The Film: ABE (8m:22sec – Live Action/CGI Hybrid)
Writer/Director: Rob McLellan; England

The Film: R’ha (6m:26sec – CGI/Animation)
Writer/Director: Kaleb Lechowski; Germany

The Film: Changing Batteries (5m:33sec – CGI/Animation)
Creators: Shu Gi, Casandra Ng, Hon JiaHui and Bahareh Darvish; Malaysia

The Film: Modin (2m:50sec – CGI/Animation)
Creators: Lam Ho Tak & Ng Kai Chung Tommy; Hong Kong

Well that was fun, yeah? Again, if you can call b.s. on any of these, or if you’ve got something better, drop your knowledge in the comments below. Or, if you just wanna say “Hey dork, did you know about this one?” – that’s cool, too – even older ones would be welcome. They’ll be added to the ANTHROBOTICvideos YouTube Channel. If fact, yeah – that’s a challenge.

Also don’t forget to remember that if you wanna get the full scoop on WHY these robo-movies are 2013′s best so far, jump to Akihabara News: Top 4 Robot-Themed Short Films of 2013 (thus far), and there you’ll appreciate a milder version of the Technosnark©®™ found here. It’s still fairly smartastic, so Anthrobotic’s 7-8 regular readers will probably dig it.

[DIRECT FILM LINKS: ABE - R'ha - Changing Batteries - Modin]

This post originally appeared here: http://anthrobotic.com/2013/05/17/2013s-best-online-robot-movies-you-will-watch-them-right-now/

Zero-days exploits are considered a primary ingredient for a successful cyber attack, and the knowledge of zero-day flaw gives the attacker a near guarantee of success. As a result, state-sponsored hackers and cyber criminals consider zero-day exploits a precious resource around which booming market has grown.

Zero-day exploits could be used to as an essential component for the design of a cyber weapon or could be exploited for cyber espionage purposes, in both cases governments appear the most interested entities for the use of these attacks.

Recent cyber attacks conducted by Chinese hackers might lead one to think Chinese Government is primary buyer/developer for zero-day vulnerabilities, but a report recently published by Reuters claims the United States government is the “biggest buyer in a burgeoning gray market where hackers and security firms sell tools for breaking into computers.”

Reuters revealed that the U.S. Government, in particular its intelligence agencies and the DoD are “spending so heavily for information on holes in commercial computer systems, and on exploits taking advantage of them, that they are turning the world of security research on its head.”. It’s a new way to compete with adversaries in cyberspace.

The emerging zero-day market is fueled by intense activities of talented hackers who sell information on flaws in large use products. According Reuters defense contractors and intelligence agencies “spend at least tens of millions of dollars a year just on exploits”.

The zero-day market is very complex due to the high “perishability” of the goods and other factors.The following are some of the key factors in this complex business.

Difficulty finding buyers and sellers – It’s a closed market not openly accessible. Find a buyer or identify of a possible seller is a difficult phase of the transaction.

Checking the buyer reliability – The small number of reliable brokers able to locate a buyer pushes the security researcher to try to tell many individuals about a zero-day discovery in an attempt to find a “reliable” buyer, but this comes with obvious risks.

Value cannot be demonstrated without loss – One of the most fascinating problems a researcher attempting to sell vulnerability information or a zero-day exploit may face is proving the validity of the information without disclosing the information itself. The only way to prove the validity of the information is to either reveal it or demonstrate it in some fashion. Obviously, revealing the information before the sale is undesirable as it leaves the researcher exposed to losing the intellectual property without compensation.

Exclusivity of rights - The final hurdle involves the idea of the exclusive rights of the information. In order to receive the largest payoffs, the researcher must be willing to sell all rights to the information to the buyer. However, the buyer has no way to protect themselves from the researcher selling the information to numerous parties, or even disclosing the information publicly, after a sale.

The trend to exploit zero-day for offensive purposes has been followed by intelligence agencies and also private companies, both of which have started to develop their own zero-day exploits.

“Private companies have also sprung up that hire programmers to do the grunt work of identifying vulnerabilities and then writing exploit code. The starting rate for a zero-day is around $50,000, some buyers said, with the price depending on such factors as how widely installed the targeted software is and how long the zero-day is expected to remain exclusive.”

The Reuters report also reveals the participation of government representatives in the ISS World Americas conference, clearly with the intent to acquire new technologies to conduct cyber espionage.

