Google Uses Artificial Intelligence to Map Thousands of Bird Sounds Into an Interactive Visualization

If you were around in 2013, you may recall that we told you about Cornell's Archive of 150,000 Bird Calls and Animal Sounds, with Recordings Going Back to 1929. It's a splendid place for ornithologists and bird lovers to spend time. And, it turns out, the same also applies to computer programmers.

Late last year, Google launched an experiment where, drawing on Cornell's sound archive, they used machine learning (artificial intelligence that lets computers learn and do tasks on their own) to organize thousands of bird sounds into a map where similar sounds are placed closer together. And it resulted in this impressive interactive visualization. Check it out. Or head into Cornell's archive and do your own old-fashioned explorations.

Note: You can find free courses on machine learning and artificial intelligence in the Relateds below.

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Introduction to Python, Data Science & Computational Thinking: Free Online Courses from MIT

FYI: MIT has posted online the video lectures for an essential series of courses. In the playlist of 38 lectures above, you can get an Introduction to Computer Science and Programming in Python. Recorded this past fall, and taught by Prof. Eric Grimson, Prof. John Guttag, and Dr. Ana Bell, the course is "intended for students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class uses the Python 3.5 programming language." Find accompanying course materials, including syllabus, here.

The follow up course, Introduction to Computational Thinking and Data Science, is again intended for students with little or no programming experience. "It aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class uses the Python 3.5 programming language." Find related course materials here, and the 15 lectures on this playlist.

Both courses will be added to our collection of Free Computer Science Courses, a subset of our collection, 1,250 Free Online Courses from Top Universities.

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Artificial Intelligence: A Free Online Course from MIT

Today we're adding MIT's course on Artificial Intelligence to our ever-growing collection, 1,250 Free Online Courses from Top Universities. That's because, to paraphrase Amazon's Jeff Bezos, artificial intelligence (AI) is "not just in the first inning of a long baseball game, but at the stage where the very first batter comes up." Look around, and you will find AI everywhere--in self driving cars, Siri on your phone, online customer support, movie recommendations on Netflix, fraud detection for your credit cards, etc. To be sure, there's more to come.

Featuring 30 lectures, MIT's course "introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence." It includes interactive demonstrations designed to "help students gain intuition about how artificial intelligence methods work under a variety of circumstances." And, by the end of the course, students should be able "to develop intelligent systems by assembling solutions to concrete computational problems; understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering; and appreciate the role of problem solving, vision, and language in understanding human intelligence from a computational perspective."

Taught by Prof. Patrick Henry Winston, the lectures can all be viewed above. Or watch them on YouTube and iTunes. Related course materials (including a syllabus) can be found on this MIT website. The textbook, available on Amazon, was written by Professor Winston.

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36 eBooks on Computer Programming from O’Reilly Media: Free to Download and Read

This past week, we featured a free course on the programming language Python, presented by MIT. A handy resource, to be sure.

And then it struck us that you might want to complement that course with some of the 36 free ebooks on computer programming from O’Reilly Media--of which 7 are dedicated to Python itself. Other books focus on Java, C++, Swift, Software Architecture, and more. See the list of programming books here.

If you're looking for yet more free ebooks from O’Reilly Media, see the post in our archive: Download 243 Free eBooks on Design, Data, Software, Web Development & Business from O’Reilly Media.\

For more computer science resources, see our collections:

Free Online Computer Science Courses

Free Textbooks: Computer Science

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A Free Course on Machine Learning & Data Science from Caltech

Right now, Machine Learning and Data Science are two hot topics, the subject of many courses being offered at universities today. Above, you can watch a playlist of 18 lectures from a course called Learning From Data: A Machine Learning Course, taught by Caltech's Feynman Prize-winning professor Yaser Abu-Mostafa. The course is summarized as follows:

This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to adaptively improve their performance with experience accumulated from the observed data. ML has become one of the hottest fields of study today, taken up by undergraduate and graduate students from 15 different majors at Caltech. This course balances theory and practice, and covers the mathematical as well as the heuristic aspects. The lectures follow each other in a story-like fashion.

A real Caltech course (it's not watered down at all), the course assumes a familiarity with basic probability, matrices, and calculus.

The lectures can be found on YouTubeiTunes U and this Caltech website, which hosts slides and other course materials. The professor wrote the course textbook, also called Learning from Data.

Learning From Data will be permanently added to our list of Free Online Computer Science Courses, part of our ever-growing collection, 1,250 Free Online Courses from Top Universities.

