry Abiog and Suresh Mahadevan of DXi will give you insight into the world of AI and its implications for e-commerce UX personalization.


5 Technological Trends shaping up Connected Beauty in 2017

#artificialintelligence

The European hair care market clocked revenues worth USD 18 billion in 2013; it is anticipated to generate revenues worth $24 billion in 2018. Recently L'Oréal presented its flagship connected beauty innovations at Viva Technology Paris show held at Porte de Versailles in Paris from 15–17th June 2017.Five of it's Group's brands -- Lancome, Kérastase, L'Oréal Paris, La Roche-Posay and L'Oréal Professionnel -- showcased how they leverage advanced digital technologies to create personalized services for consumers. L'Oréal also discovered the new version of sun care innovation My UV Patch by La Roche-Posay, L'Oréal Group's dermatological skincare brand, designed as a wearable,the first stretchable skin sensor designed to monitor exposure to UV radiation(sun rays) minimizing the frequency of sun burns and to select the right sun protection based on user's skin type. The wearer simply scans the patch with his or her smartphone to determine the wearer's daily sun exposure.Thanks to the specific algorithm, the application uses graphs and statistics to provide advice on or optimal sun protection.It also takes account of hair and skin color into consideration and offers personalized UV protection recommendations.The app alerts the user when UV protection becomes insufficient.This ultra-thin self-adhesive patch comes fitted with an electronic sensor and analyses how much UV radiation the body receives.


How to create the 'perfect' AI-driven bot - Content Loop

#artificialintelligence

Our experience creating our travel assistant app, Mezi, illustrates key principles of AI regarding the ongoing role of human involvement and how to draw the dividing line between valued assistance and unwelcome intrusion. Remember, the goal isn't for your AI to be perfect, it's for your AI to be part of a perfect service. Both to surface the full value proposition of your service, and to deepen that sense of trust, it's important for your AI to anticipate a customer's needs and offer useful help without having to be asked. Snehal Shinde is the CTO and cofounder at Mezi, the personal shopping and travel service.


CrowdFlower expands to help companies implement machine learning

#artificialintelligence

CrowdFlower, a company that helps customers build AI systems by providing them with training data, announced today that it's getting into the business of helping companies implement machine learning. It could help existing customers get unstuck with a system that isn't working, assist businesses that have already implemented one machine learning system get started with something completely new, and also get brand new customers started with implementing AI. This doesn't mean that CrowdFlower is abandoning its work providing companies with training data -- quite the contrary. Monica Rogati and Adrian Weller -- both veterans of the machine learning ecosystem -- will give CrowdFlower input on its technology and product strategy, as well as advising the company on developments in the AI ecosystem at large.