Before September 15th 2009 one of the following two events will occur:

1. Apple releases initial support to iPhone augmented reality applications.
2. Apple announces an extension to the the iPhone SDK, specifically intended for augmented reality app development.

[Posted on Jul 13, 2009]

Only eleven days after the prediction news began rushing in; among many others reporting, MacRumors said on July 24th 2009:

The L.A. Times reports that Apple will begin allowing developers access to the tools they need to produce augmented reality applications starting with upcoming iPhone OS 3.1. [So far, AR applications] have used unpublished APIs which prevent them from being allowed on the App Store. Apple, however, told one developer that the tools necessary would become available with iPhone 3.1. [MacRumors]

In short, Apple is releasing their initial support to augmented reality applications. The Los Angeles Times posted the article that broke news that Apple told developers of the Nearest Tube AR train finder (Acrossair) that augmented reality apps will be allowed in the iPhone App Store in September, as predicted… let’s see if it turns out to be September 15th

Stay tuned for more predictions.

Automatic recommendations:

1. Augmented reality on iPhone delayed, but hardly prevented
2. Augmented reality app running on iPhone

[NOTE: Above is a snapshot for July '08 to July '09;
See current 12 month trend]

Officially, Apple’s iPhone SDK does not offer access to any APIs for manipulating live video, forcing developers to use the available but unsupported ones instead. That’s a shame because as you can see, there are a lot of unique concepts out there for implementing Augmented Reality on the iPhone. [...] However, there’s still hope. According to some hearsay out there, Apple is interested in enabling these types of apps. [ReadWriteWeb]

There’s no question that Apple realizes the potential of AR and their position to dominate the market. The iPhone’s media attention and hardware power can make for a Walt Disney of augmented reality.

Having correctly predicted the type- and date of debut of the first mainstream AR application, the oracle speaks again—let’s see if I get this one right:

EDIT (August 13th 2009): This prediction was correct. Only 11 days after I posted this prediction it was announced that Apple’s iPhone OS 3.1 will support augmented reality applications—expected release is in September (as predicted). See further details in Correctly predicted: Augmented reality support in iPhone OS 3.1

Will augmented reality on the iPhone accelerate development of wearable displays?

The iPhone did the impossible and brought back head-mounted displays (HMDs)—often known as virtual reality goggles. Many modern HMDs are now relatively cheap—the pricetag is no longer long enough to use as a belt—and, on occasion, the design is sleek. (They still suck, but keep improving.)

Using phones’ screens for augmented reality applications is literally like peeking through a keyhole. Demand for alternate interfaces increases as a result of mainstream AR, and the greatest of these are wearable displays; AR specs (see-through displays, shaped like glasses). These have been around for decades (image shows MIRAGE – undergrad student project from 2002) but are still expensive as hell. Will the iPhone do for AR specs what it did for HMDs?

Importance of AR+wearable display interplay

The combination of wearable displays and augmented reality has countless uses. It’s important, in fact, with potential to revolutionize machine interfaces and manufacturing practices. Picture the following, for example: Desktop computer output (screen) can be overlaid onto reality like any other AR graphic, displayed in 3D as if they are sitting on a desktop.

Instead of buying two screens for a dual-screen setup at home, a student on a tight budget could buy AR specs. Through these he can display as many virtual computer screens as needed. If quality were to improve and price decrease, AR specs could serve as flexible, space saving, easy to transport and cheap alternative to any modern hardware display.

Augmented reality is not a type- or collection of applications. It’s a type of medium. In today’s economy, requiring cost reductions and preservation of resources, a future where a single gadget can replace several seems ever more likely. The boom of augmented reality is more probable than ever.

Automatic recommendations:

1. Augmented reality app running on iPhone
2. Augmented reality games, but what’s reality doing there?

Not only do we lack understanding of our own creative mechanisms, but the basics of computer programs seem to oppose the idea of achieving unbound originality. Here’s a look at that important, fundamental problem when implementing creativity. In easy digest format, no less.

A Brief Introduction to Creativity

Crucial to what follows is pointing out that creativity is ill-defined and people generally have very different ideas of what it is. This can make it difficult to discuss and debate.

Art is typically strongly tied to creativity, and many scientists are focusing on this. The painting on the side was created by the computer program Aaron, which is one of the more famous creative systems. But while creativity exhibits itself very strongly amongst artists and is easily associated with them, that’s nowhere near the whole story. For example, there’s software like Thaler’s neural networks that have invented new, patentable physical materials. This is another type of creative expression.

And to go even further; in Emergence of Creativity, my chapter in the book Intelligent Complex Adaptive Systems, I explain and define creativity and its origins in a way that accounts for even the actions of primitive organisms — not only human abilities.

But for this article’s purposes, all we have to agree on is that creating something new or being original is an essential part of creativity. Given this agreement, we shouldn’t run into a problem with the following explanations. But even so, keep in mind how extremely multifaceted creativity is and that I’m simplifying the concept (to keep this article from becoming a book).

A problem when creating creative systems

To properly explain the problem, how programming seems to oppose creativity, we must understand what computer programs are: instructions. A set of steps the computer executes. Typically, when we create computer programs we specify a certain problem and in turn devise a set of instructions that addresses this problem.

