- Personalization (Chris Lehmann) — We should be careful about how we use that term, and we should be very skeptical of how well computerized programs can really personalize for kids. Most of what I see – especially from curriculum and assessment vendors – involves personalization of pace while still maintaining standardization of content. This.
- Unveiling Quadrigram (Near Future Laboratory) — a Visual Programming Environment to gather, shape and share living data. By living data we mean data that are constantly changing and accumulating. They can come from social network, sensor feeds, human activity, surveys, or any kind of operation that produce digital information.
- Tim O’Reilly at MIT Media Lab (Ethan Zuckerman) — a great recap of a Tim talk. There’s an interesting discussion of the unmeasured value created by peer-to-peer activities (such as those made dead simple by the Internet), which is one of the new areas we’re digging into here at O’Reilly.
- The State vs the Internet (David Eaves) — we’ve all seen many ways in which the Internet is undermining the power of nation states. A session at Foo asked how it was going to end (which would give way first?), and this is an excellent recap. It could be that the corporation is actually the entity best positioned to adapt to the internet age. Small enough to leverage networks, big enough to generate a community that is actually loyal and engaged.
A few early and broad questions in our exploration of NYC's startup community.
Since the crisis of 2008 New York City’s massive financial sector — the city’s richest economic engine, once seen to have unlimited potential for growth — has languished. In the meantime, attention has turned to its nascent startup sector, home to Foursquare, Tumblr, 10gen, Etsy and Gilt, where VC investment has surged even as it’s been flat in other big U.S. tech centers (PDF).
I’ve started to poke around the tech community here with a view toward eventually publishing a paper on the rise of New York’s startup scene. In my initial conversations, I’ve come up with a few broad questions I’ll focus on, and I’d welcome thoughts from this blog’s legion of smart readers on any of these.
- How many people in New York’s startup community came from finance, and under what conditions did they make the move? In 2003, Google was a five-year-old, privately-held startup and Bear Stearns was an 80-year-old pillar of the financial sector. Five years later, Google was a pillar of the technical economy and among the world’s biggest companies; Bear Stearns had ceased to exist. Bright quantitatively-minded people who might have pursued finance for its stability and lucre now see that sector as unstable and not necessarily lucrative; its advantage over the technology sector in those respects has disappeared. Joining a 10-person startup is very different from taking a job at Google, but the comparative appeal of the two sectors has dramatically shifted.
- To what degree have anchor institutions played a role in the New York startup scene? The relationship between Stanford University and Silicon Valley is well-documented; I’d like to figure out who’s producing steady streams of bright technologists in New York. Google’s Chelsea office, opened in 2006, now employs close to 3,000 people, and its alumni include Dennis Crowley, founder of Foursquare. That office is now old enough that it can generate a high volume of spin-offs as Googlers look for new challenges. And Columbia and NYU (and soon a Cornell-Technion consortium) have embraced New York’s startup community.
Looking ahead at big data's role in enterprise business intelligence, civil engineering, and customer relationship optimization.
- Everything is on the Internet.
- The Internet has a lot of data.
- Therefore, everything is big data.
When you have a hammer, everything looks like a nail. When you have a Hadoop deployment, everything looks like big data. And if you’re trying to cloak your company in the mantle of a burgeoning industry, big data will do just fine. But seeing big data everywhere is a sure way to hasten the inevitable fall from the peak of high expectations to the trough of disillusionment.
We saw this with cloud computing. From early idealists saying everything would live in a magical, limitless, free data center to today’s pragmatism about virtualization and infrastructure, we soon took off our rose-colored glasses and put on welding goggles so we could actually build stuff.
So where will big data go to grow up?
Once we get over ourselves and start rolling up our sleeves, I think big data will fall into three major buckets: Enterprise BI, Civil Engineering, and Customer Relationship Optimization. This is where we’ll see most IT spending, most government oversight, and most early adoption in the next few years. Read more…
Personalized Education, Programming Living Data, The Invisible Economy, and State vs Internet
Data for the public good, the coming health IT revolution, big data in the cloud.
This week on O'Reilly: Alex Howard examined data's civic role, Dr. Farzad Mostashari discussed health IT and patient empowerment, and Edd Dumbill surveyed big data cloud offerings.
From healthcare to finance to emergency response, data holds immense potential to help citizens and government.
The explosion of big data, open data and social data offers new opportunities to address humanity's biggest challenges. The open question is no longer if data can be used for the public good, but how.
City Finances, Low-Power Computers, Future History, and Learner's Mindset
- California and Bust (Vanity Fair) — Michael Lewis digs into city and state finances, and the news ain’t good.
- Tonido Plug 2 — with only watts a day, you could have your own low-cost compute farm that runs off a car battery and a cheap solar panel.
- William Gibson Interview (The Paris Review) — It’s harder to imagine the past that went away than it is to imagine the future. What we were prior to our latest batch of technology is, in a way, unknowable. It would be harder to accurately imagine what New York City was like the day before the advent of broadcast television than to imagine what it will be like after life-size broadcast holography comes online. But actually the New York without the television is more mysterious, because we’ve already been there and nobody paid any attention. That world is gone.
- Zen and the Art of Making (Phil Torrone) — thoughts on the difference between beginners and experts, and why the beginner’s mindset is intoxicating and addictive.
IBM taps the cloud to make Hadoop easier, Factual cleans geo data, Google gets transparent with gov data requests.
IBM targets businesses with a cloud-based Hadoop product, Factual tackles incomplete geo records, and Google embraces transparency by publishing and explaining the data requests it gets from governments.
Tech predictions focusing only on technology miss a key component: people.
If you comment on new technology, you should get to know as many of the quirks and biases of human behavior as you can. That's because you're modeling people first and technology second.
To live and die making "L.A. Noire," unsensible censors, and the top 25 ways to get PWNED
The folks who make video games sound the alarm bells on working conditions, governments try to break the Internet, and MITRE unveils 2011's most dangerous software errors.
Ebay buys Where, the White House wants identity protection, and researchers find interesting data about themselves on the iPhone.
EBay's purchase of a mobile advertising and check-in service adds another piece to its mobile payment puzzle. Also, the White House calls for an online identity ecosystem and two researchers discover caches of location data left unencrypted on their iPhones.