Saturday, October 31

Machine Learning

Machine Learning

CHATBOTS FOR CUSTOMER SERVICE
Machine Learning

CHATBOTS FOR CUSTOMER SERVICE

A few days ago I had a terrible shopping experience while browsing for an Ethnic wear on India’s biggest clothing website. I was looking for a “Lehenga” of a specific type. There were so many options with no proper product description. I tried to contact customer support, ten minutes passed by, and even after navigating through multi IVR options, I didn’t get connected to any agent. After waiting for a pretty long time, I logged out. With lockdown and social distancing as the new normal, I can’t even visit the store and I just wonder — why is it so difficult to get answers to my questions from my favorite brand?Chatbots for Customer ServiceBefore i explain further on how AI Chatbots could have made a significant difference to my shopping journey above, let’s first understand some basics ab...
“Hey Google” Smart Home Summit — All That You Need to Know
Machine Learning

“Hey Google” Smart Home Summit — All That You Need to Know

“Hey Google” Smart Home Virtual Summit took place recently, with the revelation of tons of new features. Google is bent on bring about more smart home automation globally, and it envisions Google Assistant as the heart of it all.The new features showcased at the “Hey Google” Smart Home Virtual Summit marked the official reveal of all the new features of Google’s smart home ecosystem, Google Assistant, and Nest brand.However, the smart home updates as unveiled in “Hey Google” Smart Home Virtual Summit shall rise into prominence for the masses in late 2020, when Android 11 releases.Android 11 is supposed to have a separate section dedicated to facilitating smart home operations. They mostly include operations such as choosing whichever device controls users want in the menu or accessing Goog...
This month in AWS Machine Learning: July 2020 edition
Machine Learning

This month in AWS Machine Learning: July 2020 edition

Every day there is something new going on in the world of AWS Machine Learning—from launches to new use cases like posture detection to interactive trainings like the AWS Power Hour: Machine Learning on Twitch. We’re packaging some of the not-to-miss information from the ML Blog and beyond for easy perusing each month. Check back at the end of each month for the latest roundup. Launches As models become more sophisticated, AWS customers are increasingly applying machine learning (ML) prediction to video content, whether that’s in media and entertainment, autonomous driving, or more. At AWS, we had the following exciting July launches: On July 9, we announced that SageMaker Ground Truth now supports video labeling. The National Football League (NFL) has alre...
Code-free machine learning: AutoML with AutoGluon, Amazon SageMaker, and AWS Lambda
Machine Learning

Code-free machine learning: AutoML with AutoGluon, Amazon SageMaker, and AWS Lambda

One of AWS’s goals is to put machine learning (ML) in the hands of every developer. With the open-source AutoML library AutoGluon, deployed using Amazon SageMaker and AWS Lambda, we can take this a step further, putting ML in the hands of anyone who wants to make predictions based on data—no prior programming or data science expertise required. AutoGluon automates ML for real-world applications involving image, text, and tabular datasets. AutoGluon trains multiple ML models to predict a particular feature value (the target value) based on the values of other features for a given observation. During training, the models learn by comparing their predicted target values to the actual target values available in the training data, using appropriate algorithms to improve their prediction...
Enhancing recommendation filters by filtering on item metadata with Amazon Personalize
Machine Learning

Enhancing recommendation filters by filtering on item metadata with Amazon Personalize

We’re pleased to announce enhancements to recommendation filters in Amazon Personalize, which provide you greater control on recommendations your users receive by allowing you to exclude or include items to recommend based on criteria that you define. For example, when recommending products for your e-retail store, you can exclude unavailable items from recommendations. If you’re recommending videos to users, you can choose to only recommend premium content if the user is in a particular subscription tier. You typically address this by writing custom code to implement their business rules, but you can now save time and streamline your architectures by using recommendation filters in Amazon Personalize. Based on over 20 years of personalization experience, Amazon Personalize enables...
Director of National Intelligence Releases Six Principles for Ethical AI
Machine Learning

