background preloader

AI Experiments de Google

AI Experiments de Google

https://experiments.withgoogle.com/collection/ai

Related:  Intelligence artificielleVorpal ToolsIntelligence ArtificielleITGymnasiearbete

In simple words. With real-world examples. Yes, again This is Billy. Billy wants to buy a car. He tries to calculate how much he needs to save monthly for that. He went over dozens of ads on the internet and learned that new cars are around $20,000, used year-old ones are $19,000, 2-year old are $18,000 and so on. Billy, our brilliant analytic, starts seeing a pattern: so, the car price depends on its age and drops $1,000 every year, but won't get lower than $10,000.

The Infinite Drum Machine Built by Kyle McDonald, Manny Tan, Yotam Mann, and friends at Google Creative Lab. Thanks the The Philharmonia Orchestra, London for contributing some sounds to this project. The open-source code is available here. Check out more at A.I. sans titre About this course: Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it.

'Hi-tech robot' at Russia forum turns out to be man in suit A “hi-tech robot” shown on Russian state television has turned out to be a man in a suit. Russia-24 praised the ersatz android during coverage of a youth forum dedicated to robotics, boasting that “Robot Boris has already learned to dance and he’s not that bad”. But sharp-eyed bloggers were dubious. The Russian website TJournal listed questions about the robot’s performance: Where were Boris’s external sensors? Why did the robot make so many “unnecessary movements” while dancing? And why did the robot look like a person would fit perfectly inside of it?

Rules of Machine Learning:   Martin Zinkevich This document is intended to help those with a basic knowledge of machine learning get the benefit of Google's best practices in machine learning. It presents a style for machine learning, similar to the Google C++ Style Guide and other popular guides to practical programming. beepbox You can add or remove notes by clicking on the gray rows at the top. BeepBox automatically plays the notes out loud for you. Try it!

Developing a Toolkit for Prototyping Machine Learning-Empowered Products: The Design and Evaluation of ML-Rapid Developing a Toolkit for Prototyping Machine Learning-Empowered Products: The Design and Evaluation of ML-Rapid Lingyun Sun, Zhibin Zhou, Wenqi Wu, Yuyang Zhang, Rui Zhang, and Wei Xiang * Key Laboratory of Design Intelligence and Digital Creativity of Zhejiang Province, Hangzhou, ChinaState Key Lab of CAD&CG, Zhejiang University, Hangzhou, ChinaAlibaba-Zhejiang University Joint Institute of Frontier Technologies, Hangzhou, China Machine learning (ML) and design co-support the development of intelligent products, which makes ML an emerging technology that needs to be further understood in design practice.

Why Do Computers Use So Much Energy? Microsoft is currently running an interesting set of hardware experiments. The company is taking a souped-up shipping container stuffed full of computer servers and submerging it in the ocean. The most recent round is taking place near Scotland’s Orkney Islands, and involves a total of 864 standard Microsoft data-center servers. Many people have impugned the rationality of the company that put Seattle on the high-tech map, but seriously—why is Microsoft doing this? There are several reasons, but one of the most important is that it is far cheaper to keep computer servers cool when they’re on the seafloor. This cooling is not a trivial expense.

AI researchers want to study AI the same way social scientists study humans Much ink has been spilled on the black-box nature of AI systems—and how it makes us uncomfortable that we often can’t understand why they reach the decisions they do. As algorithms have come to mediate everything from our social and cultural to economic and political interactions, computer scientists have attempted to respond to rising demands for their explainability by developing technical methods to understand their behaviors. But a group of researchers from academia and industry are now arguing that we don’t need to penetrate these black boxes in order to understand, and thus control, their effect on our lives. After all, these are not the first inscrutable black boxes we’ve come across. “We've developed scientific methods to study black boxes for hundreds of years now, but these methods have primarily been applied to [living beings] up to this point,” says Nick Obradovich, an MIT Media Lab researcher and co-author of a new paper published last week in Nature.

A directory of direct links to delete your account from web services. Can't find what you're looking for? Help make justdelete.me better. easy No Info Available Login to your account, go to parameters, click Delete my account. AI and Creativity – O’Reilly The release of GPT-3 has reinvigorated a discussion of creativity and artificial intelligence. That’s a good discussion to have, primarily because it forces us to think carefully about what we mean when we use words like “creativity” and “art.” As I’ve argued in the past, each time we have this discussion, we end up raising the bar. Each time an AI system does something that looks “intelligent” or creative, we end up deciding that’s not what intelligence really is. And that’s a good thing.

The Spatial Web Will Map Our 3D World—And Change Everything In the Process The boundaries between digital and physical space are disappearing at a breakneck pace. What was once static and boring is becoming dynamic and magical. For all of human history, looking at the world through our eyes was the same experience for everyone. Beyond the bounds of an over-active imagination, what you see is the same as what I see. But all of this is about to change. Over the next two to five years, the world around us is about to light up with layer upon layer of rich, fun, meaningful, engaging, and dynamic data. New Website Generates Fake Photos of People Using AI Technology The above photos may look like your average portraits or photo ID pictures, but there’s much more than meets the eye. Using new advances in AI developed by researchers at NVIDIA, software engineer Phillip Wang created the website This Person Does Not Exist. That’s correct—none of the “people” pictured are real. Wang, who posted his work in the Artificial Intelligence & Deep Learning Facebook group, created the website to raise awareness about the technology. “Faces are most salient to our cognition, so I’ve decided to put that specific pre-trained model up,” Wang wrote. “Each time you refresh the site, the network will generate a new facial image from scratch from a 512-dimensional vector.”

Related: