Programmer creates 800,000 books algorithmically, starts selling them on Amazon

When we think about writing books, especially the technical kind, we think about a person or small group of people hunched over their keyboards typing away. There’s a good reason for that mental image: that’s how the majority of books are written. That’s not the way it has to be, though. Philip M. Parker, a marketing professor at INSEAD, has a patented system for algorithmically compiling data into book form. Thanks to Parker’s system, Amazon now has over 800,000 books for sale from his company. Other organizations pay for this service to compile data for their reports, so the system clearly has flexibility.

In a fascinating piece covering the news the sheer power of this system was revealed. Countless topics can be listed on sites like Amazon — everything you’d ever want to know. The funny part is that the books don’t even have to be written yet. Thanks to digital distribution and print-on-demand solutions, a whole new book can be generated on an incredibly obscure topic as soon as someone buys it. The system will be able to compile an entire book on the subject in the range of ten minutes to a few hours. It’s that simple.

This video below features Parker himself explaining how the process works, and why it’s useful. Because of his specialty in marketing, it’s easy to assume that these books are designed for spam-like purposes, but it does also have benefits to traditional writing outside of the amazing speed. Specifically, he points out that in the case of very rare diseases, it’s unlikely that any books would be written in the first place. Especially when you’re looking at statistics and data, having a computer compile and find potentially significant data is very useful. While the books won’t be particularly creative, they absolutely do have a place.

The technology isn’t just for books. Videos and games can be generated as well. When you’re focusing on areas like developing and distributing content all over the world in dozens of languages, traditional manpower isn’t exactly efficient. Humans just don’t have the ability to translate content to that many languages in a time and cost effective manner. Computers can knock that out during a long lunch. Using this system, it is possible to spread information to places that used to be impossible to reach. Computers won’t be replacing humans for writing the great American novel or entertaining the masses on TV, but it is obvious that computers will be an increasing fixture in the analysis and translation of content. This is a perfect complement to human creativity — not something for creatives, researchers, or consumers to fear.

[Image credit: Willi Heidelbach]

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MIT’s Brainput boosts your brain power by offloading multitasking to a computer

A group of American researchers from MIT, Indiana University, and Tufts University, led by Erin Treacy Solovey, have developed Brainput — pronounced brain-put, not bra-input — a system that can detect when your brain is trying to multitask, and offload some of that workload to a computer.

The idea of using computers to do our grunt work isn’t exactly new — without them, the internet wouldn’t exist, manufacturing would be a very different beast, and we’d all have to get a lot better at mental arithmetic. I would say that the development of cheap, general purpose computers over the last 50 years, and the freedoms they have granted us, is one of mankind’s most important advancements. Brainput is something else entirely though.

Using functional near-infrared spectroscopy (fNIRS), which is basically a portable, poor man’s version of fMRI, Brainput measures the activity of your brain. This data is analyzed, and if Brainput detects that you’re multitasking, the software kicks in and helps you out. In the case of the Brainput research paper, Solovey and her team set up a maze with two remotely controlled robots. The operator, equipped with fNIRS headgear, has to navigate both robots through the maze simultaneously, constantly switching back and forth between them. When Brainput detects that the driver is multitasking, it tells the robots to use their own sensors to help with navigation. Overall, with Brainput turned on, operator performance improved — and yet they didn’t generally notice that the robots were partially autonomous.

Now, it’s easy to see how this could be extrapolated out into the real world. We already have steering wheels that detect when we’re falling asleep — with Brainput, your car could automatically drive itself during that split second where you turn around to shout at your kids, or twiddle with various dashboard knobs. The same goes for airplane pilots, or indeed anyone seated behind the controls of a large, dangerous vehicle. As you can see in the picture at the top of the story, fNIRS is lightweight and doesn’t require a lot of hardware — and there are wireless systems available, too.

Moving forward, Solovey now wants to investigate other cognitive states that can be reliably detected using fNIRS. Imagine a computer that increases the size of buttons and text when you’re tired, or a video game that slows down when you’re stressed. Your Xbox might detect that you’re in the mood for fighting games, and change its splash screen accordingly. Likewise, Firefox could detect that you’re feeling amorous, and automatically load up Private Browsing mode. Menu buttons could move around and change in size — or disappear entirely. Eventually, computer interfaces might completely remold themselves to your mental state.

