Creating machines to think for themselves may feel like the plot of a hardcore sci-fi novel. But in reality, it's what engineers and software developers are doing today to push the boundaries of technology. This limited-time offer bundles up high-level instruction on how to actual construct self-learning machines for 91 percent off from TNW Deals. TNW Conference is back for its 12th year. In over 14 hours of instruction, these four courses take you deep inside the artificial intelligence tech that underlies advanced Google web searches and even Tesla's self-driving cars.

Want to watch this again later? Report Need to report the video? Report Need to report the video? Need to report the video? This feature is not available right now.

An original quantum foundations concept of a deep learning computational Universe is introduced. The fundamental information of the Universe (or Triuniverse) is postulated to evolve about itself in a Red, Green and Blue (RGB) tricoloured stable self-mutuality in three information processing loops. The colour is a non-optical information label. The information processing loops form a feedback-reinforced deep learning macrocycle with trefoil knot topology. Fundamental information processing is driven by ψ -Epistemic Drive, the Natural appetite for information selected for advantageous knowledge.

Researchers have found that it is surprisingly trivial to trick a machine learning model (classifier, clusterer, regressor etc.) into making an objectively wrong decisions. This field of research is called Adversarial Machine Learning. It is not hyperbole to claim that any motivated attacker can bypass any machine learning system, given enough information and time. However, this issue is often overlooked when architects and engineers design and build machine learning systems. The consequences are worrying when these systems are put into use in critical scenarios, such as in the medical, transportation, financial, or security-related fields. Hence, when one is evaluating the efficacy of applications using machine learning, their malleability in an adversarial setting should be measured alongside the system's precision and recall. This tool was released at DEF CON 24 in Las Vegas, August 2016, during a talk titled Machine Duping 101: Pwning Deep Learning Systems.

The Faculty of Engineering and Information Technologies has attracted high-profile researcher, Professor Dacheng Tao, who will join the School of Information Technologies on 5 December. In 2015 and 2016 he was ranked by Thomson Reuters as a Highly Cited Researcher for Engineering and Computer Science. In 2015 he received the Australian Scopus -Eureka Prize, and in the same year obtained the ACS Gold Disruptor Award. His research predominantly covers artificial intelligence (AI), with a focus on computer vision, deep learning, and statistical learning, as well as their applications to robotics, neuroscience, medical informatics, and video surveillance. Professor Tao is excited to be joining the university as he believes "it has a history of achieving research excellence, passing frontier knowledge on to students, and for building the base to change lives for the better."

With technology governing almost every aspect of our lives, industry experts are defining these modern times as the "platinum age of innovation"; verging on the threshold of discoveries that could change human society irreversibly, for better or worse. At the forefront of this revolution is the field of artificial intelligence (AI), a technology that is more vibrant than ever due to the acceleration of technological progress in machine learning – the process of giving computers with the ability to learn without being explicitly programmed – as well as the realisation by big tech vendors of its potential. One major tech behemoth fuelling the fire of this fast-moving juggernaut is Intel, a company that has long invested in the science and engineering of making computers more intelligent. The Californian company held an "AI Day" in San Francisco showcasing its new strategy dedicated solely to AI, with the introduction of new AI-specific products, as well as investments for the development of specific AI-related tech. And Alphr was in town to hear all about it.

RESTON, Va.--(BUSINESS WIRE)--Software AG (Frankfurt TecDAX: SOW) today announced that it has acquired Zementis, Inc. with headquarters in San Diego, California. Zementis Inc. provides software for "Deep Learning", a key capability in machine learning and data science, and a fundamental technology driving "artificial intelligence" (AI) development. Software AG sees the current machine learning and AI advances as the basis for the next generation of Internet of Things applications such as self-driving cars, personal digital assistants, medical diagnosis, predictive maintenance and robotics. Software AG has already embedded Zementis' ADAPA (Adaptive Decision and Predictive Analytics) into its Digital Business Platform to offer enterprises comprehensive insights for real time business analytics. The combination of Software AG's real-time streaming analytics and ADAPA predictive analytics delivers precise business and technical insights into customer behavior, market dynamics, security risks and sensor information from the Internet of Things (IoT).

How The'Silly' Irish Founders At Intercom Built One Of Silicon Valley's Fastest-Growing Businesses At the AWS re:Invent event, Amazon has announced a host of new services that highlight its commitment to enterprises. Andy Jassy, CEO of AWS, emphasized on the innovation in the areas of artificial intelligence, analytics and hybrid cloud. Amazon has been using deep learning and artificial intelligence in its retail business for enhancing the customer experience. The company claims that it has thousands of engineers working on artificial intelligence to improve search and discovery, fulfillment and logistics, product recommendations, and inventory management. Amazon is now bringing the same expertise to the cloud to expose the APIs that developers can consume to build intelligent applications.

Want to watch this again later? Report Need to report the video? Report Need to report the video? Need to report the video? This feature is not available right now.