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Steven Cherry
Works at IEEE Spectrum
Attended The New School
Lives in New York, N.Y.
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Steven Cherry

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Today, there are by one count 6 billion USB devices in the world, and not just printers and keyboards and mice. There’s a USB butt cooler for your chair, USB heated gloves for your hands, and a USB disco ball for your inner John Travolta. Ajay Bhatt wasn’t kidding when he envisioned a universal serial bus port.

Ajay Bhatt hasn’t stood still, and neither has USB. There’s a USB 2.0 and 3.0, and Bhatt has worked on the Accelerated Graphics Port and PCI Express. He’s worked on Intel’s desktop power-management architecture and is now helping to develop a computer that will work all day.

A Techwise Conversation with Ajay Bhatt, co-inventor of USB
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Steven Cherry

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Telecommuting, Serendipity, and Innovation
Does proximity spur collaboration? A new study finds it does

"So I think the real challenge for an organization is to decide whether they want to create a space that will facilitate, that will raise, the transactional frictions within the established groups in order to enable greater contact between established groups, or whether they will try to create a space that will allow established groups to more efficiently go about their collaborative work. Those two things are likely to be trade-offs that come through the same physical arrangement of space."

A Techwise Conversation with  Jason Owen-Smith, associate professor of sociology and organizational studies at the University of Michigan and coauthor of a new paper, “Zone Overlap and Collaboration in Academic Biomedicine.”
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".... breaking down the news into what we call “atomic units of news,” and it’s a quote, a fact, a stat, or an event, or an image. But the other thing is that in breaking down the news in that way, we’re actually saying, “These are the elements of news,” and we thread them together to tell that story. And that thread can evolve over time as new facts or new information comes to light."

A Techwise Conversation with David Cohn, founding editor of Circa, whose company motto is, "“We don’t write articles, we create story lines.”
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This is a good piece. I really enjoyed listening to the vision.

Now if I could just get an approximate date for the Android launch, myself & the other Billion Android users could join in.

Thank you Steven. 
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"There’s a lot of technologies out there right now that are being introduced into the retail space to understand what consumers are doing in the store, and heat-mapping is one of those technologies—using cameras in the ceiling to actually track where the consumer’s going. What this information tells the retailer is where a consumer is, how they’re moving around the store, whether they’re dwelling in certain places, like checkout or in front of specific merchandise. 

"There’s both the real-time application for this technology as well as a longer-term application. And so, as you’re deciding how many people should be in the store manning the registers the next week, you can actually use this information as well.

"You’re seeing retailers are being more innovative than I think historically they’ve been given credit. And IT organizations are really starting to be innovators in technology."

A Techwise Conversation with Kurt Kendall, a partner and director at Kurt Salmon, where he heads the analytics practice there.
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Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics. Other institutions teaching data science [JPEG] include New York University, Stanford, Northwestern, George Mason, Syracuse, UC Irvine, and Indiana University.

A Techwise Conversation with Chris Wiggins, a professor of applied mathematics at Columbia University, who walks us through what’s old and new in the academic field of data science. 
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Your podcast is new for me, and it's been like finding Gold in my own backyard/back pocket. Thank you Steven!

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Steven Cherry

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Steven Cherry: A key notion in your argument is that of a siren server. The Greek Sirens were half-women island demigods who lured sailors and their ships onto rocky shores with their beautiful voices and songs. In your mythology, the siren servers are Facebook, Google, Apple, and their ilk, and I guess the ship is our economy and we’re the sailors. Your argument starts by distinguishing bell curve network distributions from power law ones, which you call “winner take all.” Maybe let’s start there.

Jaron Lanier: Okay, sure.... The economics of richly connected networks is such that only the central server makes money, and then the people don’t pay each other. That’s treated as free information.

