Lifeboat Foundation

Music for the game is ‘procedurally’ generated as players move through its universe.

Columbia Engineering Professor Changxi Zheng’s new approach could lead to better tagging and coding, leveraging 3D printing of complex geometries.

New York — July 18, 2016 — Columbia Engineering researchers, working with colleagues at Disney Research and MIT, have developed a new method to control sound waves, using a computational approach to inversely design acoustic filters that can fit within an arbitrary 3D shape while achieving target sound filtering properties. Led by Computer Science Professor Changxi Zheng, the team designed acoustic voxels, small, hollow, cube-shaped chambers through which sound enters and exits, as a modular system. Like Legos, the voxels can be connected to form an infinitely adjustable, complex structure. Because of their internal chambers, they can modify the acoustic filtering property of the structure—changing their number and size or how they connect alters the acoustic result.

“In the past, people have explored computational design of specific products, like a certain type of muffler or a particular shape of trumpet,” says Zheng, whose team is presenting their paper, “Acoustic Voxels: Computational Optimization of Modular Acoustic Filters,” at SIGGRAPH 2016 on July 27. “The general approach to manipulating sound waves has been to computationally design chamber shapes. Our algorithm enables new designs of noise mufflers, hearing aids, wind instruments, and more — we can now make them in any shape we want, even a 3D-printed toy hippopotamus that sounds like a trumpet.” VIDEO: http://www.cs.columbia.edu/cg/lego/

The warning from QuintessenceLabs’ CTO John Leisoboer is stark. “When sufficiently powerful quantum computers become generally available,” he says, “it’s guaranteed to break all existing cryptographic systems that we know of.”

In other words, he adds, “Everything that we’re doing today will be broken.”

It’s a sentiment echoed by Google’s Chrome security software engineer Matt Braithwaite who wrote in a blog post earlier this month that “a hypothetical, future quantum computer would be able to retrospectively decrypt any internet communication that was recorded today”.

Continue reading “Can we find a quantum-resistant algorithm before it’s too late?” »

A team has used simple quantum processors to run “quantum walk” algorithms, showing that even primitive quantum computers can outperform the classical variety in certain scenarios—and suggesting that the age of quantum computing may be closer than we imagined.

By now, most readers of Futurism are probably pretty well acquainted with the concept (and fantastic promise) of quantum computing.

Continue reading “Primitive Quantum Computers Are Already Outperforming Current Machines” »

This is one of those sites you’re going to want to try yourself. Take any black and white image, feed it to the algorithm, and watch as it spits out its best guess at a color version, which is often quite convincing.

Using a deep learning algorithm developed by Richard Zhang, Phillip Isola, and Alexei Efros of UC Berkeley, the process was trained on one million images. Though it currently fools humans only 20% of the time, that’s still a significantly higher rate than previous iterations and represents an exciting step forward, and further training should only increase that rate. Imagine a time when Photoshop can colorize a photo in one step, leaving the end-user to just tweak a few hues here and there. Such a capability would be huge for restoring old family photos and the like.

I played with it a bit today, and the results were rather interesting. It struggles a bit with skin tones, which may be due to dataset bias (meaning the team may have trained it more with landscape-style images), but often the results are fairly good and definitely close enough that they could be tweaked to believability without a lot of effort.

Continue reading “Deep Learning Algorithm Automatically Colorizes Photos” »

Transhuman Terminology.