The choice of a government to acquire a zero-day exploit to use against a foreign government, carries serious risks since cyber terrorists, cyber criminals or state-sponsored hackers could  reverse engineer the attack to compose new malicious agents to use against the attackers themselves.

The most popular example is the case of Duqu malware, a powerful spyware designed “to steal industrial-facility designs from Iran.”  which code was subsequently adopted by the cybercrime industry to be the  components in the popular Blackhole and Cool exploit kits.

In many cases the efficiency of these zero-day exploits has a long shelf  life due the presence of infrequently updated target systems, so a typical zero-day attack has an average duration of 312 days. Once publicly disclosed increases of 5 orders of magnitude in the volume of attacks are observed.

Reuters reports to have reviewed a product catalogue from one large contractor, it contained various applications for cyber espionage purposes. The article refers to a product “to turn any iPhone into a room-wide eavesdropping device” and another one “was a system for installing spyware on a printer or other device and moving that malware to a nearby computer via radio waves, even when the machines aren’t connected to anything.

The product portfolio is very impressive including tools for gaining access to computers and phones and tools for grabbing different categories of data. It’s clear that majority of these products use zero-day vulnerabilities on various application and OS software. And most of the programs cost more than $100,000.

Based from my experience the cost of a zero day exploit depends on a multitude of factors such as the product target, its diffusion level and of course the scope of use.  A zero-day sold to a government could have a price up to 100 times an exploit kit sold to private industry.

Which are the principal mediators for zero-day sale?

The Grugq is the famous one but also small firms like Vupen and Netragard and other defense contractors such as Northrop Grumman operate this growing market.

Netragard’s founder Adriel Desautels says he’s been in the exploit-selling game for a decade, and describes how the market has “exploded” in just the last year.  He says there are now “more buyers, deeper pockets,” that the time for a purchase has accelerated from months to weeks, and he’s being approached by sellers with around 12 to 14 zero-day exploits every month compared to just four to six a few years ago.

Ever since I sold my virtual reality software company to graphics software pioneer MetaTools, I’ve imagined a future photorealistic virtual reality capability based on real time ray tracing. Our technology at that time became part of the Bryce animation tool, providing real time hardware acceleration for previews. But with advances in GPUs, real time ray and path tracing (a related technique) are now a reality.  Here’s a video update on the state of the art.

See also: http://www.fxguide.com/featured/octane-render-realtime-ray-tracing/, http://www.codinghorror.com/blog/2008/03/real-time-raytracing.html and http://datunnel.blogspot.com/2009/12/history-of-realtime-raytracing-part-3.html

Intel Real-Time Ray Tracing Demo

Intel Core Demo

Intel Xeon Luxion Demo

Rigid Gems 2.0

Cube City

Trip inside a 3D fractal (Kleinian) GPU realtime rendering

Octane

John Carmack Interview: GPU Race, Intel Graphics, Ray Tracing and Voxels . More.

One of the more controversial LENR approaches has been Andrea Rossi’s E-Cat system,  a device said to work by infusing heated hydrogen into nickel, transmuting it into copper and producing heat in the process.   Tests of the E-Cat have generated various controversies in the past (e.g. related to the machine being covered up during testing), and the LENR community has been eager for independent third-party testing of the ysystem.

Such a third party test has now been reported, in a paper dryly titled “Indication of anomalous heat energy production in a reactor device containing hydrogen loaded nickel powder”.

In short, “the results obtained indicate that energy was produced in decidedly higher quantities than what may be gained from any conventional source.”

“Data were collected in two experimental runs lasting 96 and 116 hours, respectively,” with the first experiment demonstrating a COP (Coefficient of Performance) of almost 6, and a energy density estimated at five orders of magnitude greater than conventional energy sources.   This means an energy production (per liter) one order of magnitude higher than a conventional source.
More replications will be valuable of course, and it would be better to more thoroughly understand the underlying physics.  But this is a feather in the cap of Rossi’s E-Cat approach, and preliminarily promising for the LENR field and its practical applications.

If you’re curious for more: This Forbes blog post presents a few more details on the replication, and the comments at the end of that post elaborate some of the controversy regarding Rossi.

Two dozen leading experts in the brain recently converged for a daylong meeting at Stanford University. The meeting focused on a review of the current state of research and scientific knowledge related to software products and approaches that aim to defend against age-related cognitive decline. This meeting follows a similar meeting held five years ago which resulted in the 2008 Expert Consensus on Brain Health.

