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Commenting on Code, Considering Data's Bottleneck

Communications of the ACM

In computer science, you are taught to comment your code. When you learn a new language, you learn the syntax for a comment in that language. Although the compiler or interpreter ignores all comments in a program, comments are valuable. However, there is a recent viewpoint that commenting code is bad, and that you should avoid all comments in your programs. In the 2013 article No Comment: Why Commenting Code Is Still a Bad Idea, Peter Vogel continued this discussion.


ACM's 2018 General Election

Communications of the ACM

The ACM constitution provides that our Association hold a general election in the even-numbered years for the positions of President, Vice President, Secretary/Treasurer, and Members-at-Large. Biographical information and statements of the candidates appear on the following pages (candidates' names appear in random order). In addition to the election of ACM's officers--President, Vice President, Secretary/Treasurer--two Members-at-Large will be elected to serve on ACM Council. Please refer to the instructions posted at https://www.esc-vote.com/acm2018. To access the secure voting site, you will need to enter your email address (the email address associated with your ACM member record) and your unique PIN provided by Election Services Co. Should you wish to vote by paper ballot please contact Election Services Co. to request a paper copy of the ballot and follow the postal mail ballot procedures: [email protected] or 1-866-720-4357. Please return your ballot in the enclosed envelope, which must be signed by you on the outside in the space provided. The signed ballot envelope may be inserted into a separate envelope for mailing if you prefer this method. All ballots must be received by no later than 16:00 UTC on 24 May 2018. Validation by the Tellers Committee will take place at 14:00 UTC on 29 May 2018. Jack Davidson's research interests include compilers, computer architecture, system software, embedded systems, computer security, and computer science education. He is co-author of two introductory textbooks: C Program Design: An Introduction to Object-Oriented Programming and Java 5.0 Program Design: An Introduction to Programming and Object-oriented Design. Professionally, he has helped organize many conferences across several fields.


Top 16 Open Source Deep Learning Libraries and Platforms

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TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization. The system is designed to facilitate research in machine learning, and to make it quick and easy to transition from research prototype to production system. Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Center (BVLC) and community contributors.


Top 16 Open Source Deep Learning Libraries and Platforms

#artificialintelligence

TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization. The system is designed to facilitate research in machine learning, and to make it quick and easy to transition from research prototype to production system. Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Center (BVLC) and community contributors.


Appian gives low-code software developers new AI capabilities - SiliconANGLE

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"Low-code" software development platform provider Appian Corp. is branching out into the contact center with a new version of its product catering specifically to their needs. The company announced it's also updating its main offering, enabling users to add new artificial intelligence capabilities to the applications they build. The announcements were made during a keynote today by Appian Chief Executive Officer Matt Calkin (pictured) at the company's annual Appian World event in Miami. Having launched its initial public offering last year, Appian has become one of the leaders in the rapidly emerging field of low-code software development. The company's main product is a software-as-a-service offering tailored for everyday business users.


The Information Technology Dilemma

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The Fourth Industrial Revolution -- a global transitioning to a new set of systems and the integration of digital and physical technologies -- is upon us. Processing is rising exponentially, knowledge is becoming accessible to more people and information gathering is at an all-time high. Over the years, we've seen information technology have an increased role in the furtherance of humanity's cause for innovation and digital evolution. With new technologies such as artificial intelligence, the Internet of Things, energy storage and quantum computing, the future holds even greater potential for human development. The ubiquitous nature of information technology and its integration into virtually every facet of daily living has brought it within proximity of otherwise personal data.


Building AI systems that make fair decisions

MIT News

A growing body of research has demonstrated that algorithms and other types of software can be discriminatory, yet the vague nature of these tools makes it difficult to implement specific regulations. Determining the existing legal, ethical and philosophical implications of these powerful decision-making aides, while still obtaining answers and information, is a complex challenge. Harini Suresh, a PhD student at MITs Computer Science and Artificial Intelligence Laboratory (CSAIL), is investigating this multilayered puzzle: how to create fair and accurate machine learning algorithms that let users obtain the data they need. Suresh studies the societal implications of automated systems in MIT Professor John Guttag's Data-Driven Inference Group, which uses machine learning and computer vision to improve outcomes in medicine, finance, and sports. Here, she discusses her research motivations, how a food allergy led her to MIT, and teaching students about deep learning.


Spectral Monitoring for Drone Defense Applications

IEEE Spectrum Robotics Channel

Unmanned Aerial Vehicles (UAVs), commonly known as "drones," have been gaining popularity in recent years, not just as a cool new toy for hobbyists seeking a pastime, but also as an invaluable utility in industries such as defense and security. One particular application that has gained popularity in the last few years has been the use of drones as mobile spectral monitoring nodes, i.e. equipping the UAV with a mobile radio device to gather signal intelligence (SIGINT) and relay that info back to the home base for further analysis. The use of Software Defined Radio (SDR) technology would allow the drone to be mounted with one radio device that can be programmed to perform multiple functions such as spectral monitoring, transmitting a live video feed conducting electronic warfare (EW) attacks, etc. using the same device. Before SDR, spectral monitoring solutions were often bulky and consisted of complex hardware components with a fixed software interface. For drone-mounted applications, the solution needs to be small, lightweight, and able to be powered by a battery for an extended period of time.


The Most Talked About Technologies In 2018

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Technology is omnipresent, whether its medical or education, every department is controlled and developed with technology. Although, there have been major reforms and developments that have helped us make our lives more convenient in past few years, Artificial Intelligence and medical studies have seen some major changes in terms of technology. Apart from this, almost every sector has experienced a significant rise in the development of its own technology. However, if you talk about the most talked about and popular technologies, you might want to get your head around and analyze the data. Today, we're going to talk about the most popular technologies that have emerged in the year 2018 to make our life easier: Deep Learning is a method of teaching computers to do what comes naturally to humans.


Complete iOS 11 Machine Learning Masterclass

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If you want to learn how to start building professional, career-boosting mobile apps and use Machine Learning to take things to the next level, then this course is for you. The Complete iOS Machine Learning Masterclass is the only course that you need for machine learning on iOS. Machine Learning is a fast-growing field that is revolutionizing many industries with tech giants like Google and IBM taking the lead. In this course, you'll use the most cutting-edge iOS Machine Learning technology stacks to add a layer of intelligence and polish to your mobile apps. We're approaching a new era where only apps and games that are considered "smart" will survive.