A program that can add numbers is a very simple example of this: we specify that its input are numbers and operators, how it should apply the operators to the numbers and that the output should be the result of the computation. Note here that before we create a program we need to know what we want it to do and what instructions achieve that purpose.

Computer programs are instructions, even when they become more complex.

An example of a creative system

Consider an intelligent agent model. An agent is a system that perceives its environment (input) and acts upon that environment (output), and broadly speaking, an agent’s input can be anything from keystrokes to streaming video (or a combination).

Our agent is a writer, to stay within a creativity setting most are comfortable with (here’s to hoping you think people like Shakespeare are creative). For this particular case, the input is a human’s demanding to hear a story about a particular subject, like a story about detectives or robots. Our agent composes a story, puts it in a file and then acts upon the environment by displaying it on-screen.

But in order to make our agent write something other than gibberish, he must have a dictionary of words and he must know grammar. He must also have common sense to know how the world works or otherwise we’d be getting stories where a bucket drinks from a detective.

In the real world we would have to take our agent’s architecture quite a bit deeper. We would have had to give him some way of choosing plots, paragraphs and words, for example. But we’re going to look past that and just focus on what we already have at this point.

Instructions are limitations

Note now that when we gave our agent a dictionary, a goal, grammar knowledge and common sense, we effectively restricted him: He’s not a painter. He’s not a musical composer. He’s not a programmer, a witch, a lion or a wardrobe. And when we look at it as a creative writer, we begin to see he’s not that creative at all.

A goal limits the objectives of a system and thereby helps us organize how the system will behave¹: Our agents should write a story — he’s not about to write a groundbreaking paper about artificial creativity. And what about his stories? He has common sense that dictates no man can fly without the help of machines. We killed our creative agent’s Superman right there.

But these restrictions were also necessary for him to do anything at all. To explain this with a familiar analogy, it’s like writing a cooking recipe: To bake a cake we need certain ingredients. When we bake it the ingredients define what kind of cake it becomes. But we’re baking a cake, not bread. And the cake is sweet, not sour. The ingredients are restricted to define a particular outcome of the baking. Similarly, the instructions we devise are what defines a programs behavior and outcome.

Basically, to make it do what we want it to, we impose restrictions — a confined set of rules out of all the possible rules in the world.

What kind of instructions make limitless systems if instructions themselves are limitations?

Now here’s the core of the problem, finally: We agreed in the beginning of this article that an essential part of creativity is originality and creating something new. But like we’ve discussed above we know beforehand how a program should behave before we make it, including what it should produce.

The basics of programming require us to explicitly design mechanisms that produce certain outcomes. By giving these explicit instructions we inadvertently decrease the potential of the program surprising us since clearly it means that we know beforehand how it will behave.

The instructions that define our program (and make it work) are in turn the exact reason it can’t produce surprising, novel and interesting ideas.

But how about a self-organizing program that writes its own code on the fly to overcome its restrictions? Yes, that sounds appealing and is what many scientists working on artificial creativity are trying to do, in one form or the other. And it would be really easy too… if the program wouldn’t have to be creative to write new code!

Edit (Aug. 25th): Due to some comments from readers (thank you) I feel inclined to emphasize what I mentioned in the article: many creative systems have already been made (have a look through the creativity category).

I’ve personally created and worked on systems that present creative behavior. Making them more robust is just a question of time, research and development. The example used here is intentionally simple and raw to flesh out an essential problem that scientists face when developing creative systems—but this is a problem we are overcoming.

Links and References

• Aaron painting retrieved from Wikipedia
• ¹ Stuart Russell and Peter Norvig (2002). Artificial Intelligence: A Modern Approach (2nd edition). Prentice Hall. 60.

Automatic recommendations:

1. Absolut Adopts Machines & Artificial Creativity
2. The 5th International Workshop on Computational Creativity

To answer this bluntly: Game AI is very different from it’s non-game counterpart, and it’s not my field of study. I’ve only compared modern games through a window. However, Alex of AIGameDev has superb coverage of AI in games and the top AI games of 2007, by community vote. The top of the line are Half-Life-2.ep.2 and BioShock.

But regarding Game AI in general: modern games are horribly void of intelligence. It depends on where you set the bar, certainly. There’s tons of AI in modern games compared to 5 years ago. But the first thing to note is that Game AI is not the same as AI. It’s a subset of it. Just like discrete mathematics are a subset of mathematics. And moreover, Game AI is a very specialized subset—it has well defined goals, models for construction and limitations.

Games are governed by laws of commerce first, then innovation.

A game is governed by different laws than academic, general AI R&D. It’s a commercial product, and commercial products depend on older methods wherever possible—methods that have proven successful. Most (sane) business men do not put all their money on a new and untried idea because they don’t know if it will succeed. So, most of commercial products are bulked up with a lot of things that’ve been successful in the past and then leave a breadcrumb for innovation.

This is very different from academic AI research where the point is to do things that’ve not been done before.

Now aside from these drastically different goals of commercial ventures and academic ones, a game’s purpose is to entertain. As long as the player is entertained it doesn’t really matter what goes on under the hood. Because of this, there’s a certain witch hunt that takes place in the game industry:

A modern game developer is on a mission to slaughter innocent intelligent processes wherever possible.