Sponsored by the Stanford Center on Longevity and the Max Planck Institute for Human Development in Berlin, the meeting convened amid “mounting concern” about  claims from commercial  “brain training” programs.

“We need to be cautious as scientists,” said Ulman Lindenberger, director of the Center for Lifespan Psychology at the Max Planck Institute. “When you look at the claims of these programs, they are really wildly exaggerated, because they make promises to you not only that you’ll get better on the task that you are training, but that you actually get a new brain so to speak, that cognitive abilities like your memory in general improve by playing these games. And these are claims that are not backed up by scientific evidence.”

It seems that generally most brain training software claims are dubious especially given the limited amount of time users actually employ the software. Similar recent and pessimistic results are also reported for effects of exercise on cognition. However, this does not mean there could not be other benefits of brain training and brain games in terms of overall health, mood and motivation.

Science is not magic, no matter what the movies might tell us. It operates under very real, and very palpable constraints.

One of these is money. You can’t just recite equations like they’re incantations, and pull change out of the ether. It takes time, and time costs money. Time to develop the discipline, and the integrity, time to put that discipline to use.

It is a radical shift in how to handle knowledge, and this radical nature is especially clear when you place it beside the ways in which people have historically handled knowledge.

Myths and legends, fairy tales and fables. Pretty stories that tie everything up in a neat little bow. The desire to build such stories and sustain them is a deeply human one, but one that any scientist who seeks to advance the frontier of human understanding must overcome.

And perhaps the most powerful constraint on all science is closely linked to humanity’s desire for simple little stories.

It is the assumptions that are inherited. The unknown unknowns. The assumptions that form the bedrock of our engagement with the world. As human beings, scientists are not immune.

One fascinating example of this is a set of seemingly very safe assumptions that underlie the scientific pursuit of artificial intelligence.

Computer processing speed has, in the course of a single human lifetime, increased to an incredible degree. Gordon E Moore, in 1965, coined a law where he stated that roughly every two years, computing power doubles. David House from Intel made the observation that actually, it was more like every 18 months.

And compared to the linear processing capacity of human beings, computing started faster. ENIAC, the world’s first general purpose computer, was launched in 1946. It was heralded by the press as the ìGiant Brain.î

But how did it stack up? How was it, in terms of processing speed, compared to a normal human brain?

Well, put it like this. ENIAC, in 1946, could do a 10- by 10-digit multiplication, flawlessly, at a rate of 357 of them per second.

And not only could it do that, it could do that all day, and would never get tired, and would never get confused, and would never, never, get a calculation wrong.

You can keep your “Rain Man”; nobody can do that.

It is a common staple of our speculation about the future of computing that one day computers will outclass human beings in terms of intelligence. But if, by intelligence, you mean linear processing capacity, that day has long since passed.

Today, the world’s fastest supercomputer is called Titan, and it hums away, doing its thing, in Oak Ridge National Laboratory, in Tennessee. It took the prize of the world’s fastest computer against very stiff competition in 2012 with an optimised performance of 17.59 petaFLOPS.

One petaFLOP is 10 to the power of 15 processes a second. That’s 10 with 15 zeros after it. That many calculations, every single second. And that’s one petaFLOP. Titan clocked 17.59.

Here’s my point. If, in 1946, ENIAC was doing better than any living human in terms of linear processing, and if Moore’s Law has broadly speaking played out, and it has, what is Titan compared to the linear processing power of a human?

Something well out the other side of massively better.

If we are looking to build artificial intelligence that is human-like, is this the way to go? Adding linear capacity (at an exponential rate, of course) to processing power?

Do we need we need more processing power to create a human-level of intelligence, when the speed and accuracy of calculation surpassed human capability 67 years ago?

There is an assumption embedded in our understanding of human intelligence, and it extends way back to the days of Newton. The Enlightenment period which began in Europe had a central belief right in the core. It was that reason, rationality, linear processing ñ this was the fundamental character of human intelligence.

And yes, we do other things ñ but that’s where the action is. That’s what makes us good at working things out. That’s what reason is, when you really get down to it. Make something that can do that, and whether or not it can feel emotion, it can think, because that’s what thinking is.

Or is it?

Because what we know now is that you can have a computer that can process so fast that it could probably outmatch the combined linear processing power of every human alive. But does it really think? Is it intelligent? Have we succeeded in our alchemy, and created intelligence from dead metal?

I would argue no. But then a very strange question arises. Why not?

