Collaborating Authors

Consumer Products & Services

Artificial Intelligence and Computer Vision Help Prevent Indigestion


Identifying different foods on a tray can be a non-trivial task (Image source: Chris A. Tweten on Unsplash) Unfortunately, we don't always have sufficient time to enjoy a leisurely lunchtime meal. Suppose some of your workmates invite you to join them for lunch at a local fast-food restaurant. You all typically have a limited amount of time for your lunchtime break and you need to use this time wisely and efficiently. First, you have to get to the restaurant, either by walking or perhaps by taking a short drive. When you reach the restaurant, you have to select your food, pay for it, and eat it.

Optimizing Limousine Service with AI

AI Magazine

A common problem for companies with strong business growth is that it is hard to find enough experienced staff to support expansion needs. This problem is particular pronounced for operations planners and controllers who must be very highly knowledgeable and experienced with the business domain. This article is a case study of how one of the largest travel agencies in Hong Kong alleviated this problem by using AI to support decision-making and problem-solving so that their planners and controllers can work more effectively and efficiently to sustain business growth while maintaining consistent quality of service. AI is used in a mission critical fleet management system (FMS) that supports the scheduling and management of a fleet of luxury limousines for business travelers. The AI problem was modeled as a constraint satisfaction problem (CSP).

Deploying nEmesis: Preventing Foodborne Illness by Data Mining Social Media

AI Magazine

Foodborne illness afflicts 48 million people annually in the U.S. alone. Over 128,000 are hospitalized and 3,000 die from the infection. While preventable with proper food safety practices, the traditional restaurant inspection process has limited impact given the predictability and low frequency of inspections, and the dynamic nature of the kitchen environment. Despite this reality, the inspection process has remained largely unchanged for decades. CDC has even identified food safety as one of seven "winnable battles"; however, progress to date has been limited.

Amazon's Echo Look fashion camera will stop working on July 24th


We hope you wren't leaning on Amazon's Echo Look for fashion advice -- you'll have to find an alternative soon. Simply put, the company no longer feels the Look is necessary given recent changes. Now that Style by Alexa features have found their way into Alexa devices and the Amazon Shopping app, "it's time to wind down" the Look, a spokesperson said. You can read the complete statement below. You aren't completely stranded if the smart camera was a mainstay of your morning routine.

Delivery robots maneuvering to devour food delivery market


It's free if you're a healthcare worker in certain areas in the U.S. and U.K. served by Starship Technologies, one of a handful of robotic delivery companies whose business models have been in hyper-drive these last few months. As restrictions related to COVID-19 gradually ease, developers and service providers in the autonomous delivery space are scrambling to eat as much market share as possible in the still-limited locations where they're authorized. But even robotic delivery, which seems perfectly tailored to the locked-in reality of early 2020, hasn't been spared by the pandemic, and these next few weeks will set the tone for the sector for years to come. In general, the food delivery market is walking a fine line, attempting a sensitive response to the upheaval of these last few months while also keenly aware that there's a customer grab underway and the landscape for the market will largely be remapped during the lockdown. Postmates and Uber Eats have slashed delivery prices and rolled out free delivery programs for certain affected customers, for example, which has the dual advantage of coming off as sensitive and helping the delivery leaders capture new customers.

How tech will change the way we work by 2030


Technologies like Artificial Intelligence (AI), Machine Learning (ML) and Blockchain will have a significant impact on work in the next decade and beyond. But if you believe the sci-fi hype or get bogged down in the technology, it can be difficult to relate them to today's workplaces and jobs. Here are three everyday examples of their potential, expressed in terms of the business challenge they are addressing or how consumers will experience them. I don't mean to over simplify – these are powerful tools – but I think their potential shines through best when they're expressed in their simplest terms. What do you imagine the restaurant of the future to look like?

Marty the Robot Rolls out AI in the Supermarket - AI Trends


When six-foot-four inch Marty first rolled into Stop & Shop, the robot walked into history. Social robot experts say it is among the first instance of a robot deployed in a customer environment, namely supermarkets in the Northeast. Marty rolls around the store looking for spills with its three cameras. It does take the place of the human worker, called an associate, that did the same thing, but it means the associate can do something else. Doing the walk-around of the store is seen as a mundane task.

Emotional AI platform reveals that smiles are down 32% due to COVID-19 - ClickZ


Headquartered in London, Realeyes is an eye-tracking and emotion measurement platform that uses AI and machine learning to gain insight into human behavior and expression. Their clients include Buzzfeed, Coca-Cola, Conde Nast, eBay, Mars, and Publicis Groupe, among others. Realeyes uses front-facing cameras, computer vision and machine learning technologies to detect attention and emotion among opt-in audiences as they watch video content. ClickZ recently spoke with Max Kalehoff, VP of Marketing & Growth for Realeyes to discuss the company's innovative technology and the capabilities they bring to marketers and publishers. Kalehoff learned about Realeyes after co-leading a panel presentation with Realeyes's CEO at the Sustainable Brands Conference in 2017.

EasyJet admits it was aware of 'highly sophisticated cyber attack' that affected 9 million customers as early as January

The Independent - Tech

Budget airline easyJet was aware of the data breach, which revealed personal information of nine million customers and the credit card information of over 2,200 customers, in January. News of the cyber attack broke yesterday, revealing that the attacker or attackers had access to the data of customers who booked flights from 17 October 2019 to 4 March 2020. In a statement, the airline said: "We're sorry that this has happened, and we would like to reassure customers that we take the safety and security of their information very seriously. "There is no evidence that any personal information of any nature has been misused." However, while there is no evidence the data was misused, that does not mean that it cannot be misused. Experts suggest that personal information "drives a higher price on the dark web" – the area of the internet inaccessible by mainstream search engines – and could be used for organised crime or ransomed. What does the easyJet data hack mean for you? What does the easyJet data hack mean for you? Two people with knowledge of the investigation have said that Chinese hackers are supposedly responsible for the hack based on similarities in hacking tools and techniques used in previous campaigns, but that has yet to be officially confirmed. In a statement, the Information Commissioners' Office (ICO) said: "We have a live investigation into the cyber attack involving easyJet.

What can your microwave tell you about your health?


For many of us, our microwaves and dishwashers aren't the first thing that come to mind when trying to glean health information, beyond that we should (maybe) lay off the Hot Pockets and empty the dishes in a timely way. But we may soon be rethinking that, thanks to new research from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). The system, called "Sapple," analyzes in-home appliance usage to better understand our health patterns, using just radio signals and a smart electricity meter. Taking information from two in-home sensors, the new machine learning model examines use of everyday items like microwaves, stoves, and even hair dryers, and can detect where and when a particular appliance is being used. For example, for an elderly person living alone, learning appliance usage patterns could help their health-care professionals understand their ability to perform various activities of daily living, with the goal of eventually helping advise on healthy patterns.