Skip navigation

Michael Jordan

warning: Creating default object from empty value in /var/www/vhosts/ on line 33.


It was 1 in the morning. They were flummoxed by a safe. Jordan hadn’t opened it in years, and he couldn’t remember the combination. Everything else stopped as this consumed him. After 10 failed attempts, the safe would go into a security shutdown and need to be blown open. None of the usual numbers worked. Nine different combinations failed; they had one try left. Jordan focused. He decided it had to be a combination of his birthday, Feb. 17, and old basketball numbers. He typed in six digits: 9, 2, 1, 7, 4, 5. Click. The door swung open and he reached in, rediscovering his gold medal from the 1984 Olympics. It wasn’t really gold anymore. It looked tarnished, changed — a duller version of itself.

Your rating: None

Imagine any acoustic instrument able to act as a synth, and you begin to appreciate the potential instrumental pioneer Paul Vo may be about to unlock.

As we reported last month, music-technological innovation can absolutely involve guitars, not just synths with keyboards. So, it’s fitting that we tun now to a lover of keyboards and guitars alike, Chris Stack, for a look in video at the work of Paul Vo.

Vo may not be a household name in sound tech, but he should be, as the inventor of the impressive Moog Guitar. Here, we get look back at what came before — and what’s next.

Below, Chris gets his hands on a one-of-a-kind prototype that came before the Moog Guitar, in the form of a fretless model. You can see the fruits of the labors on Moog Guitar in the video at bottom, which demonstrates what a versatile electronic instrument this can be – as much a “synth with strings” as anything, beyond only what you might think of in guitar tone.

But having done fretless, electric, bass, and lap steel, Paul Vo’s tech now reaches a truly new frontier: the acoustic guitar and other stringed instruments. And that could be very big news. Watch, at top. It’s still early to fully grasp what this instrument may be like, but already there’s something really special going on:

The Vo-96 Acoustic Synth is the newest innovation from Paul Vo, the inventor of The Moog Guitar. It opens a new method of musical expression called Acoustic Synthesis. Will Rayan and Vincent Crow of The Electric Jazz Project try it out for the first time.

Code-named LEV-96, the concept instrument here uses harmonic content from strings as its source material. The inventor explains:

The numeral 96 refers to the number of individual harmonic control channels. Each channel is capable of controlling the behavior of one harmonic partial of a string’s timbre. 16 such channels are instantiated per string. 6 x 16=96

And if your mind isn’t blown yet, here’s more from Paul on how he’s thinking:

Add-on hardware, says Vo, will unlock the harmonic content of acoustic instruments in a way you haven't ever heard before. Photo courtesy Vo Inventions.

Add-on hardware, says Vo, will unlock the harmonic content of acoustic instruments in a way you haven’t ever heard before. Photo courtesy Vo Inventions.

With Acoustic Synthesis™ any acoustic musical instrument – any object that makes a sound – can be enhanced to bring out its hidden acoustic voice. Think also of potential new instruments – playable objects of acoustic art.
So far I’ve worked mostly with vibrating strings. The musical instrument string is arguably the most ubiquitous means of making music. It’s also the most difficult to vibrate coherently using electronic control. One idea I had back in 1979 turned out to be a great solution. I was amazed to find it was still unknown and patentable 20 years later.
Over the past 50 years or so we have accepted and become familiar with using synthesizers to create an endless variety of sounds electronically. I’m saying we are now beginning to extend this idea into the physical realm. We can make the virtual become real. We can artistically create new sounds by bringing out modes of vibration that have up to now remained hidden within the material objects we call musical instruments. Through Acoustic Synthesis™ the same sonic exploration is possible for other acoustic instruments and even creative objects of acoustic art that no one has imagined – not just yet anyway.
Analog Synthesis. Digital Synthesis. Acoustic Synthesis™: it isn’t empty hype, this really is a distinctly different and new method of voicing instruments, designing new sounds, and making music.

He covers this on his site:

Vo Inventions

Finally, a look back at the best-known Vo project, the Moog Guitar:

Chris’ site has been recently improved, so it’s well worth exploring all that he’s doing with creative instrument adventures and exploring sound design.

Your rating: None

Deep Learning of Representations

Google Tech Talk 11/13/2012 Presented by Yoshua Bengio ABSTRACT Yoshua Bengio will give an introduction to the area of Deep Learning, to which he has been one of the leading contributors. It is aimed at learning representations of data, at multiple levels of abstraction. Current machine learning algorithms are highly dependent on feature engineering (manual design of the representation fed as input to a learner), and it would be of high practical value to design algorithms that can do good feature learning. The ideal features are disentangling the unknown underlying factors that generated the data. It has been shown both through theoretical arguments and empirical studies that deep architectures can generalize better than too shallow ones. Since a 2006 breakthrough, a variety of learning algorithms have been proposed for deep learning and feature learning, mostly based on unsupervised learning of representations, often by stacking single-level learning algorithms. Several of these algorithms are based on probabilistic models but interesting challenges arise to handle the intractability of the likelihood itself, and alternatives to maximum likelihoods have been successfully explored, including criteria based on purely geometric intutions about manifolds and the concentration of probability mass that characterize many real-world learning tasks. Representation-learning algorithms are being applied to many tasks in computer vision, natural language processing, speech <b>...</b>

More in
Science & Technology

Your rating: None

I am not, as Ina Fried can attest, much of a sports fan. But I love this video from ESPN on a dude who lives his life disappointing those who are and who would dearly like to meet a superstar.

Personally, I want to meet the person with the same name as Lindsay Lohan.


Your rating: None

These are some old photos of the retired Chicago Bull’s basketball player Michael “Air” Jordan.


Air Jordan

Your rating: None