Director of National Intelligence Releases Six Principles for Ethical AI

US intelligence agencies have released six principles for the ethical use of AI, emphasizing transparency, equity and security. (GETTY IMAGES) By AI Trends Staff This week, the Office of the Director of National Intelligence (ODNI) released the first of an evolving set of principles for the ethical use of AI. The six principles, ranging from privacy to transparency to cybersecurity, were described as Version 1.0 and were approved by John Ratcliffe, Director of National Intelligence. The six principles are positioned as a guide for the nation’s 17 intelligence agencies, especially to help them work with private companies contracted to help the government build systems incorporating AI, according to an account in Breaking Defense. The intelligence agency principles co...
Coping With A Potential Mobility Frenzy Due To AI Autonomous Cars
Machine Learning

Coping With A Potential Mobility Frenzy Due To AI Autonomous Cars

If true self-driving cars become available, would we become more enamored of using cars to take many more short trips, thus increasing traffic and pollution? (GETTY IMAGES) By Lance Eliot, the AI Trends Insider Walk or drive? That’s sometimes a daily decision that we all need to make. A colleague the other day drove about a half block down the street from his office, just to get a coffee from his favorite coffee shop. You might assume that foul weather prompted him to use his car for the half-block coffee quest rather than hoofing the distance on foot. Nope, there wasn’t any rain, no snow, no inclement weather of any kind. Maybe he had a bad leg or other ailments? No, he’s in perfectly good health and was readily capable of strutting the half-block distance. Here in...
AI Can Help Protect Smart Home IoT Devices from Hackers
Machine Learning

AI Can Help Protect Smart Home IoT Devices from Hackers

Smart home hubs and IoT devices, poised for dramatic growth, have an immature security infrastructure. AI can help manage the complexity. (Stephan Bechert on Unsplash) By AI Trends Staff As researchers continue to find security flaws in smart home hub IoT devices, part of an immature security infrastructure. One researcher suggests AI can be helpful to address the vulnerabilities. A cybersecurity team from ESET, an internet security company based in Slovakia, found bugs in three different hubs dangerous enough to trigger remote code execution, data leaks and Man-in-the-Middle attacks, according to a recent account from ZDNet.  The hubs were: the Fibaro Home Center Lite, eQ-3’s Homematic Central Control Unit (CCU2) and ElkoEP’s eLAN-RF-003. The issues were reported t...
Researcher Developing Smart Chips to Address Battery Safety
Machine Learning

Researcher Developing Smart Chips to Address Battery Safety

Battery development firm KVI is working on smart chips to improve the safety and performance of lithium-ion batteries, used in many devices today from electric vehicles to smartphones. (GETTY IMAGES) By AI Trends Staff The number one issue in lithium-ion batteries powering products from e-bikes and power tools for consumers, to self-driving cars and submarines, is to enhance battery safety, Dr. Rachid Yazami told an audience at the virtual International Battery Seminar from Cambridge EnerTech this week. Dr. Yazami, founder of Singapore startup KVI, which is developing smart chips to enhance battery performance and safety, is known for his critical role in the development of lithium-ion batteries. In a talk on whether AI can help address battery issues, he outlined t...
AI Has Track Record in Fraud Prevention for Credit Card Issuers
Machine Learning

AI Has Track Record in Fraud Prevention for Credit Card Issuers

Credit service providers Visa and Experian have a track record in using AI for fraud detection. (GETTY IMAGES) By John P. Desmond, AI Trends Editor The financial services industry has compiled a track record in the use of AI for fraud detection, with AI applications at Visa and Experian being two notable examples. The multinational Visa reports saving an estimated $25 billion annually from use of AI applications for fraud detection, according to Melissa McSherry, a senior VP and global head of data for Visa, according to an account in VentureBeat. The path to AI Visa chose may have lessons for other companies thinking about how to launch their automation projects. “We have definitely taken a use case approach to AI,” McSherry stated. “We don’t deploy AI for the sake...