Is it that we just need more power? More processing speed? If a linear processor can speed up even faster, if Moore’s Law keeps going for another decade, another century, surely at some point a machine will become self aware, and we will reach that singularity that Ray Kurzweil spoke of?

Except, what if linear processing is not the fundamental characteristic of human intelligence?

What if it’s something utterly different? Not just a different kind of processing, but if human intelligence is something utterly different in nature to anything we have so far considered?

And if it is, then perhaps a self-aware machine is closer than we think.

The neuroscientist Iain McGilchrist recently published a book called The Master And His Emissary. It won many plaudits, and is a strikingly new account of the actions of the human brain. It looks at the different ‘agendas’, so to speak, of the brain hemispheres, the two ‘sides’ of the brain.

To sum up an incredibly sophisticated argument in just a few sentences (forgive me, Dr McGilchrist, if I mangle it somewhat), the right hemisphere is concerned with charting reality using pattern recognition. It is not a linear processor, but far closer to the distributed systems used in the creation of neural nets.

This is, of course, to be expected, as neural nets were devised to mimic brain architecture.

But it doesn’t really do linear processing. What it does is massively distributed processing that is primarily concerned with charting patterns in reality, and representing them with as much fidelity as it can.

But then, of course, you have the left hemisphere, the ‘rational’ hemisphere that does the ‘categorisation’ stuff. Logic and structure is the domain of the left hemisphere.

Ok, so perhaps if we were to attach together a linear processor (left hemisphere) with a neural net (right hemisphere) we might be getting somewhere. And we might.

But for the fact that the left hemisphere isn’t honest.

It doesn’t work to create hi-fidelity output like the right hemisphere does. Instead, it does something very unexpected.

It seems to be working after the fact. That is to say, the rational processing it comes up with that seem to precede the decisions we make actually takes place after those decisions are made.

Very shortly after “a matter of microseconds” but after, and not before.

The left hemisphere doesn’t seem concerned with actually processing reality, or engaging with the real. What it seems primarily concerned with is rationalising the patterns recognised by the right hemisphere in terms of linear processes that are unconnected to the actual processes from which the ideas came.

Which is unutterably strange.

Why would it do this? Why bother? Why go to this effort? What’s the payoff?

Nothing that has passed through a process of evolution does something this radical for no reason. It’s not a mistake. It’s not malfunctioning. This is what it has evolved to do. Why?

There is one reason that occurs to me, and it is this.

What if the human brain is not in fact primarily concerned with processing reality, but is instead concerned with creating the illusion of so doing?

A jarring, jarring thing to think, especially if you start thinking what your thinking actually is in the light of this possibility.

Why would such an illusion evolve? What is its purpose?

Well, think about this. No matter how insecure we feel when our intelligence is compared to Titan, or even ENIAC, human intelligence has evolved well beyond any level needed by the evolutionary pressure to survive.

The ability to work out how to make a flint knife, or identify useful herbs could be understood as being a response to survival pressure. The ability to fly to the moon, less so.

But there is another element to evolution which might indeed make more sense of the minds we have, the brains we have, and the specific nature of them ñ the evolution of a courtship display.

The evolutionary psychologist Geoffrey Miller wrote a book called The Mating Mind along just these lines. His contention was that the massively amplified power of the human mind evolved in order to create greater and more elaborate courtship displays.

But what if it’s simpler than that? What if the mind itself actually is a courtship display?

A rational structure projected by the left hemisphere to be filled in by the right hemisphere with quality and emotion, in order to create the most compelling mating display in all of evolution?

The human self.

Ridiculous, of course. We’re all rational, aren’t we?

Aren’t we?

This is a very radical reorienting of what human intelligence fundamentally is, and leads to a conclusion so strange that it seems genuinely beyond reason.

What if the human mind is itself artificial intelligence?

If the rationality of the mind is a fiction, a fiction that is the bones and structure of the illusion, fleshed out with moral colour, emotional depth, and quality?

What then for AI?

It might be closer than we think. If this is true, we’ve been looking at it all wrong. Instead of strapping a linear processor to a neural net, why not do something different?

Strap two neural nets together. One of them exists to chart reality as best it can, with a number of sensors feeding raw data into it. One of them, the master one, exists not to recognise patterns, but to project them. To project a very specific kind of pattern. The illusion of rationality.