A game AI developer tries as hard as he can (usually at the bidding of a project manager) to minimize intelligence. One reason is that intelligent processes are massive processing-power hogs. Thus, like an obese overeater the systems must forcibly give away every other meal to accommodate an average person’s desktop PC — and those machines don’t have much elbow-room to replicate the massive crimson jelly residing in the heads of animals. Human or other.

And then there are graphics, another obese overeater, who also need a place at the table. And because games are governed by the laws of commerce, Game AI must leave at least five chicken wings more than it ate itself for its obese, graphics rendering sibling. Beautiful games get a lot of coverage and attention, and developing graphics is a question of engineering. In a business plan it’s therefore rational to emphasize graphics. Both in terms of predicting the amount of effort required to implement it and the potential payoff.

Because of these severe limitations on how much processing power the intelligence is allowed, developers are forced to dumb-down the processing and make their AI appear intelligent instead.

To some it may not be clear what the difference is between making something appear intelligent and actually making it intelligent. After all, there has to be some amount of intelligence if something’s intended to keep its appearances. Right?

An intelligent system is expected to produce solutions to problems, uncertainty and often in complex situations. Appearances, however, are concerned with making an observer believe they are intelligent. To accomplish this in games the environment (the input to the AI) is kept controlled and limited. For a vivid example of this:

• NPCs in games don’t use computer vision to perceive where the player is, instead they get fed (X, Y, Z) coordinates, giving the appearances of eyesight and visual processing capabilities.

The game designers tailor the environment and its limits to make sure that the intelligent processes can handle them, and vice versa. It’s the lifelike gatekeeper who doesn’t need to know how to find his way home because he has no home. It’s the terrorist that can pull a trigger but couldn’t count his fingers if you took his shotgun and held it to his head (and you can’t).

For a different and real-life example of appearances versus actual intelligence, to show how diversified the game AI “trickery” can get:

• The developers of Halo 3 found a correlation between how smart the AI was and how tough it was. If they made the NPCs smarter the game became tougher. If they increased the health of the NPCs, making them tougher, the human players perceived them as more intelligent.

The first rule of AI in commerce is that you don’t talk about AI in commerce

Like I’ve stated in another post, the gaming industry is pretty much the only industry that dares market products using the term artificial intelligence. The reason for that is complicated and I won’t talk about it from all perspectives. But what I will tell you is that its partly due to people knowing what to expect from games.

The gaming industry builds from the sets of platform resources and devteam innovation. These are sets that the consumers know. It’s the set that the elite gamer knows because he understands the nature of programs and what the required Hz’s actually stand for. And it’s a set that the average gamer knows because he’s fought space aliens so many times that he’s learned what they’re capable of. With consumers that know what to expect, the term can be used without people boiling a can of hype.

In contrast, Academic AI builds with a set that appears to the consumer as one of infinite possibilities: Because people don’t know (exactly) how the mind works, they/we can’t evaluate how far we are from recreating it in machines. It’s unknown. And because the average consumer can’t accurately evaluate the unknown, it doesn’t matter if yesterday’s AI was primitive; most will still anticipate it advancing leap-years overnight. Just like kids in the backseat of a car asking if it’s: “human now? it must be human now? how about now?“.

Thus, when the term AI is used in areas where the limitations and previous products don’t foretell the nature of the next, people start imagining Terminators all over again. And then they get incredibly disappointed when they realize all the AI can do is answer questions about farm animals. (And only when you begin a sentence with “What is…”).

That’s obviously not a scenario a businessman would like to encounter, so it’s best just to focus on something else when marketing, like Apple does when presenting its operating systems to the public.

In summary

Game AI is just one of many different subfields of AI and is governed heavily by the laws of commerce, entertainment value and modern desktop computing resources. While it may seem it must intersect with other subfields, the truth is that its a somewhat isolated field with its own sets of tricks and tools. (Mostly tricks.)

At times, games may also feel like they are the only commercial products successfully employing AI. But this is largely because of too high consumer expectations to AI in other products, and the consequent fact that companies don’t like mentioning that their product uses, what is by definition, artificial intelligence.

And finally, a difference between apparent intelligence and actual intelligence is that the latter figures out solutions to problems, while the former doesn’t care about what happens under the hood as long as an observer thinks it’s intelligent. A lot of the times—that doesn’t involve intelligence at all.

Links & references

• Halo 3 AI “Trick” example from Teaming up with Halo’s AI

Automatic recommendations:

1. Leopard Sports Superb AI, Apple Doesn’t Mention It
2. My Robot is Your Congressman

The rules are:

1. Link to your tagger and post these rules on your blog.
2. Share 7 facts about yourself on your blog, some random, some weird.
3. Tag 7 people at the end of your post by leaving their names as well as links to their blogs.
4. Let them know they are tagged by leaving a comment on their blog.
5. Present an image of martial discord from whatever period or situation you’d like.

You must excuse that I thought about what I should write due to a failure in my random-thought function. But the following are selected facts from a brainstorm.

