Personal Assistant Systems
Tinder Co-Founders Sue App's Owners For At Least $2B, Saying They Were 'Cheated'
The logo for the Tinder app, seen on a mobile phone screen in London in November 2016. The logo for the Tinder app, seen on a mobile phone screen in London in November 2016. Tinder's co-founders, along with eight other current and former executives, have slapped the popular dating app's owners with a massive lawsuit. In the suit filed Tuesday in New York, the Tinder employees past and present say the companies that own the app deliberately undervalued it to swindle them out of the money they were owed. And that is no small sum, according to founders Sean Rad, Justin Mateen, Jonathan Badeen and their fellow plaintiffs.
Social Mediaโbased Conversational Agents for Health Management and Interventions
Conversational agents could provide timely and cost-effective social support to promote behavioral changes and improve healthcare outcomes. The authors evaluated the performance of their social media-based conversational agent in a smoking cessation program. Results showed that the presence of a conversational agent effectively increased participant engagement and enhanced their smoking cessation outcomes.
Shedding Light on Black Box Machine Learning Algorithms: Development of an Axiomatic Framework to Assess the Quality of Methods that Explain Individual Predictions
From self-driving vehicles and back-flipping robots to virtual assistants who book our next appointment at the hair salon or at that restaurant for dinner - machine learning systems are becoming increasingly ubiquitous. The main reason for this is that these methods boast remarkable predictive capabilities. However, most of these models remain black boxes, meaning that it is very challenging for humans to follow and understand their intricate inner workings. Consequently, interpretability has suffered under this ever-increasing complexity of machine learning models. Especially with regards to new regulations, such as the General Data Protection Regulation (GDPR), the necessity for plausibility and verifiability of predictions made by these black boxes is indispensable. Driven by the needs of industry and practice, the research community has recognised this interpretability problem and focussed on developing a growing number of so-called explanation methods over the past few years. These methods explain individual predictions made by black box machine learning models and help to recover some of the lost interpretability. With the proliferation of these explanation methods, it is, however, often unclear, which explanation method offers a higher explanation quality, or is generally better-suited for the situation at hand. In this thesis, we thus propose an axiomatic framework, which allows comparing the quality of different explanation methods amongst each other. Through experimental validation, we find that the developed framework is useful to assess the explanation quality of different explanation methods and reach conclusions that are consistent with independent research.
A novel Empirical Bayes with Reversible Jump Markov Chain in User-Movie Recommendation system
Dey, Arabin Kumar, Jhamb, Himanshu
Dey et al. (2017), bayesian formulation of this problem is discussed. Hyper prameter choice was the major issue in that paper. However this problem was attempted only after suitable choice of feature dimension for user and movie feature vector. Usual method used to select such feature dimension is nothing but one dimensional grid search that select the dimension which minimizes the test error. This approach is boring as it attracts extra computational burden to select the feature dimension.
Google Assistant can play songs from Pandora Premium
Pandora's Plus and ad-supported users have been able to listen using Google Home for almost two years, and the streaming service is now meshing more tightly with Google Assistant. Starting today, Premium listeners can use their voice to play on-demand tunes and playlists on devices with the assistant baked in, including Google's smart speakers and third-party devices. Listeners can set Pandora as their default music streaming service on Google Home, so you won't need to add the "on Pandora" caveat when you want to play something. If you're not quite sure what a song's called but know some of the lyrics, you can ask Google Assistant to track down the tune for you -- that's a feature Spotify doesn't have. Using your voice, you can also give a song a thumbs up or thumbs down, repeat a track, skip tunes and create stations.
7 things Amazon Echo can do to help students
What parent wouldn't use anything at their disposal to help their kids succeed? We know that sitting down with our kids and helping them grasp the concepts they're learning at school is the best way to help them academically. And they probably don't need more time interacting with electronics, but Alexa offers some skills that can help students when parents aren't available. Luckily, if you have an Amazon Echo smart speaker, (in this case we recommend the Echo Dot for Kids) you have access to a wealth of brain-sharpening, knowledge-enhancing activities. To enable a skill on your Echo device, just say, "Alexa, enable [exact name of skill]."
Apple may be working on multi-user support for Siri
Today, Apple Insider reported that Apple had been granted a patent that would allow a voice recognition system to identify a user based on their speech and perform tasks based on who is speaking. This could be the framework for Apple to offer multi-user support with Siri. Right now, Siri will answer to whomever is speaking. This system would allow a user to set up profiles on their phone, and Siri could match the voice of whoever is speaking to the onboard profiles and customize responses. For example, a phone's primary user could restrict calendar or message access to protect information they'd like to keep private.
How to better secure your smart home
With the advent of gadgets like doorbell cameras, smart kitchen appliances and data-logging sensors that track your sleep, the smart home now extends to even the most intimate areas of the household. It's great for general convenience, like knowing whether you left the heater on or locked the door behind you, but these connected devices also bring with them a host of security concerns. We asked Wendy Nather, director of advisory CISOs at Duo Security, for a reality check on what the real vulnerabilities in a smart home are. "The most prevalent threat is automated attacks that are trying to take over devices as they would personal computers, to assemble into a group that can be used for their own purposes," she said. These threats often include denial-of-service attacks, cryptocurrency mining and stealing user passwords.
Ambient Weather WS-2902 Osprey Weather Station review: The best choice for smart-home buffs
Smart home enthusiasts take note: You can tie Ambient Weather's WS-2902 Osprey weather station into your smart home system, so your indoor lights won't wait until sunset to turn on when it's gray and dreary outside; your smart sprinkler will stop watering the lawn if it starts to rain; and you can ask Alexa or Google Assistant for a weather report from where you actually live, not from the closest National Weather Service (NWS) monitoring station. You'd think most home weather stations do these things, but they don't. Netatmo comes close, with hooks into Samsung SmartThings and IFTTT, but you'll spend more than $300 to build out a complete Netatmo system that can measure temperature, rainfall, and wind speed. The WS-2902 Osprey is built with connectivity top of mind. It's Wi-Fi capable and it works with IFTTT, so you can program weather events and conditions to trigger actions in your smart home.