To project it, and also, to use the contours mapped by the hi-fidelity neural net to fill that illusion, to flesh it out. And the master net would choose to use or discard these patterns along a very specific set of parameters ñ not the most accurate, but the most effective at bolstering the illusion of a self that is coherent, rational and aware.

Strap that together, and you might have something massively more human than anything of which Oak Ridge Laboratory can boast.

Forget artificial intelligence. Try artificial humanity.

This involves an extremely radical reorienting of our understanding of humanity itself. But that doesn’t mean the jarring account isn’t true. Reality does not care to conform to our expectations of it. It does what it wants to do, and the only choice we have is to be open to that, or closed to that.

If we are open to this new way of looking at human intelligence ñ and it is a very strange new way, granted ñ then the building of an AI architecture along these lines could well demonstrate whether this is, or is not, what is going on with people.

It is a profoundly testable theory, no matter how jarring or strange it is. And we have the technology, right now, to create a system that would test it.

To create a self-aware computer by actually giving it a self of which it can become aware.

Maybe it won’t work, maybe it will. But one thing is certain.

I’d be loathe to plug it in to the defence systems of the United States of America.

We know how that would end.

We’ve all seen Terminator.

In his article – - Welcome, Robot Overlords. Please Don’t Fire Us? – Drum put forward the case that as humans we are increasingly forced to compete against machines designed to perform better and smarter than us. The idea that machines may one day take over is not new but the article argues that this trend has already started and it is merely the blindness of statisticians and economists that has prevented it from being seriously discussed so far.

The economics community just hasn’t spent much time over the past couple of decades focusing on the effect that machine intelligence is likely to have on the labor market. Now is a particularly appropriate time to think about this question, because it was two centuries ago this year that 64 men were brought to trial in York, England. Their crime? They were skilled weavers who fought back against the rising tide of power looms they feared would put them out of work.

The crux of the article is that the trend for human unemployment has already started and that while we may discuss issues such as job training or access to opportunities we are ultimately on a one way path that can only lead to less and less jobs for humans.

There was general consensus that the rise of AI capable of doing human jobs was inevitable but the solutions were varied. In his article for Forbes – Inequality In The Robot Future – Karl Smith, writes that no matter what sophisticated machines are developed there remains hope in the form of legal frameworks that recognize humans as fundamentally different from intelligent machines.

Birth is something that happens to a minority of beings who are special, flesh and blood humans.

An article in The Atlantic by Noah Smith – The End of Labor: How to Protect Workers From the Rise of Robots –  pointed to the potential for inequality between the largely unemployed masses with little hope of earning money and the owners of the machines who would have a virtual license to print money. He suggests a solution that would endow all humans with rights to the robotic means of production.

What if, when each citizen turns 18, the government bought him or her a diversified portfolio of equity? 

An article on the topic published in The Economist – In the long run, we are telepathic androids –echoed many of these concerns and suggested that the solution to the problem lay with clear delineation of intelligence in a distributed system. While the article predicted that there was scope for humans to survive financially the question was raised as to what exactly separates a human from a machine in a world where brains and servers are super-connected.

Lochlan Bloom lives in London and does not have a cat or a dog. He is a writer of fiction and non-fiction and has completed recent projects for BBC Radio Scotland, H+ Magazine , Ironbox Films and Calliope, the official publication of the Writers’ Special Interest Group (SIG) of American Mensa, amongst others.

The BBC Writersroom describe his writing as ‘unsettling and compelling… vivid, taut and grimly effective work’. He currently has a feature length script in production with Porcelain Film. His novella, Trade, is out now.

For more details visit www.lochlanbloom.com.

According to Techcrunch today, Google’s Larry Page estimates we’ve done a mere 1% of what is possible with our existing technologies and knowledge. I have to agree.

“… We’re at maybe 1% of what is possible. Despite the faster change, we’re still moving slow relative to the opportunities we have. I think a lot of that is because of the negativity…”

Further, Larry says he wants to create an experimental techno-futurist playground, a sort of “Burning Man” for testing tech. He envisions a temporary autonomous zone or zones  specifically to allow developers and technologists to explore the social and human impacts of novel technologies and products before they are ready for mainstream markets.

“We don’t want our world to change too fast. But maybe we could set apart a piece of the world .. I like going to Burning Man, for example. An environment where people can try new things. I think as technologists we should have some safe places where we can try out new things and figure out the effect on society. What’s the effect on people, without having to deploy it to the whole world.”

All we at H+ can say is….BRING IT ON!

See Larry Page Wants Earth to Have a Mad Scientist Land