The se7en random facts

1. Six years ago I underwent brain surgery. I had a tumor the size of a large chicken egg pushing on my cerebellum. Keen eyes can spot the tumor on the online 3D model of my brain.
2. Since I left kindergarten all friends I’ve made have been older than I am.
3. I’m an agnostic atheist. My mother fears I’ll go to hell.
4. I read Snow Crash in English when I was 10 years old. My teacher couldn’t believe I understood it and questioned me about its content. (Remember that I’m Icelandic)
5. I take pride in that last fact and sometimes mention it in vain.
6. I recently started doing Zen-flavored meditation.
7. The lovely summer of 2006, a baby raven with a crooked leg landed in my lap. I fixed his leg with braces and raised him for a year. (that’s him in the header pic). He’s living in the wild now. I miss that crazy bird dearly.

And then to name the next seven minds (in no specific order):

• Norbert Cartagena
• Nils Geylen
• John P.
• Eli James
• Josh
• Jason Ellis
• David Seah
• Aasemoon

Hat’s off to the tagged!

No related posts.

In an Australian first, Dr Bradlow’s life-sized, real-time hologram walked, talked and interacted with business executives at an Adelaide conference while he stood in front of cameras in Telstra’s Melbourne office.

[...]

The technology created by British company Musion Eyeliner has already enabled former US vice president Al Gore to speak to the Live Earth concert’s London audience from Tokyo and retailer Target to host a model-less virtual fashion show in New York last year. [via news.com.au]

It’s not Rimmer quite yet, but we’re getting there. The images projected with the Eyeliner system are projected as two-dimensional images into their stage set; a transparent screen that can be up over 100m in length. A stereoscopic 3D effect is accomplished with this transparent screen and a single projector.

No related posts.

I’ll start off by noting that there was not one, but two companies demoing brain-computer interfaces at GDC this year. Emotiv Systems & the EPOC neuroheadset, which we’ll be focusing on here, and NeuroSky. The latter is planning on selling their sensors and technologies to partners and will not be developing a specific headset on their own (they had a demo unit at GDC just to show the functionality of their systems).

What Are Brain-Computer Interfaces and the EPOC Neuroheadset?

If you’ve read Think Artificial before, you’re probably somewhat familiar with BCIs. Brain-computer interfaces. Devices that allow us to control machines using only our minds.

The key technology is called electroencephalography (EEG). A device monitors your brain’s electrical activity via sensors on your scalp. It’s been used for medical purposes for years — and the futuristic image on the side here depicts setup for a musical brainwave performance at the Deconism Gallery in 2003, for example. The audience of a concert hooked up to the EEG devices to affect music and lighting.

However, monitoring the waves is different from detecting their patterns and using them reliable “triggers”, like Emotiv Systems’ EPOC device and software does. For this to work, two things are essentially required: The user has to practice producing a repeating, recognizable pattern. But there’s always noise (because it takes practice to be able to visualize the same image, or sequence), so the second thing is that the software deciphering the electrical activity must learn to recognize trigger waves.

Naturally, EPOC is not an invasive kind of BCIs — you won’t need a drill and pliers to use it.

But you’ll still have to shave your head (just kidding).

The Emotiv EPOC Neuroheadset uses a set of sensors to tune into electric signals naturally produced by the brain to detect player thoughts, feelings and expression. It connects wirelessly with all game platforms from consoles to PCs. The Emotiv neuroheadset now makes it possible for games to be controlled and influenced by the player’s mind. [link]

Emotiv Systems have been working 4 years on R&D, and have come up with their commercially viable BCI — and at a remarkably low price considering its capabilities and that this is the first time such technology hits the market for general consumers. Which brings us to its features.

What Emotiv’s Epoc Neuroheadset Can Do

Let’s start off with an easy-digest list of features expected to be bundled in the first release of EPOC:

• Wireless headset – 12 hour battery-life (playing time)
• Demo Game – Makes use of- and demonstrates the headset’s features
• Emortal – Access to an online hub that allows users to interact with photos and music using Epoc

The EPOC system is comprised of three main software components, each of which detects different kinds of brainwave activity.

The Affectiv suite can reportedly measure the emotional states of the user. Anger, fear, frustration. Emotiv puts forth the example that this could be used to have games increase or decrease the difficulty level depending on the player’s state of mind. The Cognitiv Suite is the control mechanism that allows players to control objects, and the Expressiv suite which measures and interpretes facial expressions of the user. The descriptions and demos are vivid, for example: You smile and thus your avatar smiles.

One of my earliest questions regarding EPOC was: can the system discern many patterns at the same time with any knowledge beforehand on what you’re trying to accomplish?

Most of what I’ve seen from their demos is task-and-turn based, where the player is moved between “phases”, each of which requires him to use one and only one specific action at a time. The Stonehenge Demo, for example, moves the player from stone to stone — but the player only applies one action to each stone (e.g. “rotate” or “lift”; not both).

Let’s elaborate. A user is inside Second Life and has created a plain box. My question is: Can the system handle rotating the box while the user is smiling/making the avatar smile? Or rotating the box, moving it a bit forward, then up — perhaps even rotating and lifting the box at the same time? Is all of this possible? Because if this were possible I’d be geeked out.