Read more at Erin Treacy Solovey’s website (or jump directly to the paper [PDF])

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ZX Spectrum: 30 years old, and still one of the cheapest computers ever made

Today is the 30th birthday of the ZX Spectrum, one of the most popular home computers ever made, and probably the single most important factor in the creation of the IT industry in the UK. The ZX Spectrum, made by Sinclair Research in Cambridge, England is usually considered the UK equivalent of the US-made Commodore 64.

Hardware-wise, the ZX Spectrum was completely unremarkable. There was an 8-bit Zilog Z80A CPU, a graphics chip capable of outputting 32 columns by 24 rows (256x192px) with 15 colors, and either 16 or 48KB of RAM. At just £125 ($200), however, the ZX Spectrum was incredibly cheap. The Commodore 64 cost $600. The BBC Micro, made by Sinclair’s arch rival Acorn Computers, cost £299. Despite costing just a fraction of its contemporaries, the ZX Spectrum had comparable functionality. All three computers had similar amounts of RAM and processing power, and all three had similar editions of the BASIC programming language.

How did Sinclair Research pull it off? Innovative design and aggressive engineering. From the very start, Sinclair Research knew that it wanted the ZX Spectrum to be as cheap as possible, and so almost every component was engineered from the ground up with penny pinching in mind. The main printed circuit board was kept as small and dense as possible, which resulted in a very lithe chassis (just 23x14x3cm, compared to the monstrous 40x21x7cm Commodore 64 and gargantuan 40x35x8cm BBC Micro). Instead of using a conventional keyboard with hundreds of moving parts, a rubber, chiclet “island” keyboard with just four or five parts was used. (In the eyes of original users, this resulted in the ZX Spectrum keyboard feeling like “dead flesh” — an early example of a tech meme.) The ZX Spectrum was wrapped in a plastic case and weighed just 550 grams (1.2lbs), compared to the metal, clunky 1.8kg (4lb) Commodore 64, and back-breaking 3.7kg (8.1lb) BBC Micro.

In short, the ZX Spectrum was simply better engineered than its contemporaries — much like iPhone, except Apple uses its engineering and supply line advantage to squeeze out higher profits, rather than slashing prices. Like the ZX Spectrum, it’s not like the iPhone uses fundamentally different silicon or materials — Apple is still limited by the state of the art — but through design, engineering, and supply line expertise, Apple simply manages to cram more tech into the same (or smaller) space — and with a cheaper bill of materials.

ZX Spectrum+, a later version that did away with the “dead flesh” keyboard

The ZX Spectrum would go on to sell five million units — not bad, when you consider there are only 30 million homes in the UK — and net Clive Sinclair, the owner of Sinclair Research, a knighthood for “services to British industry.” Curiously, Sinclair, a serial inventor, recently admitted that he doesn’t actually use computers — he prefers the telephone to email.

To this day, even after 30 years of being hammered at by Moore’s law and accounting for inflation, there are remarkably few home computers that have been sold at a lower price point than the ZX Spectrum (it would cost around $450 today). The Raspberry Pi, a British-made Linux-based PC that will be sold for around $25, is the obvious exception, and the spiritual successor of the ZX Spectrum.

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Red Ray 4K cinema laser projector on display at NAB Show 2012

At NAB Show 2012, Red officially unveiled itspreviously teased Red Ray 4K cinema projector. All matte-black metal and visible bolts, the device looks as though it has been lifted directly from science fiction — especially given the fact that movies projected by this impressive piece of tech will be blasted at the screen by a laser.

There will be two editions of the Red Ray: The less-than-$10,000 home model supporting screens up to 15 feet in size should be released to market sometime this year, while a more expensive professional model to suit larger screens will be released later. The device has a rated laser life of over 25,000 hours, supports both 2D and passive 3D (with 4K projection for each eye) from a mean-looking T1.8 50mm lens, and has dedicated access panels for the laser phase adjustment oscillator, the angular refraction aberration indexer, and the lens filter.

Reports from the NAB Show floor uniformly praise the performance of the Red Ray, citing impressive contrast, color reproduction, dynamic range, and clearly defined small detail.

