Full time engineering position on the design, development and testing of machine learning solutions on embedded platforms. Candidates should be familiar with different methodologies and techniques from statistics, data science, and machine learning. Candidates must have knowledge of neural networks. Required technical skills include systems design and development using C/C, Python, Java. Prior research experience and the ability to work independently and to communicate fluently are highly desired.

Industries everywhere are intrigued by the advent of artificial intelligence. While arguably still in its infancy stage, the potential of artificial intelligence is opening a whole universe of possibilities. Will it make for faster, cheaper operations? Will it replace human workers? As companies experiment with the capabilities of machine learning in their fields, ecommerce sites are already starting to feel some of the ripples of the something big.

About Austin: Austin is the CEO and co-founder of Yhat, Inc. He was previously at OnDeck Capital, the largest online small business lender in the United States. Alan Turing posed this question at the outset of his 1950 paper "Computing Machinery and Intelligence," a seminal piece of literature in the field of artificial intelligence. Turing wanted to know whether computers would eventually imitate humans' responses so well that people wouldn't be able to tell whether they were interacting with a human or a machine. Decades later, in an era when computers are capable of recognizing and responding to human speech, processing images and even driving cars, the question for data scientists and engineers has become "What else can machines think about?"

In today's so-called smart home, you can dim the lights, order more toothpaste or tell the kids to go to bed simply by talking to a small Wifi-connected speaker, such as Amazon's Echo or Google's Home. This voice-first market – combining voice with artificial intelligence (AI) – barely existed in 2014. This year, Voice Labs, a consultancy, expects 24.5 million appliances to be shipped. Other big tech firms have their own plans: Apple is taking its Siri voice assistant beyond its mobile devices to PCs, cars, and the home; Baidu last month bought Raven, billed as China's answer to Amazon's Alexa intelligent personal assistant; and Samsung Electronics plans to incorporate Viv, its newly acquired virtual assistant, into its phones and home appliances. But not everyone thinks the future of communicating with the Internet of Things needs to be vocal.

Today at SXSW in Austin, Texas, a panel of Disney executives talked about the expanding field of artificial intelligence and machine learning, along with other technologies. Jon Snoddy, of Disney's Imagineering group, mentioned the importance of new technologies serving the stories the company wanted to tell, and said that sometimes they scrap the use of technology entirely when it doesn't meet that goal. The panel also showed video clips from their R&D lab. One showed an animatronic "Pascal," inspired by the movie Tangled, which could be carried around and respond to input from people that touched it. Another video showed a completely autonomous droid that people would quickly learn to interact with.

The European Parliament is calling for EU-wide civil law rules addressing the fast-developing field of technology – robotics and artificial intelligence. Robots assisting in the field of medicine or the automotive industry is already an everyday reality, however the civil law rules need to be adapted in order to boost innovation and creativity, address issues of liability in the case of damages and set ethical standards. The European Parliament is the first parliament to debate robotics and artificial intelligence. The Parliament's Resolution initiates a timely debate on a wide range of issues related to robotics and AI including standardisation, safety and security, data protection, autonomous vehicles, care and medical robots, human repair and enhancement, drones, liability rules, ethical questions, but also considers education and employment. "European industry in the field of robotics and AI deserves a legal framework within which it can continue to grow. Innovations go beyond borders and are carried out by experts from several member states working together. This collaboration requires our support. The creation of EU-wide rules on robotics is a necessary step forward to allow the full exploitation of the economic potential of the sector, to promote growth and innovation, and to protect and create more jobs", said Therese Comodini Cachia MEP, Parliament's Rapporteur for robotics.

TensorFlow has become the most popular AI programming project on software code sharing service GitHub, leapfrogging well-regarded systems created by universities and corporate rivals, according to data gathered by Bloomberg. Deep Learning has had a huge impact on computer science, making it possible to explore new frontiers of research and to develop amazingly useful products that millions of people use every day. Our internal deep learning infrastructure DistBelief, developed in 2011, has allowed Googlers to build ever larger neural networks and scale training to thousands of cores in our datacenters. We've used it to demonstrate that concepts like "cat" can be learned from unlabeled YouTube images, to improve speech recognition in the Google app by 25%, and to build image search in Google Photos. DistBelief also trained the Inception model that won Imagenet's Large Scale Visual Recognition Challenge in 2014, and drove our experiments in automated image captioning as well as DeepDream.

Reflecting the rapidly increasing interest and investment in cloud computing, 10,000 developers, engineers, IT executives, and Google employees and partners gathered at Next '17, Google's annual cloud event for enterprise customers. Google showcased customer testimonials from Disney, Verizon, HSBC, Colgate-Palmolive, and Ebay; support from a number of new partners, including SAP; and a series of AI and cloud infrastructure-related announcements. Analysts were not impressed (see here and here, for example). Google, the argument goes, is a consumer company and does not understand or have ready access to enterprise customers. Amazon's first mover advantage has produced an insurmountable market lead (last year, it reported cloud revenues of $12.22 billion, compared to Microsoft's $2.42 billion and Google's $900 million, Deutsche Bank estimates).

This repository provides tutorial code for deep learning researchers to learn PyTorch. In the tutorial, most of the models were implemented with less than 30 lines of code. Before starting this tutorial, it is recommended to finish Official Pytorch Tutorial.

Artificial intelligence is progressing rapidly. Advancements in deep learning have propelled the idea of an AI-powered world from a faraway fantasy to a fast-approaching reality. AI, whether it be in the form of personal assistants on our smartphones or data miners who predict our spending habits, is becoming more deeply integrated with our everyday lives. What's more, we're starting to see artificial intelligence make its way into larger applications. Perhaps the most exciting applications are seen in nascent AI healthcare technologies.