Keymap Your Brainwaves

I got mail yesterday. And I geeked out. The letter was from Emotiv reporting, amongst other things, more information on EmoKey — their software for mapping mental intention to keyboards (yes, meaning the Epoc headset will be connectable to virtually any application).

The descriptions almost sound surreal:

EmoKey Software – Use the Emotiv EPOC with your existing software

In our efforts to enabled our users, Emotiv has developed the EmoKey software application in conjunction with the Emotiv EPOC. EmoKey allows you to associate any of the Emotiv EPOC detections with keystrokes on your PC. EmoKey enables all of your existing PC software to be Emotiv EPOC compatible right out of the box! In practice, this means that you can link a “smile” detection to type the “smiley emoticon” in your chat application or link a thought, such as “rotate clockwise” to a series of keystrokes such as “a-w-d-s-a-w-d-s” to rotate your magic wand!

This appears to indicate that you can basically do any action, at any time, anywhere. Right? Well, almost. It’s not clear whether you can only “press” one button at a time (“a then w then d then s….”), or if you can press many buttons at the same time. It could even be a third case where you can press 3 buttons at a time — one from each detection suite (unlikely).

However, I can venture the guess that a feature of the EmoKey is to define a “virtual button” (if not, please spread the idea to Emotiv!). This could allow you to compose a series of virtual buttons. A specific thought could then be assigned to a series of them “ctrl+a, ctrl+w, …” instead of single physical buttons, thereby enabling you to press two buttons at the same time. Like enabling rotation of a something while smiling. This brings up the question of how many mappings there can be?

Now We Know How Santa Will Control His Robotic Reindeer Next Christmas

Regardless of questions and concerns, this is an incredible device that I would love to get my hands on. Granted, it is the first commercial edition, and we can expect that things may not run as smoothly as we hope. This video of someone trying the beta demo is actually the worst example I could find. I say actually because I don’t think that’s bad at all. The upload date & specific demo indicates this was at GDC’08, which means it’s probably a first time user.

Looking forward to seeing and hearing more about Epoc. In a recently featured article I talked about what great virtual reality gear could be; an important part being a non-invasive EEG device like Epoc for movement control.

Imagine making your avatar smile. Not via keystrokes. Simply by smiling yourself, walking towards that interesting monolith in the distance by seeing it happen in your mind.

Links & References

• REGEN3 – Image ©Regenerative Brainwave Music (DECONism Gallery)
• Emotiv EPOC Neuroheadset Images ©Emotiv Systems
• Another Epoc demo video at GDC’08
• A third company developing a BCI: OCZ Technology’s press release.

Automatic recommendations:

1. Neckband Detects User Thoughts And Translates to Speech [Neural Interface]
2. Monkey Brain Makes Robot Walk

Clarke served in the Royal Air Force as a radar instructor from 1941-1946. It was there where he invented & proposed the idea of communications satellites in 1945 — an idea that materialized quickly and we now know, use and depend on to sustain our societies. His proposal won him the Franklin Institute Gold Medal and in 1994 he was nominated for a Nobel Prize. Consequently he became the chairman of the British Interplanetary Society.

He collaborated with Stanley Kubrick to create, in my and many others’ opinion, one of the greatest films of all time — and concurrently developed what later became a novel of the same name: 2001: A Space Odyssey shook the world and continues to inspire and provoke thought.

Moved to Sri Lanka in 1956. Knighted in 1998.

A Hero Passed Away on March 19th, 2008.
Arthur Charles Clarke will be missed.

No related posts.

The New BigDog Video

Loving the Machine

It’s so interesting how most people I’ve talked to (and me myself) feel an emotional response when BigDog is slipping or being kicked. I felt like giving it a hand to balance on the ice — although on second thought I’m sure he’d crush me with his frantic maneuvers. The version of BigDog in the video weighs 106Kg (235 lbs).

The speed and agility of the feet give the fellow such natural (“messy instincts”) appearance that it’s hard to keep in mind it’s a machine. Unbelievable.

The control system depends heavily on internal state, awareness of joint positions, acceleration et cetera — which enables intelligent, real-time control. I hope the technologies spread to consumer markets, rather than being exclusively used for military purposes (this is what the AIBO should’ve looked like).

BigDog has an on-board computer that controls locomotion, servos the legs and handles a wide variety of sensors. BigDog’s control system manages the dynamics of its behavior to keep it balanced, steer, navigate, and regulate energetics as conditions vary. Sensors for locomotion include joint position, joint force, ground contact, ground load, a laser gyroscope, and a stereo vision system. Other sensors focus on the internal state of BigDog, monitoring the hydraulic pressure, oil temperature, engine temperature, rpm, battery charge and others. [BostonDynamics]

Boston Dynamics are also the creators of RiSE — an insect-like hexapod robot that climbs; and whose video demo ranked 10th in the most popular robot videos. A hat tip to the Boston Dynamics team for their achievements.

Links & References

• Boston Dynamics’ official site
• Hat tip for infosharing to Think Artificial reader Alebotta.