Beyond the laser projection itself, Red Ray is outfitted with a lot of extra wizardry. To feed the projector with high-res video files, there’s an internal SSD hard drive, an SD card slot, USB socket, and a couple of HDMI sockets. The Red Ray websitesuggests that there might be a future version with Firewire and eSATA connectivity, too. Considering the projector is capable of pumping out 120 fps, at 4K-3D, there’s probably a very powerful processor under the hood, too — much like the Red Epic-X 5K camera.

It would seem logical for lasers to someday take over as the primary method for projector illumination. As we learned from BMW’s latest and greatest headlamps, laser diodes are significantly brighter, use less power, last longer, and are physically smaller, making them better in almost every way when compared to LEDs or the more traditional projector lamps. The only negative is in the price; it would be safe to assume that a sizable portion of the $10,000 price point could be attributed to the new pew-pew laser beam technology. While out of reach for most consumers, it is quite possible that the shift to laser-based projectors will happen in cinemas in the not-too-distant future, hopefully going at least a small way toward justifying the price of movie tickets these days.

[Image credit: Engadget]

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Researchers create brain-computer interface that bypasses spinal cord injury paralysis

Scientists at Northwestern University in Chicago, with funding from the National Institutes of Health, have successfully bypassed the spinal cord and restored fine motor control to paralyzed limbs using a brain-computer interface.

The researchers have created a neuroprosthesis that combines a brain-computer interface (BCI) that’s wired directly into 100 neurons in the motor cortex of the subject, and a functional electrical stimulation (FES) device that’s wired into the muscles of the subject’s arm. When the subject tries to move his arm or hand, that cluster of around 100 neurons activates, creating a stream of data which can then be read and analyzed by the BCI to predict what muscles the subject is trying to move, and with what level of force. This interpreted data is passed to the FES, which then triggers the right muscles to perform the desired movement.

The end result is a computer network that effectively replaces the nervous system and restores remarkably accurate fine motor control to a paralyzed arm — watch the video below and be amazed. You will notice that, as always with bleeding edge science, the subject of this study is a rhesus monkey rather than a human — but our anatomy is very, very similar to that of our primate cousins.

The novel element of Northwestern’s neuroprosthesis is the introduction of a brain-computer interface. At the moment, state-of-the-art solutions use FES devices with pre-programmed basic movements (arm lift, hand open, etc.) that are triggered by small muscle movements in non-paralyzed muscles. With the BCI, rather than listening for second-hand signals, around 100 neurons from the specific region of the motor cortex that handles arm and hand movements are used. As you can see from the video, not only is this approach responsive, it seemingly allows for a whole range of grasping movements.

Now, it’s important to bear in mind that we’re a long way away from human trials — these monkeys had a multi-electrode array directly implanted into their brains — but, even so, we should still be very excited. This is a hugely important step towards bionic implants that make paralysis a thing of the past. It might even be the answer to other neurological diseases, such as Parkinson’s. The research paper (paywalled) notes that, worldwide, 130,000 people per year sustain spinal cord injury — with half of those becoming paralyzed from the neck down.

Even healthy humans — especially those of transhumanist stock — might want to replace or augment their nervous system with a computer network. Due to slow clockspeed and neuron-neuron signal propagation, human reaction time is fairly lackluster — but what if we had a computer coprocessor and electrical wiring that kicked in, when needed? Like modern cars that have complex timing and power control systems, what if humans could run faster or stay awake longer if we had a computer system to help out? You’d be able to connect to your on-board (on-brain?) computer via your smartphone, of course, and tweak various settings…

Read about decoding brain signals and bionic eye implants

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Is holographic storage finally coming to market?

Holographic storage is one of those snake-oil technologies that’s almost as vaporous as Duke Nukem Forever or Half-Life 2: Episode 3. It has been been something of a digital philosopher’s stone since the ’60s, promising infinite storage and massive data rates. When a holographic storage prototype was finally demonstrated at NAB 2005 by InPhase Technologies, many of us couldn’t believe that we might actually be standing on the cusp of a storage renaissance.

