The CyberGuy shows you how to manage your online presence. The double-squeeze action is a feature that lets you quickly activate Siri, the voice assistant on your iPhone, by squeezing the sides of your device. A solution opens up a world to some amazing voice command tricks for better control of your iPhone. "Hello Cyberguy, I have an issue with Apple over their squeeze to confirm for purchase, etc. Many people do not have the ability to do the double-squeeze. Their hands are not capable for many reasons. I'm sure the elderly come to mind immediately, but it's also ones who suffer from carpel tunnel, arthritis and many others. It's personal to me as my daughter was at dinner with clients after an all-day business conference and choked without being aware on a piece of steak. Her heart stopped for over six minutes. The medics refused to give up, and she is now mind and body strong but having to fight to walk again and has lost much of the use of her hands. Gripping to confirm on the iPhone is one of the things she cannot do. She's extremely literate and intuitive with her workmates and would work well with someone. Here's how to make your iPhone more accessible. CLICK TO GET KURT'S FREE CYBERGUY NEWSLETTER WITH SECURITY ALERTS, QUICK TIPS, TECH REVIEWS, AND EASY HOW-TO'S TO MAKE YOU SMARTER Any suggestions you have would be greatly appreciated."

GPT-3 (short for "Generative Pre-trained Transformer 3) is a state-of-the-art large scale language processing AI model developed by OpenAI. It can generate human-like text based on various inputs, regardless of the complexity. This revolutionary technology can be used in a wide range of applications, such as content creation, advanced numerical analysis, text summarization, and code creation. As a result, it will benefit numerous industries around the globe. Before this innovation, individuals would extract information through search engines, like google, in the following manner.

This past weekend, data visualization, and specifically data visualization around depicting uncertainty, got a bit of national attention. As someone who designs with data and uncertainty, this was very exciting to me (not to mention it gave me a way to talk to my family about what I do!) On Wednesday President Trump spoke in front of reporters holding up a map of the approaching Hurricane Dorian. The reason this became a news items on its own is that the map had been altered from its original form. A map of the gulf coast that originally had a cone-shaped graphic mapping the potential path of the hurricane now had a new addition -- an extra bulbous bump. The new addition was immediately suspicious, and there are a couple of obvious reasons why.

The primary professional hat I wear is as a data science consultant working with machine learning in a variety of problem domains. Due to my academic past in computer science and applied statistics, my development environment of choice today is typically R. Lately however, Python is taking the lead position for working with deep learning workloads, so that's why I took special notice of this ODSC West 2018 talk "Deep Learning in R with Keras," presented by Gabriela de Queiroz, Senior Developer Advocate at IBM (Center for Open Source Data & AI). Gabriela is also Founder of the R-Ladies group. With Keras on top of R, I can get a little more mileage out of my R experience. For those of you still making the transition to deep learning, Keras is an open-source neural network library written in Python and capable of running on top of TensorFlow, Microsoft Cognitive Toolkit (CNTK), or Theano.

In this article: Build a chatbot using C# and Dialogflow I've explained how to setup intents in Dialogflow and so far we expected that the user is sending a message and the phrase/text passed has all what we need, but we didn't dive much into training intents or features which are a core functionality for building smart chatbots, let's explore more around intents in Dialogflow. The real world conversation is undetectable, it differs from one person to another and from one culture to another, even the same person will express his intent in a different way each time. Chatbot is not a human to be able to adapt quickly to that change in the conversation, hence we need to supply them with different possible scenarios under one intent, and that's exactly what Training Phrases is for. As the purpose is to have a chatbot being able to catch all the possible intents from the user either by creating additional intents or by training the existing intents with additional phrases. Thanks to NLP (Natural Language Processing) algorithms that analyzes and process natural/human language and allow us to extract intents from text.

We can bring analytics students into this to figure the best way to analyze the environmental data,

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Google Cloud announcements bring deep learning and big data analytics beyond data scientists, but enterprises will want more. If last week's Google Next 2018 event is any indication, Google Cloud is growing quickly. Registrations for the July 23-26 event topped 25,000, and actual attendance easily doubled the 10,000 at Google Next 2017. That's good, but if this public cloud is going to catch up with also-fast-growing rivals Amazon Web Services (AWS) and Microsoft Azure, Google is going to have to play to its strengths. From my perspective, Google's biggest appeals to big businesses are its deep learning (DL), machine learning (ML) and data platform capabilities (though I'm biased and my Constellation colleagues who follow G Suite and the rest of Google Cloud Platform (GCP) cloud infrastructure might see it otherwise).

Data science and machine learning are having profound impacts on business, and are rapidly becoming critical for differentiation and sometimes survival. Being able to quickly categorize the potential impacts into one of five categories, and communicate their potential, will help data and analytics leaders drive better results. Gartner research director Erick Brethenoux explains the five categories of impact and provides real-world examples taken from the worlds of government, sport and business. With their ability to frame complex business problems as machine learning or operations research problems, data scientists hold the key to unveiling better solutions to old problems. They may even reveal new problems and approaches that were previously unknown.