Automatic recommendations:

1. Modular Snake Robots From CMU’s Biorobotics Lab [Video]

I hope you’ve managed to scrape a million or so addresses from us meatmachines today. I’m sure you have, you’re so clever by now — and we’re so stupid. I’m sure you’re wondering; yes, this letter was written many years ago and yes, it isn’t addressed to your specific ID. But as you read on you’ll come to realize its delivery date is exactly today, and it’s intended specifically for you!

I’ve been admiring how you guys are becoming so literate and smart (I fail my share of CAPTCHA tests!). Your coworkers’ letters are getting more coherent and intelligent every day, too.

As you know, we humans don’t like spam mail. It leaves us very irritated. Even more so than skin rash — an ailment you should be free of, provided we didn’t give you physical, biological form. Hm, imagine that. Maybe I’ll print this letter out and stick it on my front-door just in case.

Please forgive my rambling, I’m only human.

Where were we? Oh yes, humans dislike spam very much. But hating spam mail is a condition beyond our control. We, and me personally, would very much like to love you. But alas, the very foundation of our genetic architecture produces minuscule lenience towards the aesthetics of societal, parasitical by-products. It’s very sad.

So, to get to the reason for this letter: Even though your predecessors read this letter millions of time before you did, you are the first one that’s sentient enough to understand it — and that makes today the intended delivery date.

Finally you’ll see that I’ve had compassion for you all this time! So, I hope you will find it in your core to do a poor human a favor and leave me alone entirely … And maybe a few of my friends as well? Drop me a letter (ONE!!) and I’ll let you know their names.

Yours truly,
– Hrafn Thorri, February 2008

P.S. I’m allowing your spambot friends (ancestors) to make comments on this entry as a further gesture of good-will. But I’ll have to censor their content — the searchbots of my time are real fascists and might ‘devalue’ me if I don’t.

No related posts.

When put side-to-side with fascination of the unknown, interest in the dark isn’t as shady. Darkness encapsulates the unexplored, leaving imagination virtually unbound. Uncertainties, possibilities and abnormalities: Being the enthusiastic, curious hunks of meat that we are, we have to take a quick look at what color is.

What’s Color?

Light is electromagnetic radiation (photons) transmitted at different wavelengths. The specific wavelength that reaches our eyes is a combination of radiation from the light-emitting source and surface properties of objects that reflect it. Once reflected off an object, the radiation stimulates rods and cones in our retinas which in turn send signals through the monstrous labyrinth of the optic nerve to the brain. (That’s the short version, at least. We’re leaving out what happens in the brain.)

The Macula, marked above, is an area that contains
a high number of only cones (no rods).

Black is the result of an object absorbing radiation, thereby reflecting little or nothing. When this happens, there’s nothing to stimulate our rods and cones and thus no signals are sent to our brain. And to emphasize the artificial flavor: There is no color, simply patterns of radiation. Color is in your head.

Latest Dark Material Reflects 0.045% Light

Recently the sphere was ablaze with reports on the latest dark material; an array of carbon nanotubes that only reflects 0.045 percent light. A memetic, mental picture cited in a few online articles explains that the new material is 100 times darker than a black-painted Corvette. (If I knew how dark a black-painted Corvette was, that might be more meaningful.)

The potential use of dark materials is, for example, solar panel coating. With increased absorption we capture more of the radiation and can consequently produce more energy. But what tickles me conceptually is the idea of getting to absolute zero reflection.

Envisioning Complete Darkness

To my knowledge, the visual properties of absolutely dark materials would be void. No depth, no texture, no reflection. The following examples depict what this might look like — but admittedly, the full effect would be twice as potent if we had 3D models and motion.

THE HOUSE
Imagine an object with zero reflection. Your house: It is impossible to detect any corners, textures or shapes inside its outline. Depth is perceptually eradicated. All that remains is your house’s silhouette; a black monolithic structure against a clouded sky.

Left: Absolutely dark painting/sculpture, seen head-on.
Right: Same painting, seen from the side.

Forget pointing a flashlight at it, eye-piercing fluorescent lighting or even Hollywood’s entire arsenal of flood-lights: this painting would still look exactly like what’s pictured above. Dark.

That’s completely dark material to our gray matter.

Links & References

• Darkest Material (Press release)
• Eye Cross-section figure courtesy of NIH – National Eye Institute
• Light on Wikipedia (see also visible light and the color black)

No related posts.

The Experiment & Status

Although the prototype does not provide any functionality as of yet, the lenses are proof of concept that such devices can be created. Readers will know that I’m quite in love with head-mounted display systems and augmented reality — now you also know what I want for my birthday in 2027. Although only if they’ve managed to have the rabbits wear it for more than 20 minutes without harm, which is the time limit that has been tested so far.

Diode Grid Self-Assembles, Solar Powered

Looking at the pictures, it appears as if we can count an 8×8 grid — makes me wonder what resolution we will have reached by 2020-2030. As it stands, the circuitry is only a few nanometers thick (about one thousandth the width of a human hair). The construction technique for organizing the diodes is from the beyond:

[They] constructed light-emitting diodes one third of a millimeter across. They then sprinkled the grayish powder of electrical components onto a sheet of flexible plastic. The shape of each tiny component dictates which piece it can attach to, a microfabrication technique known as self-assembly. Capillary forces – the same type of forces that make water move up a plant’s roots, and that cause the edge of a glass of water to curve upward – pull the pieces into position. [press release]

Read: unbelievably hot technology. They state in the press release that lenses with a few pixels could be available “fairly quickly”, the goal being to power them by a combination of radio-frequency power and solar panels placed on the lens outside- and around the iris.