In 2010, though, with no further public demonstrations, $100 million spent, 10 years of R&D, and commercial viability remaining elusive, InPhase ran out of money and shut up shop. For many of us storage nerds, it was the end of a dream. Well, good news: InPhase’s assets have been bought up by a company called HVault, and it’s currently demonstrating its holographic storage tech at NAB 2012 in Las Vegas. Better yet, HVault’s tech will apparently launch in “spring 2012″ — i.e. soon.

Holographic storage, if you haven’t heard of it before, is (generally) a write-once-read-many (WORM) archival storage technique. Where tape and hard drives are magnetic, and optical discs bounce lasers off little pits, holographic storage actually uses a photosensitive medium — like photographic film — to store 3D images that represent data.

To store data, two lasers are used: a reference beam and a signal beam. The signal beam is modulated by the data being written, while the reference beam illuminates the target region and effectively keeps track of where the data is being recorded. To read data, the reference beam is pointed at exactly the same location, creating a hologram of the data stored by the signal beam. This hologram is immediately “read” by a sensor, much like the CMOS sensor found in a digital camera. Unlike conventional, linear storage mediums (HDD, DVD, tape) every “bit” of the holographic image is read in parallel, potentially resulting in huge data rates.

Holographic storage can also (in theory) store a vast amount of data — about four gigabits per cubic millimeter. Basically, depending on the thickness and quality of the storage medium, and the laser, thousands of individual holograms can be stored, stacked on top of each other. Depending on the angle and wavelength of the reference beam, and the position of the media, different holograms can be projected. HVault advertises that its system could replace petabyte storage clusters, but it doesn’t directly say how much data it can store on each holographic storage disc. Four gigabits per cubic millimeter equates to around 2.5 terabits per square inch — more than two times denser than Seagate’s recently-announced HAMR hard drive tech.

Finally, holographic media is meant to be blessed with a lifespan of over 50 years, compared to 2-5 years for magnetic storage. Of course, whether holographic readers will still exist in 50 years is another question entirely.

Now we just have to wait and see if HVault actually launches this spring, or whether it’s still just vaporware. For a technology that promises to revolutionize storage, its website does not instill me with hope. The fact that I don’t have a pretty photo of some holographic storage to share with you probably isn’t a good sign either. Still, you never know!

Read more about holographic storage on Wikipedia

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MIT discovers the location of memories: Individual neurons

MIT researchers have shown, for the first time ever, that memories are stored in specific brain cells. By triggering a small cluster of neurons, the researchers were able to force the subject to recall a specific memory. By removing these neurons, the subject would lose that memory.

As you can imagine, the trick here is activating individual neurons, which are incredibly small and not really the kind of thing you can attach electrodes to. To do this, the researchers used optogenetics, a bleeding edge sphere of science that involves the genetic manipulation of cells so that they’re sensitive to light. These modified cells are then triggered using lasers; you drill a hole through the subject’s skull and point the laser at a small cluster of neurons.

Now, just to temper your excitement, we should note that MIT’s subjects in this case are mice — but it’s very, very likely that the human brain functions in the same way. To perform this experiment, though, MIT had to breed genetically engineered mice with optogenetic neurons — and we’re a long, long way off breeding humans with optogenetic brains.

In the experiment, MIT gave mice an electric shock to create a fear memory in the hippocampus region of the brain (pictured above) — and then later, using laser light, activated the neurons where the memory was stored. The mice “quickly entered a defensive, immobile crouch,” strongly suggesting the fear memory was being recalled.

The main significance here is that we finally have proof that memories (engrams, in neuropsychology speak) are physical rather than conceptual. We now know that, as in Eternal Sunshine of the Spotless Mind, specific memories could be erased. It also gives us further insight into degenerative diseases and psychiatric disorders, which are mostly caused by the (faulty) interaction of neurons. “The more we know about the moving pieces that make up our brains,” says Steve Ramirez, co-author of the paper. “The better equipped we are to figure out what happens when brain pieces break down.”

Bear in mind, too, that this research follows on from MIT’s discovery last year of Npas4, the gene that controls the formation of memories; without Npas4, you cannot remember anything. MIT has successfully bred mice without the Npas4 gene.