ADHOCRACY
AEONOMICS
A-LIFE
AGORIC SYSTEM

AI-COMPLETE ALEPH ALGERNON AMORTALIST ARACHNIOGRAPHY ARCH-ANARCHY ARCOLOGY ARROW IMPOSSIBILITY THEOREM ARTILECT ASEX ASIMORT ASIMOV ASSEMBLER ATHANASIA ATHANOPHY ATHEOSIS AUGMENT AUTOEVOLUTIONIST AUTOMATED ENGINEERING AUTOMORPHISM AUTOPOTENT AUTOSCIENT BABY UNIVERSE BASEMENT UNIVERSE BEAN DIP CATASTROPHE BEANSTALK BEKENSTEIN BOUND BERSERKER BETELGEUSE-BRAIN BIG CRUNCH BINERATOR BIOCHAUVINISM BIOLOGICAL FUNDAMENTALISM BIONICS BIONOMICS BIOPHILIAC BIOSTASIS B-LIFE BLIGHT BLIND UPLOADING BLUE GOO BOGOSITY FILTER BORGANISM BREAKEVEN POINT BROADCATCHING BRUTE FORCE UPLOADING BUSH ROBOT CALCUTTA SYNDROME CALM TECHNOLOGY CALORIE RESTRICTION CASIMIR EFFECT CEREBROSTHESIS CHINESE ROOM CHRONONAUTS CHURCH-TURING THESIS COBOTS COMPUFORM COMPUTRONIUM CONCENTRATED INTELLIGENCE CONSILIENCE CONNECTIONISM CONTELLIGENCE CONTINUITY IDENTITY THEORY COSMYTHOLOGY CRYOBIOLOGY CRYOCRASTINATE CRYOGENICS CRYONICS CRYONIC SUSPENSION CRYPTO ANARCHY CRYPTOCOSMOLOGY CYBERCIDE CYBERFICTION CYBERGNOSTICISM CYBERIAN CYBERNATE/CYBERNIZE CYBERSPACE/CYBERMATRIX CYBRARIAN CYPHERPUNK DEANIMALIZE DEATH FORWARD DEATHISM DEEP ANARCHY DEFLESH DIGITAL PSEUDONYM DIAMONDOID DISASSEMBLER DISASTERBATION DISTRIBUTED INTELLIGENCE DIVERGENT TRACK HYPOTHESIS DIVERSITY IQ DIVIDUALS DOOMSDAY ARGUMENT DOWNLOAD DRYWARE DUBIFIER DYSON SPHERE ECOCALYPSE ECTOGENESIS

EMBRYOMEME
EMULATION
ENHANCED REALITY
ENVIROCAPITALISM
EPHEMERALISTS
E-PRIME
ESCALATORLOGY
THE ETERNAL LIFE POSTULATE
EUPSYCHIA
EUTHENICS
EVOLUTIONARILY STABLE STRATEGY (ESS)
EVOLUTURE
EXCONOMICS
EXES
EXFORMATION
EXISTENTIAL TECHNOLOGY
EXOPHOBIA
EXOSELF
EXTROPIAN
EXTROPIATE
EXTROPIC
EXTROPOLIS
EXTROPY
FACULTATIVE ANAGOROBE
FAR EDGE PARTY
THE FERMI PARADOX
FEMTOTECHNOLOGY
FLATLANDER
FLUIDENTITY
FOGLET
FORK
FREDKIN’S PARADOX
FUNCTIONAL SOUP
FUTIQUE
FUTURE SHOCK
GALAXY BRAIN
GAUSSIAN
GENEGENEERING
GENETIC ALGORITHM
GENIE
GREEN GOO
GÖDEL’S THEOREM
GOLDEN GOO
GREAT FILTER, THE
GREY GOO
GUY FAWKES SCENARIO
HALLUCINOMEMIC
HIVE COMPUTING
HOMORPH
HPLD
HYPERTEXT
HYPONEIRIA
HYPOTECH

Continue reading “Transhumanist Terminology” »

Researchers have developed a computer algorithm that doesn’t solve problems but instead creates them for the purpose of evaluating quantum computers.

The desire for quantum computers stems from their potential to solve certain hard problems faster than classical computers. But those bragging rights haven’t actually been earned yet, as no experiment has shown this presumed speedup. Researchers from the University of Southern California, Los Angeles, and the Complutense University of Madrid, Spain, have devised an algorithm that generates extra hard problems that could offer quantum computers the chance to prove their worth.

The problems that the team focused on belong to the general class of optimization problems. The main example is the Ising model, which describes the interaction of a large number of spins within a lattice. The goal is to find the ground state, which is the orientation of spins that minimizes the interaction energy. The problem is computationally hard because there are many local minima (pseudo-ground-states) that can fool a search algorithm.

Is search of the sound of silence.

To a physicist, perfect quiet is the ultimate noise. Silence your cellphone, still your thoughts, and muffle every kind of vibration, and you would still be left with quantum noise. It represents an indeterminacy deep within nature, bursts of static and inexplicable motions that cannot be gotten rid of, or made sense of. It seems devoid of meaning.

Considering how pervasive this noise is, you might presume that physicists would have a good explanation for it. But it remains one of the great unsolved problems in science. Quantum theory is silent not just on where the noise comes from, but on how exactly it enters the world. The theory’s defining equation, the Schrödinger equation, is completely deterministic. There is no noise in it at all. To explain why we observe quantum particles to be noisy, we need some additional principle.

Continue reading “The Noise at the Bottom of the Universe” »

The Defense Advanced Research Projects Agency has demonstrated a new mathematical framework that works to help researchers discover patterns in complex scientific and engineering systems. DARPA said Thursday researchers at Stanford University created algorithms designed to explore patterns in data in order to gain insights into network structure and function under the Simplifying Complexity in Scientific Discovery [ ].