computer


Artificial intelligence will enhance us, not replace us

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In his 1990 book The Age of Intelligent Machines, the American computer scientist and futurist Ray Kurzweil made an astonishing prediction. Working at the Massachusetts Institute of Technology (MIT) throughout the 1970s and 1980s and having seen firsthand the remarkable advances in artificial intelligence pioneered there by Marvin Minsky and others, he forecast that a computer would pass the Turing test – the test of a machine's ability to match or be indistinguishable from human intelligence – between 2020 and 2050. Kurzweil, now Google's head of artificial intelligence, or AI (an acronym with which we've all now become familiar), has subsequently refined his claim. He now says this event will happen by 2029. What's more, in 2045 we will witness what he calls "the singularity" – the point at which human and artificial intelligences merge, leading to exponential advances in technology and human capabilities.


Natural Language Processing: Crash Course Computer Science #36

@machinelearnbot

Today we're going to talk about how computers understand speech and speak themselves. As computers play an increasing role in our daily lives there has been an growing demand for voice user interfaces, but speech is also terribly complicated. Vocabularies are diverse, sentence structures can often dictate the meaning of certain words, and computers also have to deal with accents, mispronunciations, and many common linguistic faux pas. The field of Natural Language Processing, or NLP, attempts to solve these problems, with a number of techniques we'll discuss today. And even though our virtual assistants like Siri, Alexa, Google Home, Bixby, and Cortana have come a long way from the first speech processing and synthesis models, there is still much room for improvement.


'Untrained Eyes' explores how computers perceive you

Engadget

If you search for "man" on Google, most of the image results you'll get are of white males looking confidently at the camera. "Woman," meanwhile, brings up pictures of women that appear to have been taken from a male gaze -- and yes, you guessed it, they're also predominately white. That lack of inclusion in machine learning is what "Untrained Eyes," an interactive art installation, aims to shed light on. The project, created by conceptual artist Glenn Kaino and actor/activist Jesse Williams, comes in the form of a sculpture that uses five mirrors and a Kinect to get its point across. Stand in front of it, wave and, within seconds, you'll be presented with an image that will "match" your appearance.


Artificial Intelligence, Deep Learning and Machine Learning: A primer

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Frank Chen of a16z is highly regarded as one of the great creators of Silicon Valley. He is also one of the great teacher/mentors and this video on Artificial Intelligence proves that. Frank provides a fantastic overview of Artificial Intelligence (AI), including its history, its roots in human mythology and fiction, and its birthday! The term Artificial Intelligence, the birthday can be marked in the summer of 1956 when a group of researchers kicked off research at Dartmouth to research with the aim of creating an artificially intelligence being. This is the birth of the discipline.


Startup taps ARM computer vision for deep learning skills

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Dr Ilya Romanenko played a key role in R&D leadership for 12 years at image sensor designer Apical and after the company was acquired by ARM in 2016 he became R&D Director for ARM's computer vision team. He wants to combine Spectral Edge's proven Phusion image processing technology with a new approach based on Deep Learning for a new range of imaging technology for smartphones. "Spectral Edge is built on impressive fundamental technology, which sits at the intersection of the image processing and computer vision fields, meaning I can use my knowledge and expertise in both to move the company forward," said Romanenko. "It is already delivering significant benefits to companies in the broadcast market, and I am confident that working with the team we can bring this technology to life, particularly within products in the mobile sector, improving the user experience and bringing a new quality to existing products." His appointment follows that of new CEO Rhodri Thomas, who joined from SwiftKey/Microsoft in February 2017.


The Next User You Design For Won't Be A Human

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The centaur refers to the Greek myth of a half horse and half man. More recently, it has been used to describe human and artificial intelligence working together toward a common goal. This is the inevitable march of technology. Computers are faster and smarter than ever, and they will only improve, but they lack key cognitive skills like common sense and the ability to draw on a diverse set of experiences–things people do well. People and computers can be more effective working in tandem.


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It isn't just the tech entrepreneurs and Hollywood directors who dream about the role that artificial intelligence can play, or will play, in everyday human life--educators have begun to join them. However, those dreams aren't always pleasant and may, in fact, sometimes turn into nightmares. If computer systems are able to perform tasks that humans have performed for thousands of years, will it render teachers and administrators a thing of the past? Or is artificial intelligence the secret to freeing up educators' time for other, non-routine tasks, like mentoring and spending more one-on-one time with students? To find out, I went straight to the source--eight educators, including superintendents, coaches and teachers--to find out whether AI tickles their fancy or scares them straight.


Project Titan: Apple Scientists Disclose Research Paper On Autonomous Technology, 3D Detection

International Business Times

Computer scientists at Apple have released a research paper online on how autonomous cars can better detect cyclists and pedestrians while using fewer sensors, Reuters first spotted. The paper comes after Apple CEO Tim Cook clarified in June that the company was not building its own self-driving vehicle, but was instead focusing on an autonomous car system. It also follows a recent spotting of Apple's self-driving test Lexus SUV last month. Apple has been low-key about its autonomous technology plans, but the research paper finally shows how invested the company is in self-driving cars. The research paper, submitted last week to the journal arXiv, was written by Apple scientists Yin Zhou and Oncel Tuzel.


Introduction to Machine Learning : Part 1

@machinelearnbot

Working in the IT field for almost 20 years has afforded me the ability to focus on many different areas and to gain a wealth of experience in many generalities. I would say that I have never been a specialist in anything, other than perhaps network performance monitoring and managing large-scale enterprise software packages. This is not an extremely difficult task, in and of itself, so I have always been interested in gaining some new experience that I can specialize in. The new role I find myself in is engineering, but from a sales slant. That means that I spend more time cultivating relationships and less time on the keyboard, so I spend much of my personal time and most of my work time doing research and actively developing in an effort not to lose my edge.


Apple scientists disclose self-driving car research

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The paper by Yin Zhou and Oncel Tuzel, submitted on Nov. 17 to independent online journal arXiv, is significant because Apple's famed corporate secrecy around future products has been seen as a drawback among artificial intelligence and machine learning researchers. The scientists proposed a new software approach called "VoxelNet" for helping computers detect three-dimensional objects. Academics are used to freely sharing their work with peers at other organizations. Yielding to that dynamic, Apple in July established the Apple Machine Learning Journal for its researchers. Their work rarely appears outside the journal, which so far has not published any research on self-driving cars.