WORLD’S LARGEST NATURAL SOUND LIBRARY NOW ONLINE

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The Macaulay Library, with over 150,000 recordings of 9,000 species is now digitised and has been uploaded to an online searchable database.

The library, housed at Cornell University’s Lab of Ornithology, has made available over ten terabytes of recordings, with a runtime of 7513 hours of natural sounds.

The collection, which began in 1929 has taken researchers dozens of years to accumulate. It currently holds recordings to a massive three-quarters of the world’s entire bird species, but it’s not all chirps and squawks, there’s also a decent helping of whale songs, insects, bears, elephants, primates and just about every other critter or creepy crawley that roams the earth.

The collection’s curator Greg Budney describes the archives as revolutionary, in terms of the speed and the breadth of material that is now accessible online.

“This is one of the greatest research and conservation resources at the Cornell Lab,” said Budney. “And through its digitization we’ve swung the doors open on it in a way that wasn’t possible 10 or 20 years ago.”

“Our audio collection is the largest and the oldest in the world,” explained Macaulay Library director Mike Webster. “Now, it’s also the most accessible. We’re working to improve search functions and create tools people can use to collect recordings and upload them directly to the archive. Our goal is to make the Macaulay Library as useful as possible for the broadest audience possible.”

Now the team has digitised its massive archive, it’s focusing on collecting new material from amateur and professional recordists from around the world.

The sounds are not only used by sound designers and filmmakers, but also by researchers, museums, or anyone interested in the sounds of nature.

“Plus, it’s just plain fun to listen to these sounds,” explained Bundy. “Have you heard the sound of a walrus underwater? It’s an amazing sound.” 

*UPDATE*

We had previously stated the library was free to use, but that seems not to be the case – rather, it’s ‘free to listen’. Licensing for commercial and non-commercial use is available, however it requires submitting an online purchase order, which may have fees associated with it (in other words, not free).

You can access the library now at macaulaylibrary.org.

Sound Recordists Chris Watson (image: lists/uk)

Check out some of the fun sounds found at the library:

• Earliest recording: Cornell Lab founder Arthur Allen was a pioneer in sound recording. On a spring day in 1929 he recorded this Song Sparrow sounding much as they do today.
• Best candidate to appear on a John Coltrane record: The indri, a lemur with a voice that is part moan, part jazz clarinet
• Most spines tingled: The incomparable voice of a Common Loon on an Adirondacks lake in 1992
• Most erratic construction project: the staccato hammering sounds of a walrus under water
• Most likely to be mistaken for aliens arriving: Birds-of-paradise make some amazing sounds – here’s the UFO-sound of a Curl-crested Manucode in New Guinea

ORIGINAL: Video and Film Maker

Here’s What Developers Are Doing with Google’s AI Brain

Researchers outside Google are testing the software that the company uses to add artificial intelligence to many of its products.

WHY IT MATTERS

Tech companies are racing to set the standard for machine learning, and to attract technical talent.

Jeff Dean speaks at a Google event in 2007. Credit: Photo by Niall Kennedy / CC BY-NC 2.0

An artificial intelligence engine that Google uses in many of its products, and that it made freely available last month, is now being used by others to perform some neat tricks, including 

• translating English into Chinese, 
• reading handwritten text, and 
• even generating original artwork.

The AI software, called Tensor Flow, provides a straightforward way for users to train computers to perform tasks by feeding them large amounts of data. The software incorporates various methods for efficiently building and training simulated “deep learning” neural networks across different computer hardware.

Deep learning is an extremely effective technique for training computers to recognize patterns in images or audio, enabling machines to perform with human-like competence useful tasks such as recognizing faces or objects in images. Recently, deep learning also has shown significant promise for parsing natural language, by enabling machines to respond to spoken or written queries in meaningful ways.

Speaking at the Neural Information Processing Society (NIPS) conference in Montreal this week, Jeff Dean, the computer scientist at Google who leads the Tensor Flow effort, said that the software is being used for a growing number of experimental projects outside the company.

These include software that generates captions for images and code that translates the documentation for Tensor Flow into Chinese. Another project uses Tensor Flow to generate artificial artwork. “It’s still pretty early,” Dean said after the talk. “People are trying to understand what it’s best at.”

Tensor Flow grew out of a project at Google, called Google Brain, aimed at applying various kinds of neural network machine learning to products and services across the company. The reach of Google Brain has grown dramatically in recent years. Dean said that the number of projects at Google that involve Google Brain has grown from a handful in early 2014 to more than 600 today.

Most recently, the Google Brain helped develop Smart Reply, a system that automatically recommends a quick response to messages in Gmail after it scans the text of an incoming message. The neural network technique used to develop Smart Reply was presented by Google researchers at the NIPS conference last year.

Dean expects deep learning and machine learning to have a similar impact on many other companies. “There is a vast array of ways in which machine learning is influencing lots of different products and industries,” he said. For example, the technique is being tested in many industries that try to make predictions from large amounts of data, ranging from retail to insurance.

Google was able to give away the code for Tensor Flow because the data it owns is a far more valuable asset for building a powerful AI engine. The company hopes that the open-source code will help it establish itself as a leader in machine learning and foster relationships with collaborators and future employees. Tensor Flow “gives us a common language to speak, in some sense,” Dean said. “We get benefits from having people we hire who have been using Tensor Flow. It’s not like it’s completely altruistic.”

A neural network consists of layers of virtual neurons that fire in a cascade in response to input. A network “learns” as the sensitivity of these neurons is tuned to match particular input and output, and having many layers makes it possible to recognize more abstract features, such as a face in a photograph.

Tensor Flow is now one of several open-source deep learning software libraries, and its performance currently lags behind some other libraries for certain tasks. However, it is designed to be easy to use, and it can easily be ported between different hardware. And Dean says his team is hard at work trying to improve its performance.

In the race to dominate machine learning and attract the best talent, however, other companies may release competing AI engines of their own.

ORIGINAL: Technology Review

By Will Knight

December 8, 2015

Thousands Of Darwin's Hand-Written Manuscripts Made Available Online

photo credit: AMNH

While we can never pick Charles Darwin’s brilliant brain, a collaborative project is bringing us closer to his thoughts than ever before. As of his week, to mark the 155th anniversary of the publication of his iconic book On the Origin of Species, the Darwin Manuscripts Project has made a treasure chest of Darwin’s hand-written notes available online, allowing people across the globe to trace the development of the man that changed the way we look at the world.

photo credit: AMNH

The project, which is a collaboration between the American Museum of Natural History (AMNH) and Cambridge University Library, was founded in 2003, and set out to digitize and transcribe a collection of Darwin’s writings. So far, more than 16,000 high resolution images of the naturalist’s notes, scientific writings and sketches have been made publicly available, but the project is only halfway through.

The documents hitherto released cover 25 years of Darwin’s life, “in which Darwin became convinced of evolution; discovered natural selection; developed explanations of adaptation, speciation, and a branching tree of life; and wrote the Origin,” according to the AMNH site.

You can even see a drawing by one of Darwin’s children, a scene of carrot and aubergine cavalry, which was sketched on the back of a page of the On the Origin of Species manuscript. You can also see his first use of “natural selection” as a scientific term, among many other things.

By June 2015, the archive will host more than 30,000 documents authored by Darwin between 1835 and 1882. The next release will cover the notes of his eight post-Origin books. The ultimate goal of the project, the AMNH explains, is to provide “access to the primary evidence for the birth and maturation of Darwin’s attempts to explore and explain the natural world.”

ORIGINAL: IFLScience

by Justine Alford

November 27, 2014