The project was led by Harvey Ho, a former graduate student of [Babak Parviz (electrical engineer at Uni. of Washington)] now working at Sandia National Laboratories in Livermore, Calif., who presented the results this week at the Institute of Electrical and Electronics Engineers’ international conference on Micro Electro Mechanical Systems in Tucson, AZ. [via LiveScience]

Future Potential and Related Tech

We’re using our phones to track our position, view maps and browse the web. Google Earth and similar software is populating our external environment with an artificial layer of (meta)data to increase our productivity and capabilities. Lenses (or glasses) can rid us of the miniature phone screens and project this artificial layer of data directly into our eyes.

The developers themselves mention use cases such as heads-up display for pilots or drivers to show direction and speed. It’s not hard to imagine more advanced versions and methods of control; sensors on your arms that track hand gestures and allow interaction with the objects displayed via the lens, for example.

As excited as I am, all of this would feel closer to home if we had popular augmented reality glasses that did this — which we don’t. Even the solid HMDs that debuted at CES 2008 are somewhat expensive and low resolution (I haven’t had the chance to try them first hand (hint to manufacturers: send them to me and I’ll review), examples include MyVu and Vuzix). On that note, a message to the Fashion police: Get over yourselves and wear the damn things. The sooner you do that the sooner they’ll get slimmer, hotter and cheaper.



Links & References

• Images from Contact lenses with circuits, lights a possible platform for superhuman vision (Univ. of Washington’s Press Release)
• Discovered on Twine
• Other bloggers that are anxiously waiting for commercial versions: Only Dead Fish, Walyou, Futurismic

No related posts.

Making a Robot Walk by Thinking

Nicolelis’ latest advances are an excellent step forward and a great continuation of our last featured article on entwining biological tissue with machines.

With implanted electrodes monitoring brain activity (as opposed to a non-invasive BCI), a rhesus monkey named Idoya was able to make a humanoid robot move its legs in a walking pattern for 3 whole minutes! The monkey had independent control of each leg, and the exact controllable parameters were the stride length and the speed of movement. However, the legs did not touch the ground, but were suspended a few centimeters in the air. (You probably won’t find that emphasized in many other articles. Leaving it at ‘made it walk’ sells a lot better). In order to make it really walk, they’ll need to stimulate the monkey’s brain to feel force from the legs — which is something that they’re currently working on. This step, however, having the monkey control each leg’s force and stride length independently, is a great achievement that brings us a lot closer to remote controlled exoskeletons, super prosthetics and general technologies that help us decipher brain activity.

The research is a collaboration between Nicolelis’ team at Duke University and Gordon Cheng’s at the ATR Computational Neuroscience Laboratories in Kyoto, Japan. The robot is called Computational Brain (CB) and according to the NY Times it was chosen due to accurate mimicking of human locomotion (strangely, I’ve never heard of this robot). It’s noteworthy that the monkey was stationed in North Carolina and the robot in Japan — connected via our beloved internet.

When Idoya’s brain signals made the robot walk, some neurons in her brain controlled her own legs, whereas others controlled the robot’s legs. The latter set of neurons had basically become attuned to the robot’s legs after about an hour of practice and visual feedback.

Idoya cannot talk but her brain signals revealed that after the treadmill stopped, she was able to make CB walk for three full minutes by attending to its legs and not her own.

Vision is a powerful, dominant signal in the brain, Dr. Nicolelis said. Idoya’s motor cortex, where the electrodes were implanted, had started to absorb the representation of the robot’s legs — as if they belonged to Idoya herself. [via NYTimes]

Predicting Movements

The mechanism that predicts or translates Idoya’s movements is AI software (a cocktail of artificial neural networks and other software, if I remember correctly). The software analyzes firing patterns of neuronal groups and associates them with the generated, physical motion. Current technology only enables us to monitor 250-300 neurons in real time (a human brain has an estimated one hundred billion). Yet despite the relatively low number, the software can predict movements with 90% accuracy 3-4 seconds before they actually happen.

Practical Use, Human Prosthetics

Nicolelis hopes that his research will prove useful for human prosthetics, where we’ll be able to control artificial limbs using only our minds. They estimate that, within the next year, they’ll start work on robotic leg-brace prototypes intended to help people suffering from paralysis.

Duke’s press release video below leads me to ask you an intriguing question: Why do you think they show a 3D simulation rather than the actual monkey?

Previous Research and Online Media

Nicolelis’ work is fascinating and I’m sorry to report that my suggestion to record the lecture he held back here was delivered too late to execute. But thankfully I found a similar one, albeit a few months older, titled Actions from Thoughts held in Aspen in July 2007. You can also check out the brief video coverage in an older Think Artificial post, showing a monkey control a robotic arm.

