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Diffbot — Machine learning is the new Big Data and Giving it away might be a Money Maker.

Machine learning is the new Big Data and Giving it away might be a Money Maker.

“Everything’s becom­ing intel­li­gent, but the lim­it­ing fac­tor of intel­li­gence is access to struc­tured data,” Tung says. Diff­bot, an arti­fi­cial intel­li­gence com­pa­ny that helps clients extract and com­bine data from mul­ti­ple Web sources wants to scrape all the data on the web (all of it) to put it into a struc­tured for­mat. Mak­ing it use­ful for all sorts of busi­ness pur­pos­es and make mon­ey doing so.  The com­pa­ny says its tech­nol­o­gy “uses com­put­er vision and NLP algo­rithms to extract and struc­ture any web page into the world’s largest struc­tured data­base… with no human cura­tion or over­sight.” Found­ed in 2009 The Palo Alto, CA-based start­up announced today it raised $10 mil­lion from investors to expand its “knowl­­edge-as-a-ser­vice” offer­ings to busi­ness­es and con­sumer apps.  They have raised close to $13 mil­lion since its seed round in 2012.  Diffbot’s plan is to cat­a­log tril­lions of facts across the Web—many of them drawn from page ele­ments such as com­ment forums, which can’t be mined by tra­di­tion­al search engines. Web-min­ing can be a com­pet­i­tive advan­tage for apps as well as the pro­lif­er­at­ing devices of the Inter­net of Things, Tung says. The start­up says it has made a sig­nif­i­cant start on that goal, hav­ing indexed 1.2 bil­lion…

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7 E‑Commerce Shopping Innovations for Future Holidays

7 E-commerce Shopping Innovations for Future Holidays

Con­sid­er­ing it’s the hol­i­day shop­ping sea­son I fig­ured we should look into what’s on the E‑commerce hori­zon. Ray Burke direc­tor of Indi­ana Uni­ver­si­ty’s Cus­tomer Inter­face Lab­o­ra­to­ry has spent years ana­lyz­ing shop­ping habits. He was inter­viewed in a recent arti­cle on Popsci.com and he cov­ers 7 top­ics about the future of buy­ing com­mer­cial goods and con­sumer expe­ri­ence. E‑commerce will become the only com­merce; with the use of Big Data and Psy­chol­o­gy they’re fig­ur­ing out nov­el ways to track your in-store behav­ior, antic­i­pate your needs, and help you find exact­ly what you need if it’s avail­able. So let’s see what 7 inno­va­tions are in “store” for us lit­er­al­ly: 1. Track­ing Eye Move­ment 2. De-stress­ing Shop­pers 3. Quick­er Store Exits 4. Mon­i­tor­ing Moods 5. Instan­ta­neous Prod­uct Print­ing 6. Intu­itive per­son­al­iza­tion through feed­back shop­ping 7. Shar­ing Econ­o­my Some of these may feel very intru­sive in a “Big Broth­er” kind of way but at this very moment you still live in a con­sumer dri­ven soci­ety and mak­ing buy­ing eas­i­er keeps you hap­py and makes the retail­er rich­er. It is a twist­ed win-win sce­nario. Besides shop­ping for the hol­i­days just seems like a chore so per­haps all of these will gen­uine­ly help. Track­ing Eye Move­ment —…

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What does Google’s D‑WAVE, Blippar, and Machine Vision have to say about where media is heading?

What does Google’s DWAVE, Blippar, and Machine Vision have to say about where media is heading?

