There is no registration fee. However, the workshop venue has limited space, so pre-registration is mandatory for every attendant (whether presenting an abstract or not). When the maximum number of attendees will have been reached, additional registrations will be placed on a waiting list. Please let us know if you have registered and then decide not to attend. Additionally, non-US citizens will need to register at least 8 weeks before the workshop, i.e., by August 1st, 2018 at the latest, in order for badges to be processed in time for the workshop. NASA civil servant and contractor employees are also expected to register in the NASA Conference Tracking System (NCTS) to attend the workshop, even for non-cost, local attendance. Visit https://ncts.nasa.gov to complete this process. The NCTS number for the NASA Goddard Workshop on Artificial Intelligence is 34572-18.

The 51-year-old artificial intelligence and robotics scientist is responsible for co-developing Google Street View, pioneering self-driving cars, founding Google X – the internet giant's secretive research lab – and revolutionising education by kickstarting massive open online courses (Moocs). His most recent project is developing flying cars. You launched your flying car company, Kitty Hawk, in 2015 backed by Google co-founder Larry Page and you have two projects in development – a personal aircraft called Flyer and an autonomous air taxi called Cora. Why do we need flying cars? The ground is getting more and more congested – we are all stuck in traffic all the time.

Did you know that you can write R and Python code within your T-SQL statements? Machine Learning Services in SQL Server eliminates the need for data movement. Instead of transferring large and sensitive data over the network or losing accuracy with sample csv files, you can have your R/Python code execute within your database. Easily deploy your R/Python code with SQL stored procedures making them accessible in your ETL processes or to any application. You can install and run any of the latest open source R/Python packages to build Deep Learning and AI applications on large amounts of data in SQL Server.

Existing fuzzy neural networks (FNNs) are mostly developed under a shallow network configuration having lower generalization power than those of deep structures. This paper proposes a novel self-organizing deep fuzzy neural network, namely deep evolving fuzzy neural networks (DEVFNN). Fuzzy rules can be automatically extracted from data streams or removed if they play little role during their lifespan. The structure of the network can be deepened on demand by stacking additional layers using a drift detection method which not only detects the covariate drift, variations of input space, but also accurately identifies the real drift, dynamic changes of both feature space and target space. DEVFNN is developed under the stacked generalization principle via the feature augmentation concept where a recently developed algorithm, namely Generic Classifier (gClass), drives the hidden layer. It is equipped by an automatic feature selection method which controls activation and deactivation of input attributes to induce varying subsets of input features. A deep network simplification procedure is put forward using the concept of hidden layer merging to prevent uncontrollable growth of input space dimension due to the nature of feature augmentation approach in building a deep network structure. DEVFNN works in the sample-wise fashion and is compatible for data stream applications. The efficacy of DEVFNN has been thoroughly evaluated using six datasets with non-stationary properties under the prequential test-then-train protocol. It has been compared with four state-of the art data stream methods and its shallow counterpart where DEVFNN demonstrates improvement of classification accuracy.

Natural language processing (NLP) is an area of computer science and artificial intelligence that is concerned with the interaction between computers and humans in natural language. The ultimate goal of NLP is to enable computers to understand language as well as we do. It is the driving force behind things like virtual assistants, speech recognition, sentiment analysis, automatic text summarization, machine translation and much more. In this post, you will learn the basics of natural language processing, dive into some of its techniques and also learn how NLP benefited from the recent advances in Deep Learning. Natural Language Processing (NLP) is the intersection of Computer Science, Linguistics and Machine Learning that is concerned with the communication between computers and humans in natural language. NLP is all about enabling computers to understand and generate human language.

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For more than a century, the life of a vehicle has begun in the factory. To ensure a smooth transition to the automotive life cycle of the future, manufacturers must carefully design, build and run datacenters optimized for training artificial intelligence at scale. Autonomous vehicles rely on deep neural networks to handle functions that a human driver would typically be responsible for. These algorithms can perceive the world around the car, plan the vehicle's motion and actuate that path. Before they can safely run in the car, deep neural networks must be rigorously trained in the datacenter, where they are shown millions of hours of driving data, enabling an autonomous vehicle to recognize and react to scenarios on its own.

Learn to code and build apps! A wildly successful Kickstarter funded this course. Learn how to use TensorFlow 1.4.1 to build, train, and test machine learning models. A machine learning framework for everyone, If you want to build sophisticated and intelligent mobile apps or simply want to know more about how machine learning works in a mobile environment, this course is for you.

It's not very surprising that Google has come to dominate the more high-end aspects of cloud computing and data storage. The tech giant's suite of cloud computing services powers everything from its famed search algorithms to YouTube, and has become an increasingly important player in the worlds of machine learning and Artificial Intelligence (AI). If you're interested in beginning or advancing a career that's even remotely tied to any of these overarching industries, having an in-depth knowledge of how the Google Cloud Platform can be used alongside the latest innovations in tech is essential, and the Google Cloud Mastery Bundle will get you up to speed for just $39--90% off its usual price. Each of the four courses in this expert-led bundle introduces you to a different element of the Google Cloud and explains how this versatile service can be applied to a variety of in-demand AI and data analysis platforms. The Google DialogFlow For Chatbots course walks you through how to build intelligent voice-aware bots that lie at the heart of today's customer service and online support industry.

The new iPhone is coming. There are probably just days to go until Apple reveals the new handset. And just days after that it'll be ready and waiting, for those who've successfully clicked or queued their way into buying it. All of that makes it just about the worst possible time to buy an iPhone. They are all their usual price, and are just about to be overtaken by a whole host of brand new phones.