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Neural Networks for Machine Learning: A Free Online Course

The 78-video playlist above comes from a course called Neural Networks for Machine Learning, taught by Geoffrey Hinton, a computer science professor at the University of Toronto. The videos were created for a larger course taught on Coursera, which gets re-offered on a fairly regularly basis.

Neural Networks for Machine Learning will teach you about "artificial neural networks and how they're being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion, etc." The courses emphasizes " both the basic algorithms and the practical tricks needed to get them to work well." It's geared for an intermediate level learner - comfortable with calculus and with experience programming Python. [Get a free course on Python here.]

You can find the video playlist on YouTube. It's also indexed in our collection of Free Computer Science courses, part of our meta collection, 1,250 Free Online Courses from Top Universities.

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If you'd like to support Open Culture and our mission, please consider making a donation to our site. It's hard to rely 100% on ads, and your contributions will help us provide the best free cultural and educational materials.

Are We Living Inside a Computer Simulation?: An Introduction to the Mind-Boggling “Simulation Argument”

The idea that we are living in a vast computer simulation as hyper-sophisticated simulated characters with limited self-awareness sounds like the kind of thing that issues forth from stoned philosophy majors in late night dorm room sessions. And no doubt it has, thousands of times over, especially after 1999, when The Matrix debuted and turned an amalgam of Plato, Descartes, Berkeley, and other metaphysicians into a then-cutting-edge sci-fi kung fu flick.

But is it a ridiculous idea? The obvious objection that first arises is: how could we possibly ever know? Computer simulated characters, after all, have no ability to step beyond the confines of the worlds designed for them by programmers, a limitation illustrated when one reaches a dead-end in a game and finds that, while there may be the image of a forest or a field, the game designers have seen no need to actually create the environment. Our character bumps up against the game's edge stupidly, until we toggle the controls and move it back into the prescribed field of play.


But (fire up your bongs), does the character know it’s reached a dead end? And if the universe is a simulation, who’s running the damned thing? And why? Welcome to “the simulation argument,” a theory endorsed by philosopher and futurologist Nick Bostrom, Tesla and Space X founder Elon Musk, and quite a few other non-dorm-dwelling thinkers. “Many people have imagined this scenario over the years,” writes Joshua Rothman at The New Yorker, “usually while high. But recently, a number of philosophers, futurists, science-fiction writers, and technologists—people who share a near-religious faith in technological progress—have come to believe that the simulation argument is not just plausible, but inescapable.”

Given their quasi-religious bent, are these technologists and futurists simply replacing a creator-god with a creator-coder to flatter themselves? Judge for yourself, firstly perhaps by listening to Musk explain the concept in brief at a Recode Conference above. (If you find yourself comforted by his answer, you may just be a game designer.) Then, for a more sprawling, pop-cultural dive into the simulation argument, spend an hour with The Simulation Hypothesis at the top of the post, a documentary that—depending on the laws of your current place of residence—may or may not be enhanced by an edible.

We might also reference Bostrom’s 2003 article---or watch him describe his position in the video below. Bostrom speculates that we might be living in an “ancestor simulation” run by an incredibly advanced civilization thousands of years in our future. Like Musk, writes Rothman, he concludes that “we are far more likely to be living inside a simulation right now than to be living outside of one.” The possibility raises all sorts of disturbing questions about the reality of choice, the moral meaning of our actions, and the nature of human identity. These are questions philosophers (and Philip K. Dick) have always asked, but until recently, they had little recourse to independent confirmation of their hypotheses. Now, as you'll discover in The Simulation Hypothesis, physicists have begun to discover that "our universe isn't an objective reality."

It is indeed perfectly plausible, given the exponential speed with which technology advances, that we will be able to run simulations with the same level of sophistication as our reality in a matter of a few generations or less… provided we don't destroy ourselves first or completely lose interest. Which answers the question of who might be running the program. As with the higher beings in Interstellar who reach back to give the dying human species a hand, “there is,” writes Rothman, “no sanctity or holiness in the simulation argument. The people outside the simulation aren’t gods," or even aliens, "they’re us.” Or some sufficiently evolved version, that is, whose technological achievements would likely seem to us like magic.

The Simulation Hypothesis will be added to our list of Free Documentaries, a subset of our collection, 1,150 Free Movies Online: Great Classics, Indies, Noir, Westerns, etc..

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Josh Jones is a writer and musician based in Durham, NC. Follow him at @jdmagness

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