This month we're chatting with Arte Merritt, CEO and Cofounder of Dashbot, a bot analytics platform that enables publishers and developers to increase engagement, acquisition, and monetization. When we refer to "bots," we mean any conversational interface, whether more text based--like Facebook or Slack--or voice based--like Alexa or Google Home. Originally they just provided scores of the games, but noticed users were asking about players, and added support for player info. They saw this in the analytics and added support for a "mute" functionality that enabled users to mute the score updates when their teams are losing -- and thus they retained the users instead of losing them.
Yet most of the streaming companies I talked to either missed the memo about Fling or aren't interested: I also reached out to NexPlayer, a company that sells video player tools to streaming services, and added Amazon Fling to its developer toolkit last year. With hands-free voice commands, users can launch videos on a nearby Chromecast from streaming services like Netflix, HBO Now, Hulu, and YouTube. While Amazon's Echo speaker does support voice commands on some TV devices, such as Dish Hopper DVRs, this is a different kind of integration that requires each device maker to develop its own Alexa skill, and right now no such controls exist for Fire TV devices. For instance, it will soon be able to show supplemental information on televisions in response to Google Home voice commands, and the audio version of Chromecast now enables whole-home audio across multiple Google Home speakers.
This was a crucial step as it allowed me to get comfortable with using a natural tone in my request and allowed me to understand how Edi would handle my calendar. I should also mention that Edi was built from a series of coordinated investments across Microsoft that brought together artificial intelligence (AI), conversational computing and calendaring. Because of AI and conversational computing, Edi will learn from my behaviors to be a better digital assistant and give a personalized experience. You simply add her to the "cc:" line of your email requesting she schedule a meeting and anyone on the "to:" will be scheduled.
In this article, we will briefly introduce model performance concepts, and then focus on the following parts of the machine learning process: data selection, preprocessing, feature selection, model selection, and model tradeoff considerations. Once you have a representative, unbiased, cleaned, and fully prepared dataset, typical next steps include feature selection and feature engineering of the training data. Basic techniques for feature selection, particularly for regression problems, involve estimates of model parameters (i.e., model coefficients) and their significance, and correlation estimates amongst features. Some advanced techniques used for feature selection are principle component analysis (PCA), singular value decomposition (SVD), and Linear Discriminant Analysis (LDA).
She was built by the startup Clara Labs, using a cross of AI and real people to handle scheduling for me. Instead, Clara Labs was gathering data to train its own machine to have one perfect conversation that might play out a million different ways: scheduling a meeting. While Nelson wouldn't commit to a percentage of responses handled by Clara, she says that people are only flagged in when Clara doesn't have a high certainty of offering a perfect response. "We want people to understand what it is to have a hybrid system, and many systems work like this.
Artificial Intelligence enables marketers to personalise and create more effective customer experiences, and improve ROI. The second, the Zeitgeist Tool, again using Visual Recognition APIs, analysed trends of colours and styles from Instagram images, to help predict colors, styles, necklines, cuts and fabrics. Building APIs to measure social sentiment analysis is possible using natural language and tone analysis to understand what content is relevant to your brand, what the sentiment is and helps you to make decisions on which posts to act on. How: Our wonderful partner Servian has created a compelling solution which, leverages tone analysis, social sentiment analysis – and more – to help your organisation profile the persona of the best possible fit for your organisation, and then find that person – leveraging their CV, social profiles, references and more.
As part of the update to Google Forms, one of the improvements included is intelligent response validation, and from time to time (whenever it's possible to do so) Google Forms will make a suggestion to users to validate a response that was issued by the person filling out a Google Form based on the questions that are asked by the form's creator. Also in the presence of saving time for users, Google Forms will now allow you to set up pre-configured preferences for future forms that you create so you don't have to choose certain elements each time you set up a new form, such as the option for always collecting email addresses or making questions required. Google has set limits on the file uploads, which starts at just 1GB, but there's also an option to increase the limit to 1TB if it's needed. So, when creating a new Form, if you want to provide the recipients with the ability to select multiple options for a single question, the Checkbox Grid would be the one to pick.
Increasingly sophisticated, with sensors enabling independence from on-the-ground operators, many of these flying robots are capable of acting on their own, autopilot systems avoiding collisions as well as detecting and reacting to threats. UAV systems are making commercial airliners' autopilots more sophisticated, while drone technology is being tested by Facebook to launch solar-powered UAVs to provide Internet access to remote areas. At the same time, almost every major automobile manufacturer is investing heavily in driverless technology, with initial data suggesting that autonomous automobiles are safer than human-controlled ones. This development could revolutionize almost every manufacturing industry – and combined with the rise of 3D printing and improved big data processing, new, improved models will be able to be designed, prototyped, tested and released to market far faster than previous research and development cycles.
Customers of ING Direct may soon be able to ask their "digital assistant" to check their bank balance, or tell a "chatbot" on Twitter to freeze a credit card that has gone missing. While many banks are active on social media, and other Australian banks are also working with chatbots, ING says its new wave of bots are different because they will be able to talk to customers in in everyday, jargon-free language. In response, the bots will be able to tell them their account balance, or arrange a simple transaction such as moving money between a customer's accounts. "It's important for us as a bank to be able to talk to our customers in normal, everyday language," Mr Paul said.
Imagine a recruiter can watch a video of your face and analyse your facial expressions. Face Recognition software is taking the world by storm. In Europe, a number of high-end hotels and retailers are reportedly using facial recognition to help identify VIPs and celebrities for preferred treatment when they enter the front door. Obviously, adding face recognition technology to this video platform could be of tremendous benefit to an employer.