FEATURED STORY

Now available: Big Data Now, 2014 edition

Our wrap-up of important developments in the big data field.

In the four years we’ve been producing Big Data Now, our year-end wrap-up of important developments in the big data field, we’ve seen tools and applications mature, multiply, and coalesce into new categories. This year’s free wrap-up of Radar coverage is organized around seven themes:

  • Cognitive augmentation: As data processing and data analytics become more accessible, jobs that can be automated will go away. But to be clear, there are still many tasks where the combination of humans and machines produce superior results.
  • Intelligence matters: Artificial intelligence is now playing a bigger and bigger role in everyone’s lives, from sorting our email to rerouting our morning commutes, from detecting fraud in financial markets to predicting dangerous chemical spills. The computing power and algorithmic building blocks to put AI to work have never been more accessible.
  • Read more…

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Four short links: 26 January 2015

Four short links: 26 January 2015

Coding in VR, Git Workflows, Programming as Bookkeeping, and Valuing People

  1. How Might We Code in VR? — caught my eye because I’m looking for ideas on how to think about interaction design in the holoculus world.
  2. Git Workflows for Pros — non-developers don’t understand how important this is to productivity.
  3. All Programming is Bookkeeping — approach programming as a bookkeeping problem: checks and balances.
  4. Why I Am Not a Maker (Deb Chachra) — The problem is the idea that the alternative to making is usually not doing nothing—it’s almost always doing things for and with other people, from the barista to the Facebook community moderator to the social worker to the surgeon. Describing oneself as a maker—regardless of what one actually or mostly does—is a way of accruing to oneself the gendered, capitalist benefits of being a person who makes products.
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Designing on a system level

Andy Goodman on service design, embeddables, and predictive analytics.

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I recently sat down with Andy Goodman, designer and group director of Fjord’s US studios. Goodman has been designing and managing design teams around the globe for the past 20 years. Goodman is a contributor to Designing for Emerging Technologies — our conversation covers embeddables, wearables, and predictive analytics. To kick off the conversation, I asked Goodman to define “service design”:

“It’s well-known that if you ask a service designer to define “service design,” you get 10 different answers. For me, it’s really about thinking on a system level about design … It’s thinking about how systems, and not just computer systems, but how human systems and computer systems and physical systems all interact with each other. You need to be thinking not about individual moments; you need to be thinking about journeys and flows, and thinking about how a human being will naturally, without even thinking about it, move from one context to another using different devices, using physical objects, being in physical spaces. For me, it was very appealing, this idea that you can design more than just interactions in a way, more than just interactions on a screen. You can actually design other things that are more about the way we live and work and play.”

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Bitcoin is just the first app to use blockchain technology

Understanding the value of the blockchain above and beyond bitcoin.

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Editor’s note: Lorne Lantz is a program co-chair for our O’Reilly Radar Summit: Bitcoin & the Blockchain on January 27, 2015, in San Francisco. For more on the program and for registration information, visit the Bitcoin & the Blockchain event website.

I remember the first time I heard about bitcoin. It was June 2012, and I was invited to a bitcoin meetup. The whole time I was sitting there, I thought these were a bunch of computer geeks playing around with nerd money.

At the same time, I felt excited about the possibilities. If what the bitcoin believers were saying was true, it could become something very big. When I took a closer look, I realized why it could be so groundbreaking: decentralization.

Unlike other currencies and payment networks, bitcoin is not controlled by a bank, government, or financial institution. Instead, thousands of computers around the world verify transactions and manage a global decentralized ledger. This innovative technology is called the blockchain, and it provides a unique pathway that allows — for the first time — many computers that don’t trust each other to achieve consensus. In bitcoin’s case, they are achieving consensus on updates to the global ledger. Read more…

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Blockchain scalability

A look at the stumbling blocks to blockchain scalability and some high-level technical solutions.

Author note: Vitalik Buterin contributed to this article.

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Editor’s note: Kieren James-Lubin is a program co-chair for our O’Reilly Radar Summit: Bitcoin & the Blockchain on January 27, 2015, in San Francisco. For more on the program and for registration information, visit the Bitcoin & the Blockchain event website.

In a talk at CoinJar last fall, well-known bitcoin expert Andreas Antonopoulos made the following comment:

“I have no worries that bitcoin can scale, and the simple reason for that is that I know that IPv4 can’t, and yet I use it every day.”

The issue of bitcoin scalability and the phrase “blockchain scalability” are often seen in technical discussions of the bitcoin protocol. Will the requirements of recording every bitcoin transaction in the blockchain compromise its security (because fewer users will keep a copy of the whole blockchain) or its ability to handle a great number of transactions (because new blocks on which transactions can be recorded are only produced at limited intervals)? In this article, we’ll explore several meanings of “blockchain scalability” and some high-level technical solutions to the issue.

The three main stumbling blocks to blockchain scalability are:

  1. The tendency toward centralization with a growing blockchain: the larger the blockchain grows, the larger the requirements become for storage, bandwidth, and computational power that must be spent by “full nodes” in the network, leading to a risk of much higher centralization if the blockchain becomes large enough that only a few nodes are able to process a block.
  2. The bitcoin-specific issue that the blockchain has a built-in hard limit of 1 megabyte per block (about 10 minutes), and removing this limit requires a “hard fork” (ie. backward-incompatible change) to the bitcoin protocol.
  3. The high processing fees currently paid for bitcoin transactions, and the potential for those fees to increase as the network grows. We won’t discuss this too much, but see here for more detail.

We’ll consider these first two issues in detail. Read more…

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Bringing an end to synthetic biology’s semantic debate

The O'Reilly Radar Podcast: Tim Gardner on the synthetic biology landscape, lab automation, and the problem of reproducibility.

Editor’s note: this podcast is part of our investigation into synthetic biology and bioengineering. For more on these topics, download a free copy of the new edition of BioCoder, our quarterly publication covering the biological revolution. Free downloads for all past editions are also available.

Tim Gardner, founder of Riffyn, has recently been working with the Synthetic Biology Working Group of the European Commission Scientific Committees to define synthetic biology, assess the risk assessment methodologies, and then describe research areas. I caught up with Gardner for this Radar Podcast episode to talk about the synthetic biology landscape and issues in research and experimentation that he’s addressing at Riffyn.

Defining synthetic biology

Among the areas of investigation discussed at the EU’s Synthetic Biology Working Group was defining synthetic biology. The official definition reads: “SynBio is the application of science, technology and engineering to facilitate and accelerate the design, manufacture and/or modification of genetic materials in living organisms.” Gardner talked about the significance of the definition:

“The operative part there is the ‘design, manufacture, modification of genetic materials in living organisms.’ Biotechnologies that don’t involve genetic manipulation would not be considered synthetic biology, and more or less anything else that is manipulating genetic materials in living organisms is included. That’s important because it gets rid of this semantic debate of, ‘this is synthetic biology, that’s synthetic biology, this isn’t, that’s not,’ that often crops up when you have, say, a protein engineer talking to someone else who is working on gene circuits, and someone will claim the protein engineer is not a synthetic biologist because they’re not working with parts libraries or modularity or whatnot, and the boundaries between the two are almost indistinguishable from a practical standpoint. We’ve wrapped it all together and said, ‘It basically advances in the capabilities of genetic engineering. That’s what synthetic biology is.'”

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