Autonomous Cars: The Level 5 Fallacy – Monday Note


Today, I'll offer the pedestrian crossing at the intersection of Hayes and Octavia in San Francisco: Understandably, the Google Street View picture was taken in the early morning. Can an SD car acknowledge a pedestrian's nod, or negotiate "turning rights" with a conventional vehicle? The messy "30-year transition", the many uncertain steps in sensor and software engineering, the poorly understood problems of coexistence between conventional and SD cars leave much room for competitors large and small. To take our minds off iPhone leaks and too-predictable comments following the September 12th event, I offer an ancient (September 2012) Monday Note titled Apple Never Invented Anything.

Creepiest Stories in Artificial Intelligence Development


Now, these agents learned associatively: if they experienced pain around the time they saw a dog, they'd learn to associate the dog with pain. Microsoft launched the AI-powered bot, called Tay, in 2016. Actually, Tay was able to handle a variety of tasks, for example, joking with users, suggesting comments to the pictures you send her, telling stories, playing a game, and mirroring users' statements back to them. "Each team had designed a robot whose job it was to "herd" little robotic sheep into the robot's designated pen.



In exchange for $1.1 billion in cash, HTC will hand over 2,000 employees to the search giant. But for this to make sense, you need to remember that the company bundled the U11 with a voice assistant: Amazon's Alexa. So, Google bought Motorola and, with patent leverage on its side, hassled Samsung to row back on TouchWiz and generally fall back in love with Android. Samsung has launched its own smart assistant platform, Bixby, and has even added a hardware button to trigger it on its Galaxy S8 flagship.

Windows 10 digital ink: All the improvements with the Fall Creators Update


The improvements include two major elements: navigation, including using the pen or stylus to select and scroll text; and better interpretation of inked words as text, via a more accurate and responsive handwriting panel. Once it comes to writing actual words with your digital pen, though, Microsoft's new handwriting panel does an impressive job of interpreting inked words as editable text. Note that the keyboard icon won't appear on your taskbar unless you right-click the taskbar and select Show touch keyboard button from the menu that appears. Once you've enabled, and clicked, the touch keyboard button, you'll need to enable the pen input by selecting the pen keyboard.

Create Forecasting Models using Excel and Machine Learning.


Finally, with the increased importance of Data Science and Machine Learning and the increasing complexity of business data, Business Analysts have taken to more sophisticated methods to do forecasting. Thus, the importance of exploring how to incorporate more sophisticated forecasting models within Excel workflows. Azure Machine Learning (or Azure ML) is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions. While there are several ways of integrating ML workflows into Excel including the work of our partners such Anaconda, XLWings, Pyxll we'll focus on AzureML in this post.

9 AI terms to know


AI might apply an algorithm, or series of algorithms, to an artificial neural network to train itself for various tasks. Deep learning builds upon neural networks and machine learning techniques by applying deep networks with unsupervised learning. Because language is so complex, computers must carefully parse vocabulary, grammar and intent, while also allowing for variation in word choice when processing language, which is why programmers often take multiple AI approaches to NLP. Cognitive computing builds upon neural networks and deep learning to build a system that covers multiple disciplines, including machine learning, natural language processing, speech recognition and human-computer interaction.

5 overriding factors for the successful implementation of Artificial Intelligence


Even just five years back, Artificial Intelligence (AI) was still the stuff of science fiction, confined to research labs and tech giants' showcases. Processing power capacity, availability of representative data, development of more powerful algorithms, adaption of user interfaces, and, last but not least, a willingness to get the right policies in place. These single-chip processors were originally designed for video games but their capacity now to handle parallelization of multi-data processing means they're lending themselves to the use of complex AI algorithms and neural networks. This kind of complex machine learning though represents a big user challenge.

Graph technology the beating heart of new data management tools


In effect, Live Data Map acts as a knowledge graph and metadata repository, and can help automation of data discovery and preparation tasks. Informatica company leaders pointed to Live Data Map as one among several signs of the company's commitment to innovation. They indicated the company has worked to improve performance of the open source Titan graph database on which Live Data Map, originally discussed at last year's edition of the conference, was built. He suggested Live Data Map and other technology activity at Informatica World 2016 show a company still very much in the game.

AI processors go mobile


At its iPhone X event last week, Apple devoted a lot of time to the A11 processor's new neural engine that powers facial recognition and other features. The week before, at IFA in Berlin, Huawei announced its latest flagship processor, the Kirin 970, equipped with a Neural Processing Unit capable of processing images 20 times faster than the CPU alone. The company also has math libraries for neural networks including QSML (Qualcomm Snapdragon Math Library) and nnlib for Hexagon DSP developers. The closest thing that Qualcomm currently has to specialized hardware is the HvX modules added to the Hexagon DSP to accelerate 8-bit fixed operations for inferencing, but Brotman said that eventually mobile SoCs will need specialized processors with tightly-coupled memory and an efficient dataflow (fabric interconnects) for neural networks.

AI won't go anywhere unless it has empathy


This filtering ultimately helped Xiaoice avoid major ethical challenges. Algorithms created to realize AI were divided into algorithms exclusively authored by humans and algorithms authored by machines themselves. Initially, systems like black box AI were considered "neural networks" due to their similarity to the human brain. A notable example of black box AI used for good is Mount Sinai Hospital's Deep Patient project, which applied deep learning to medical records for over 700,000 patients.