The question now, though, is how memories are actually encoded — can we programmatically create new memories and thus learn entire subjects by inserting a laser into our brain? We know that a cluster of neurons firing can trigger the memory of your first kiss — but why? How can 100 (or 100,000) neurons, firing in a specific order, conjure up a beautifully detailed image of an elephant? We’ve already worked out how images are encoded by the optic nerve, so hopefully MIT isn’t too far away from finding out.

Read more at MIT or check out the research paper at Nature (paywalled)

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Wikipedia kills off Encyclopaedia Britannica, at least in print

Nearly two and a half centuries after the first edition of the Encyclopaedia Britannica was released, the printing presses have stopped. Gone are the traveling salesmen hawking the books door to door, making for yet any victim of the digital age. From here on out, the reference books that all of us used at one time or another will head to the web.

Chicago-based Encyclopaedia Britannica, Inc. will stop selling the current edition once inventory are depleted.  This means that the 32-volume set, which costs $1,395 and includes some 65,000 articles, will be the last printed by the company. The focus will shift to the web version which runs a much more palatable $69.95 per year and currently has about 500,000 subscribers.

Britannica sees their online version as a natural progression of things: “In a larger sense this is just another historical data point in the evolution of human knowledge,” the company said in a blog postannouncing the move. “For one thing, the encyclopedia will live on — in bigger, more numerous, and more vibrant digital forms.”

The death of what could be considered the most important reference work of modern times can be laid directly at the foot of another marvel of modern learning: Wikipedia. The site, while written by anyone and not just the “Nobel laureates, historians, curators, professors, and other notable experts” that comprise Britannica’s writers, is generally a good resource. Wikipedia is also free, and that is a big draw (so is the rest of the Internet as well). In a time where knowledge was not easy to come by, paying a premium for a source like Encyclopaedia Britannica made sense. Now, not so much.

In response, Britannica will pin its future on the web. This seems well and good, but even at $69.95 there’s a cost — most people will still turn to Wikipedia and other free sources. One thing the publisher may have going for it is the position of educators, though: many forbid Wikipedia as a source for papers and the like due to its crowd-sourced nature.

With the content within Encyclopaedia Britannica coming from reputable and knowledgeable sources, it still is a top-tier source for students — and respected by educators — even though a 2005 study byNature showed Britannica had nearly the same amount of errors in its articles, on average, as Wikipedia. I guess image is everything.

This all noted, there is a future for reference materials in book form. While the usefulness and speed of the Internet is nice, for some nothing beats the printed word. Yes the market has shrunk dramatically, but I strongly believe there’s too many of us old fashioned folks out there to let it completely die. Would you?

[Image credit]

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IBM Watson heads to Wall Street

After conquering Jeopardy, battling patent trolls, making inroads into medical insurance claims, and threatening to replace customer service representatives, IBM’s Watson is now looking to take its first foray into Wall Streetesque financial services. Working with Citigroup, IBM has entered into an “exploratory agreement” that will cover everything from streamlining the banking experience for customers, through to “empowering financial professionals to make better business decisions.” In other words, watch out stock traders: Watson’s coming.

Watson, powered by IBM’s DeepQA software, is fundamentally a huge question answering machine. You feed in as much data as possible — general knowledge in the case of Jeopardy, or financial and customer data in the case of Citigroup — and Watson then gets to work, making links from seemingly disparate data.

As far as stock trading goes, Watson is obviously well-suited to helping financial professionals make quick and well-informed decisions based on (potentially) decades of past data. On the other side of the fence, Citigroup hopes that Watson’s ability to understand natural language (as shown off in Jeopardy) will be able to provide “a first-of-a-kind customer interaction solution.” This will probably take the form of telephone and online banking where Watson helps you complete a typed or spoken request.

That Watson is wading into stock trading is exciting, but probably not as shocking as it first seems. Yes, Watson will probably be very good at advising (and maybe even making) trades, but the concept of algorithmic trading — automated, computer-controlled trading — is already very mature and used by every major bank. Still, until IBM actually hooks Watson up to a stock market, it’s probably not too wise to prejudge the outcome; Watson is obviously pretty wizardly, and for all we know he might devise a trading scheme that earns Citigroup billions more than its existing algorithms. It would be nice to think that that money will somehow make it back to the bank’s customers, but it will probably just be spent on more Watsons.

Read more about the inner workings of Watson

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