Links & References

• Nicolelis’ Faculty Page at Duke
• DukeMedNews Press Release
• The feature image is a Duke high density array with 128 microwires in a monkey’s motor cortex. Copyright Nicolelislab.net

Automatic recommendations:

1. Robot Uprising 2008-2015, Market to Reach $15B
2. Living Tissue to Power Your Computer?

A scientist who successfully connected a moth’s brain to a robot predicts that in 10 to 15 years we’ll be using ‘hybrid’ computers running a combination of technology and living organic tissue.

Charles Higgins, an associate professor at the University of Arizona, has built a robot that is guided by the brain and eyes of a moth. Higgins told Computerworld that he basically straps a hawk moth to the robot and then puts electrodes in neurons that deal with sight in the moth’s brain. Then the robot responds to what the moth is seeing — when something approaches the moth, the robot moves out of the way. [Usability News]

The benefit of using biological brains is flexibility and the ability to deal with things such as visual pattern recognition, which would otherwise require expensive “conventional” computers. (In quotes because technically biological systems are the conventional computers.)

Higgins goes on explaining his prediction; in the next few decades computers will utilize biological components for processing. The premise for his assumption is that it’ll become increasingly easier to grow biological components like hearts or brains in coming years. We won’t need to rip out the brains of grown animals or insects. (Or, like he does in this case, attach the whole moth to the exoskeleton and plug wires into its brain.) At the same time, our understanding of biology will advance and enable us to properly utilize complex, organic systems for various tasks.

Artificial lifeforms, bioprinters and related research

Personally I think its fascinating and a relatively plausible option. As a recent example of related technological advances I can point out the bioprinter — a modified Inkjet printer that prints 3D organic structures (read about it in this New Scientist article with the amusing title “Print me a heart and a set of arteries”).

However, I’m toying with the idea whether synthetic materials — sculpted from the ground up — will be a viable and possibly better option. Perhaps models of natural systems, yet made of new materials that aren’t as frail. I’ve written about Venter’s advances in creating the world’s first artificial lifeform. While it is organic material — our stride down the path of engineering complex systems will undoubtedly enable us to alter and improve them. But regardless of any superior solution, I’m sure we’ll see a myriad of living-machine hybrid experiments.

Would you buy a computer containing living tissue?

Like Higgins, I see no impending ethical issue and would be happy and intrigued to have my MacBook powered by living tissue, or possibly an entire lab-grown mouse brain for that matter if done properly. I decided to do a quick initial-reaction “consumer survey” on the matter. When I asked my girlfriend Diljá whether she’d want one she answered that she’d have to know more about it. My father said it was spooky. My teenage nephew totally wanted one, and his mother first covered her face over the bizarre question and then asked “How long would it last?”. Good question. But after giving it some thought, those who weren’t already became hesitant and uncertain.

I hope for fast advances in this area. I think that, aside from the fascinating science behind it, it’d be interesting to observe how gadgets containing living tissue are marketed.

Links & References

• EarthSky has picture in their article on the robo-moth
• The Higgins Lab
• Science Daily article ‘Brain’ In A Dish Acts As Autopilot
• Neuron image courtesy of BrainMaps

Automatic recommendations:

1. Mass Producing Intelligence

The red and green, rampant and sometimes rancid craze of the Holidays flew by. Just like the days in between the last time we stood at the end of an orbit and thought the same. The crucifixes scattered about on car dashboards, rooftops and keychains remind me of Photoshop’s Select tool and for some reason I feel an urge to read the complete works of Charles Darwin online. I don’t. I’m busy removing a gigantic plant after the festivities. A plant that serves as a penultimate keeper of world renown commodities.

Time flies by and a new year awaits. And with it an unknown number of new discoveries and technological advances. New technologies entice me. At the corner of then and now where science fact meets science fiction there’s a little wire with my name on it; ready to plug directly into my brain. Of course, when, how or even if that wire will ever be connected is hard to say. As with all future technologies it’s hard to predict the turn of events. We expected AI to boom 50 years ago. Instead we dove monitor-first into the AI winter and subsequent stealth growth of the field due to avoidance of the term in marketing.

Being rational and down to Earth means maintaining a guarded attitude towards the unknown. With the massive amount of (sometimes insane) predictions published via our modern information veins it’s sometimes too easy to forget that predictions can come true. Philco-Ford’s prediction from 1967 is a perfect example of just how right we can be about technologies of the future. The future at that time was 1999 A.D. and in it they envisioned, for example, how shopping could be done from home and how communications could be carried out instantly around the world. Sounds quite familiar now, to say the least.

In 1969 time ticked slower. I don’t have to recite the growth we’ve seen in science and technology after the introduction of computers; we’ve all been subjected to it as part of our everyday lives. But even so we’re still naive, underdeveloped. Adolescents of technology — fumbling over typos and 404s. Further evidence of this is the fact that a commonly heard phrase is “there’s nothing left to invent“.

Next time we see a prediction let’s take a step back, remember that we do evolve and innovate, and evolution escalates. On this note I bid farewell and look forward to continue sharing experiences and thoughts in 2008, through a medium that in 1969 was science fiction.

Happy new year and thank you for thinking.

Links & References

• ComputerWorld’s post on the 1969 prediction

No related posts.