South of the South

Jul 31

Hurricane. Adventureland, Long Island, c.1995

Hurricane. Adventureland, Long Island, c.1995

Jul 29

You know you’re out of South Florida and in Martin County dri

You know you’re out of South Florida and in Martin County dri

Jul 28

Miami office. Lame.

Miami office. Lame.

Jul 27

everything will be ok

everything will be ok

Jul 26

Not cool. And this was my second* favorite person in the company from another office. *first favorite is Josh in Charleston, of course.

Not cool. And this was my second* favorite person in the company from another office.

*first favorite is Josh in Charleston, of course.

Jul 23

Hobe Sound Beach

Hobe Sound Beach

Jul 22

business cat from Russia.

business cat from Russia.

EXCUSE ME I WAS LOOKING AT THE WATER via i.imgur.com

EXCUSE ME

I WAS LOOKING AT THE WATER

via i.imgur.com

Jul 20

It never even crossed my mind that I was doing something good, like helping to archive human knowledge that predates the Internet, each time I solved a reCAPTCHA to post a snide message board comment. This is without a doubt the most practical/amazing use of crowdsourcing I’ve seen to date. Web 3.0 is here. A CAPTCHA is a program that can tell whether its user is a human or a computer. You’ve probably seen them — colorful images with distorted text at the bottom of Web registration forms. CAPTCHAs are used by many websites to prevent abuse from “bots,” or automated programs usually written to generate spam. No computer program can read distorted text as well as humans can, so bots cannot navigate sites protected by CAPTCHAs. About 200 million CAPTCHAs are solved by humans around the world every day. In each case, roughly ten seconds of human time are being spent. Individually, that’s not a lot of time, but in aggregate these little puzzles consume more than 150,000 hours of work each day. What if we could make positive use of this human effort? reCAPTCHA does exactly that by channeling the effort spent solving CAPTCHAs online into “reading” books. To archive human knowledge and to make information more accessible to the world, multiple projects are currently digitizing physical books that were written before the computer age. The book pages are being photographically scanned, and then transformed into text using “Optical Character Recognition” (OCR). The transformation into text is useful because scanning a book produces images, which are difficult to store on small devices, expensive to download, and cannot be searched. The problem is that OCR is not perfect.

It never even crossed my mind that I was doing something good, like helping to archive human knowledge that predates the Internet, each time I solved a reCAPTCHA to post a snide message board comment. This is without a doubt the most practical/amazing use of crowdsourcing I’ve seen to date. Web 3.0 is here.

A CAPTCHA is a program that can tell whether its user is a human or a computer. You’ve probably seen them — colorful images with distorted text at the bottom of Web registration forms. CAPTCHAs are used by many websites to prevent abuse from “bots,” or automated programs usually written to generate spam. No computer program can read distorted text as well as humans can, so bots cannot navigate sites protected by CAPTCHAs.

About 200 million CAPTCHAs are solved by humans around the world every day. In each case, roughly ten seconds of human time are being spent. Individually, that’s not a lot of time, but in aggregate these little puzzles consume more than 150,000 hours of work each day. What if we could make positive use of this human effort? reCAPTCHA does exactly that by channeling the effort spent solving CAPTCHAs online into “reading” books.

To archive human knowledge and to make information more accessible to the world, multiple projects are currently digitizing physical books that were written before the computer age. The book pages are being photographically scanned, and then transformed into text using “Optical Character Recognition” (OCR). The transformation into text is useful because scanning a book produces images, which are difficult to store on small devices, expensive to download, and cannot be searched. The problem is that OCR is not perfect.