Some other great examples to me are the free systems of Linux or the Wikipedia, which are supported by people who do think information should be free, which is a view I used to have but no longer do. But if you look at all the people who contribute to a big Wikipedia article or to, say, the Linux stack, what you see is a remarkably broad range. You do see some people who contribute a lot more than others, but you see a big hump in the middle of people who contribute a fair amount. And so there, once again, is this middle-class distribution showing up; it’s just in a nonmonetized way.
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"These mass central feeding operations, they are just simply too big—thousands, tens of thousands of animals, and they are so efficient, basically. In the case of chickens, really, they have hardly any room to move. And then because of the proximity of these animals, you have to feed them preventive antibiotics, because once one chicken would get sick, then you have 80 000 sick chickens.

"So it’s simply the scale is too large, but, of course, it has driven prices so low, so it’s now massively affordable. But there are quite a few new steps being taken, which show that you don’t have to at that scale, and you don’t have to put so many chemicals into it. So we can do better. The model is here to stay. We have to produce meat in large quantities. The mom-and-pop operations cannot satisfy mass markets, but it could be done better."

A Techwise Conversation with Vaclav Smil, a distinguished professor emeritus of the University of Manitoba and the author of 30 books, including Should We Eat Meat? (Wiley, 2013)
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"We have to think in terms of the robot plus person working as a cooperative pair, and the ways in which the split of responsibility in doing any particular task, let’s say making breakfast, how that’s going to occur, how that might be defined by the person.

"For example, the person might want to do all of the actual cooking but would like the robot to retrieve all the ingredients. That might be somebody who has some mobility impairment, could even be arthritis, and they don’t move around as fast, and so how they would interact would be very different.

"So you could imagine that if the person needs help lifting something, then the robot cooperating to provide the extra physical force to lift that frying pan, for example, provides a much different type of a challenge than just a split of responsibilities—'You do this, I do that.' "

A Techwise Conversation with Jim Osborn, executive director of the Robotics Institute’s Quality of Life Technology Center at Carnegie Mellon University.
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 As it turns out, there’s a fair amount of data out there and—like baseball—when you look at it with a statistician’s eye, you get all sorts of clues that will help you win games. I mean, cases. Won/lost  stats for litigators are just the starting point. What if you knew which judges were most likely to grant which specific motions? Which opposing law firms offer big settlements, but only in certain types of cases? Or what impact the flu season—or the hunting season—has on juries?

A Techwise Conversation with Andrew Winship, attorney and founder of Juristat, a St. Louis–based start-up that’s doing the Moneyball thing for court jurisdictions all over the country.
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"The real issue is semantics. So the way that a search engine gets its power is it can find words on pages and how they correlate with each other. So if I see the word tank, and somewhere else near it on the page is the word fish, I get one concept, whereas if it’s the word tank and somewhere near it is soldier or army, I get a different concept.

"Problem is, if I’m looking at a data set and see a number 13, and somewhere near it is the number 27, and then some other data set 13, and the number near it is 1026, are they the same? Are they different? If I know that those numbers represent class numbers or identifiers of people or ages, then suddenly I start to understand a little bit about whether these are linked together. We use the term linked data nowadays for a lot of this.
"So the question is, can Watson take advantage of the linked data, the unstructured descriptions?"

A Techwise Conversation with Jim Hendler, a professor of computer science and cognitive science at Rensselaer Polytechnic Institute, in Troy, N.Y., and a key researcher in the related fields of knowledge discovery, software agents, and the the Semantic Web.
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Have him in circles
758 people
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Work
Occupation
Writer, editor, teacher of writing and editing
Employment
  • IEEE Spectrum
    Senior Associate Editor, 1998 - present
  • ACM
    Executive Editor, Magazines, 1994 - 1998
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New York, N.Y.
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Journalist, writer, professor, husband, father, friend, rock climber......
Education
  • The New School
    M.F.A., Creative Writing
  • State University of New York at Geneseo
    B.A., Mathematics, Philosophy
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Male
Birthday
December 18
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Married