Showing posts with label Matching. Show all posts
Showing posts with label Matching. Show all posts

April 26, 2016

Owl Mugs

Just wanted to share these three new owl mugs we got. 

One is orange, one is brown, and one is light blue.

The eyes are adorable on these cups. 

It's almost like a family the way they look together. 

All the other coffee/tea cups we have are now officially obsolete. 

These are the only ones getting any thirsty attention. ;-)

(Source Photo: Andy Blumenthal)

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August 5, 2011

Facial Recognition Goes Mainstream

Bar

Facial recognition applications are no longer just for the military and law enforcement to identify hostiles or criminals, but rather is going mainstream.

The Wall Street Journal (5 August 2011) reports from the bar scene to the television and from vampire gaming to celebrity match-ups, facial recognition software is now part of our everyday technology mix.

Facial recognition is "at a tipping point where some of these face-recognition technologies are not just gimicks, but are becoming useful." Moreover, the technology has become quite good with "frontal face images, the error rate of rejecting a legitimate claim--when the face image and name match-decreased to 0.29% in 2010 from a rate of 79% in 1993."

So here are some examples of how facial recognition is being used:

- SceneTap: Free app for iPhone and Droid "displays real time stats on the local bar scene...shows the number of people at the bar, the male-to-female ratio, and the average age of the patron"--all from facial recognition--this is not bad except for the bartender on a slow night.

- TVs with Viewdle: TV set-top boxes with facial recongition can "identify who is sitting in front of the TV then customize programming accordingly...displaying most recently watched or recorded shows"--can anyone say America's Got Talent!

- Third Eye: Facebook game that based on facial recognition identifies people as either vampires or slayers. Even without the app, I'd bet I'm one of the slayers :-)

- FaceR Celebrity: This iPhone app uses a picture and facial recognition software to determine which celebrities you most closely resemble. For me, it's Sylvester Stallone, all the way--I'm sure of it.

A lot of people are concerned about the privacy implications of facial recognition--collecting and storing images of faces and using it for surveillance and tracking and getting into your business...like knowing what bars or whereever else you are going to.

But apps like SceneTap say they don't collect personal information, nobody sees the video feed, and they don't match the images to photos on the web or Facebook to identify exactly who is entering the bar. This is sounding a little like TSA and the body imaging scanners they use--i.e. don't worry nobody sees your privates! :-)

But perhaps, whether or not they do or don't isn't the point, they could and that is a privacy concern.

Facial recognition technology, even though it is used in gaming, it is not kid's play, and it should be regulated to avoid a society where Internet "big brother" has virtually unlimited capability to track and match each and every facial you!

(Source Photo: here)

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November 7, 2010

Match Me With You

eHarmony and Match.com and other matchmaking sites are all the rage on the single scene with recommended partners for people being done by computer algorithm.

Now this concept of matching of people is going beyond people’s love lives and into the world of business.

CIO Magazine (1 Nov. 2010) reports in an article called “Call Center Matchmaking: Analytics pair customers with the right agents for better service” that companies are using similar technology to match customers and call centers reps in order to get higher satisfaction ratings and increased retention rates—and it’s working!

Since implementing the IBM system called Real-Time Analytics Matching Platform (RAMP), for example, Assurant has increased customer retention rates by 190 percent.

Other companies have been doing customer matching on a more elementary level for some time—for example, financial service firms route calls from high-net worth or high-balance customers to “premier agents.” Similarly, calls made at certain time are “routed to Boise instead of Bangalore.”

With computer systems like RAMP, there is a recognition that customers can do better by being matched with specific customer service representatives and that we can use business analytics to examine a host of data variables from sex and age to persistence in calling to match a customer to “the right” representative to handle their issues.

Based on success rates, computers have been shown to perform sophisticated business and data analysis, and to successfully match people for more successful business (and life) transactions.

If we can successfully pair people for love and for customer service, it makes me wonder what’s next (maybe happening already)? For example, will we pair people to “the right”:

  • Potential adoptee parents?
  • Neighborhoods?
  • Schools?
  • Jobs?
  • Bosses?
  • Coworkers?

In essence, as the “bar is raised” in a highly global and competitive environment, will we be pushed to seek to maximize our potential for success interaction with others—for developing high-performance and highly profitable interactions—by pairing exclusively with those that “screen” positive for us?

With genetic testing already being used to screen for babies that people want—like an order at Burger King—“hold the pickle, hold the lettuce, special orders don’t upset us…”—we are already well on our way to “special ordering” the people in our lives.

Companies have also started to use intelligence and personality tests to weed out applicants, and the use of personality tests like Myers Briggs is already being employed for better understanding each other and working together.

However crude all this may be, it is essentially a high-tech way of trying to optimize our performance. The question is can we use technology to enhance personal interactions and elevate performance without subjecting people to undue bias, criticism, and violation of their privacy? This is a very slippery slope indeed.

Another potential problem with computer matching is that when we rely on computers to “tell us” when we have a good match, we are potentially missing potential opportunities for matches with others that cannot be easily quantified or summed up by a computer algorithm? As they say, for some “two birds of a feather flock together” and for others “opposite attract”—we shouldn’t limit ourselves to any creative, positive possibilities in relationships.


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