Okay Glass, pay for Tang.

Barcodes revolutionized commerce with their increased adoption in the early 1980s. Suddenly, accurately ringing up items in stores became much less dependent on the competence of the cashier. The shift from price tag to barcode meant that products simply needed a quick scan rather than a manual key-driven input. But before the barcode became affixed to virtually every product under the sun, how would you have proposed speeding up something like the supermarket checkout line?

Well, in 1961, the answer of the future was quite simple: voice recognition.

Voice recognition technology has been a promise of the future for decades. Countless sci-fi movies and futurist tracts assured the public that machines would soon understand us — or at least act semi-intelligently when given verbal instructions. But obviously it wasn't until recently that voice recognition started working in a way that the average person would deem acceptable. Today, Siri does her best to find us tomato soup delivery, and the magic of Google Glass lets me record video of my... (skydiving excursions?) without touching a button.

If you were reading the Sunday comics on August 27, 1961 you got a peek into this futuristic world of commerce, driven by engineer-perfected voice recognition. Arthur Radebaugh's "Closer Than We Think" illustrated how the supermarket checkout of the future would be made much more efficient with a microphone and "speech transcoder."

The supermarket cashier of the future would verbally input the items and their prices, and the machine would understand and tabulate them automatically:

Fascinating new areas of mechanics are opened up by the development of a typewriter which operates in response to the spoken word instead of to tapped keys.

The phonetic typewriter, an RCA invention, writes what it hears. This can lead to any number of startling applications. One may be a market tabulating machine run by the checker's voice — replacing the cash register with its banks of figure keys. The machine would print a tape showing each item and its price, then total the bill quicker than the checker could hand over the merchandise to the wrapping section. This phonetic checker would speed the checkout line to where it could become the fastest part of your visit to the market.

That "phonetic typewriter" struggled to prove itself technologically in any practical way. The methods for analyzing speech were far too primitive in the 1960s to render anything that would've worked in the wild.

But this kind of retail checkout system would be entirely possible today, given voice recognition's tremendous strides in the past decade. Retailers, however, seem to have another idea. The public's familiarity with barcodes has spurred the rise of a new kind of checkout experience that makes things much more efficient for the retailer, if perhaps more frustrating for consumers: the self-checkout.

Please put the Tang in the bagging area... Please put the Tang in the bagging area... Please...

In the middle of the last decade, the number of miles driven — both over all and per capita — began to drop, notes a report to be published on Tuesday by a nonprofit advocacy organization.

According Four public university presidents had compensation topping $1 million, according to the annual pay report by The Chronicle of Higher Education, four public university presidents had compensation topping $1 million. Education.

I promised last week that I would discuss three developments that turned almost-useless language-connected technological capabilities into something seriously useful. The one I want to introduce first was introduced by Google toward the end of the 1990s, and it changed our whole lives, largely eliminating the need for having full sentences parsed and translated into database query language.

The hunch that the founders of Google bet on was that simple keyword search could be made vastly more useful by taking the entire set of pages containing all of the list of search words and not just returning it as the result but rather ranking its members by influentiality and showing the most influential first. What a page contains is not the only relevant thing about it: As with any academic publication, who values it and refers to it is also important. And that is (at least to some extent) revealed in the link structure of the Web.

This idea led to the development of an astonishingly powerful technique for finding information and answering questions. Page ranking tends to melt away many of the problems that might have led one to think Natural Language Processing would sooner or later be a necessity.

You hardly need a system that can understand the sentence “What problems make breeding pandas in captivity difficult?” when the search string breeding captivity panda calls up a list of sites in which the top-ranking ones (those most referred to by others) contain exactly what you’re looking for.

There is scant need for a system that can parse “Are there lizards that do not have legs but are not snakes?” given that putting legless lizard in the Google search box gets you to various Web pages that answer the question immediately.

It is possible to find questions that are close to unanswerable using nothing but Google’s keyword search (and it is fun to try; I gave a simple example here), but it is difficult.

Google relies on at least four facts, all of them crucial, but especially the fourth one.

1. Computer memory chips have become so cheap and so tiny that in an office-sized space you can pack enough random-access-memory units to store an utterly gigantic automatically maintained concordance to the whole Web, augmented with copies of huge portions of what is on those sites.
2. Networks and processors have become so fast that your search command can be delivered to a server far away and checked against the gigantic index in just hundredths of a second.
3. The number of sites containing all of the words on a list (rather than just some of them) goes down rapidly with the length of the list, and much more rapidly when the words have low probabilities of occurrence.
4. Humans looking for a certain piece of information can on the whole be trusted to be smart enough to supply a list of words with the crucial property of having low probability in most texts but being guaranteed to occur in texts containing the desired information.

 

The combination is like magic. You can get very close to finding just the site you want by simply selecting a few words that won’t appear in most Web pages but will be in the ones you want to see. A nontrivial accomplishment (as pointed out to me by the linguist and founding staff member at Powerset Ron Kaplan, it is akin to translating English into a very basic structureless language), and one that not everyone will excel at. But it works.

Where is that giant tokamak machine being built to harness nuclear fusion in confined plasma for power generation, by some huge international collaborative project whose name you can’t remember? Forget build, generation, giant, harness, in, machine, power, project. … Those words are much too common; they’re almost useless to you. But try tokamak international: The top hit is the home page of ITER, which is the project name, and with a click or two you can find the location (near Saint-Paul-lez-Durance, France).

This doesn’t rely on artificial intelligence, it relies on your intelligence. It works so well that it has largely obviated question-answering by means of NLP. Devising computer programs that can understand the grammar and meaning of sentences remains an academic research challenge, and could still be very useful, but the pressure to provide it in a hurry has receded because of Google’s innovation.

In my next post I’ll describe a second development that has had a similar effect on the need for NLP.

On the heels of today's Creative Cloud software announcement, Adobe pulled the wraps off a new peripheral initiative for creating on a slate. First, Project Mighty is a cloud-connected stylus experiment that pulls tools from Creative Cloud setups and offers pressure sensitivity, a rechargeable battery, Bluetooth connectivity and built-in memory. This device is part of a new undertaking for Adobe that will seek to bridge the gap between software and hardware. In addition to Mighty, there's Project Napoleon, which will offer a second tool for tablet-style drawing. This peripheral will project straight lines to keep sketches neat and tidy in a high-tech ruler fashion. Details are scarce on both items for now, but those who are interested can opt for updates via the source link.

Update: We added a video demo from Adobe after the break

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Source: Projects Might and Napoleon Mighty and Napoleon

We might have been divided on the useful merits of the original HoodiePillow, but this updated travel version strikes a perfect balance between portability, comfort, and its ability to block out all distractions.

Like the original, the Travel HoodiePillow is basically just the hood from a hoodie attached to a soft cushion. But in this case the whole far outweighs the sum of its parts, since besides providing a comfy place to rest your head when you can't lay down, you can also draw the hood closed for modicum of privacy. It's no cone of silence, that's for sure, but for just $20 you can't ask for a better travel companion. [HoodiePillow via The Green Head]