So why is a com­put­er being able to see be so darn impor­tant, I’ll tell you why, so adver­tis­ers can know exact­ly who you are, wher­ev­er you are, and send a high­ly tar­get­ed prod­uct adver­tise­ment at you through some pret­ty clever chan­nels. Let’s imag­ine a far future sce­nario, like in 16 months from now, where you are walk­ing down the street and the HD dig­i­tal dis­play screen which is in actu­al­i­ty the glass of a store­front you hap­pen to be pass­ing near calls out to you specif­i­cal­ly. “Hey Jere­my! I love the Ralph Lau­ren Jack­et you’re wear­ing. We just got in the 2017 bold cut of that jack­et in Dark Green, take a look” The dis­play screen pro­ceeds to show you what you would look like by over­lay­ing the new jack­et on top of the old while main­tain­ing the street view behind you by using Aug­ment­ed Real­i­ty. The dis­play then pro­ceeds to say “if you come in and buy one right now, we’ll offer you a %10 per­cent dis­count”. You say to your­self, damn, I look great in this jack­et and walk right on in. SUCKER!!!! Hon­est­ly sce­nar­ios like this are in devel­op­ment right now. Not as cohe­sive as the…

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Disney and Carnegie Mellon is redefining Big Data with EM-Sense.

Disney and Carnegie Mellon is redefining Big Data with EM-Sense.

We’ve all grown up hear­ing and expe­ri­enc­ing the “Mag­ic of Dis­ney”, but what does that real­ly mean? Well thanks to their lat­est mag­ic com­pa­nies will know every­thing and we mean every­thing about you, like what you’re hold­ing in your hands at this very moment. No cam­eras, drones, or stalk­ers required, basi­cal­ly just a smart­watch with some cool soft­ware. It’s called EM-Sense, devel­oped by sci­en­tists at Dis­ney Research and Carnegie Mel­lon Uni­ver­si­ty. So the ques­tion you should be ask­ing your­self right now is “What the heck is Dis­ney up to”? It seems like they are get­ting involved in every pos­si­ble piece of tech­nol­o­gy, small, large, sim­ple to super com­plex. But why? Not too long ago we wrote about their aug­ment­ed real­i­ty col­or­ing tech and their appli­ca­tion of Li-Fi. Now they appear to be mov­ing into stranger realms. A research paper was recent­ly pre­sent­ed at a user inter­face soft­ware and tech­nol­o­gy sym­po­sium and it basi­cal­ly explained our bod­ies con­duct elec­tro-mag­net­ic sig­nals and this con­duc­tion can be eas­i­ly mea­sured. It also turns out that objects pro­duce dis­tinc­tive EM sig­nals as well. By using the body as an anten­na and soft­ware to fil­ter the sig­nals, EM-Sense has shown it is pos­si­ble to dis­crim­i­nate reli­ably…

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Will Robots report the News and make Data journalism a thing of the Past?

Will Robots report the News and make Data journalist a thing of the past?

The only con­stant is that jour­nal­ism has to re-invent itself. With tech­no­log­i­cal out­lets ooz­ing into every­day cul­ture, the way we get what’s hap­pen­ing out in the real-world is chang­ing and it appears the new word on the streets is Data Jour­nal­ism. Data is king, and we have become like machines who only acknowl­edge the val­ues of num­bers and sta­tis­tics. More data; less social sci­ence based inves­ti­ga­tions and sto­ry­telling, towards data col­lect­ing, analy­sis and pub­lish­ing based on code, algo­rithms and soft­ware from the com­put­er sci­ences? Don’t wor­ry just yet jour­nal­ism is still all about sto­ry­telling, but the sto­ries are being told from new­er more sci­en­tif­i­cal­ly inte­grat­ed meth­ods. Start-ups are most def­i­nite­ly try­ing to cre­ate a mar­ket posi­tion for data jour­nal­ism. Per­haps in the future coders will be tak­ing over the news­room. It is amaz­ing how quick­ly feeds from drones were imple­ment­ed as a report­ing tool. Right now we have pro­grams that can be instruct­ed to cre­ate rudi­men­ta­ry sto­ries and rewrite them a myr­i­ad num­ber of ways. Arduinos have allowed a num­ber of indi­vid­u­als to cre­ate cus­tom sen­sors that can be applied in the field for sen­­sor-based jour­nal­ism, where you can cat­a­logue real world envi­ron­men­tal data. You can cap­ture any­thing from water…

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