"ai" entries

Four short links: 27 February 2015

Four short links: 27 February 2015

No Estimates, Brand Advertising, Artificial Intelligence, and GPG BeGone

  1. #NoEstimatesAllspaw also points out that the yearning to break the bonds of estimation is nothing new — he’s fond of quoting a passage from The Unwritten Laws of Engineering, a 1944 manual which says that engineers “habitually try to dodge the irksome responsibility for making commitments.” All of Allspaw’s segment is genius.
  2. Old Fashioned Snapchatget a few drinks in any brand advertiser and they’ll admit that the number one reason they know that brand advertising works is that, if they stop, sales inevitably drop.
  3. Q&A With Bruce Sterling on Artificial Intelligence — in which Sterling sounds intelligent, and the questioner sounds Artificial.
  4. GPG and Me (Moxie Marlinspike) — Even though GPG has been around for almost 20 years, there are only ~50,000 keys in the “strong set,” and less than 4 million keys have ever been published to the SKS keyserver pool ever. By today’s standards, that’s a shockingly small user base for a month of activity, much less 20 years. This was a great talk at Webstock this year.
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Four short links: 20 February 2015

Four short links: 20 February 2015

Robotic Garden, Kids Toys, MSFT ML, and Twitter Scale

  1. The Distributed Robotic Garden (MIT) — We consider plants, pots, and robots to be systems with different levels of mobility, sensing, actuation, and autonomy. (via Robohub)
  2. CogniToys Leverages Watson’s Brain to Befriend, Teach Your Kids (IEEE) — Through the dino, Watson’s algorithms can get to know each child that it interacts with, tailoring those interactions to the child’s age and interests.
  3. How Machine Learning Ate Microsoft (Infoworld) — Azure ML didn’t merely take the machine learning algorithms MSR had already handed over to product teams and stick them into a drag-and-drop visual designer. Microsoft has made the functionality available to developers who know the R statistical programming language and Python, which together are widely used in academic machine learning. Microsoft plans to integrate Azure ML closely with Revolution Analytics, the R startup it recently acquired.
  4. Handling Five Billion Sessions a Day in Real Time (Twitter) — infrastructure porn.
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Four short links: 19 January 2015

Four short links: 19 January 2015

Going Offline, AI Ethics, Human Risks, and Deep Learning

  1. Reset (Rowan Simpson) — It was a bit chilling to go back over a whole years worth of tweets and discover how many of them were just junk. Visiting the water cooler is fine, but somebody who spends all day there has no right to talk of being full.
  2. Google’s AI Brain — on the subject of Google’s AI ethics committee … Q: Will you eventually release the names? A: Potentially. That’s something also to be discussed. Q: Transparency is important in this too. A: Sure, sure. Such reassuring.
  3. AVA is now Open Source (Laura Bell) — Assessment, Visualization and Analysis of human organisational information security risk. AVA maps the realities of your organisation, its structures and behaviors. This map of people and interconnected entities can then be tested using a unique suite of customisable, on-demand, and scheduled information security awareness tests.
  4. Deep Learning for Torch (Facebook) — Facebook AI Research open sources faster deep learning modules for Torch, a scientific computing framework with wide support for machine learning algorithms.
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Four short links: 9 January 2015

Four short links: 9 January 2015

Complex Addresses, AI Applications, Scaling Diversity, Audiovisual Coding

  1. Falsehoods Programmers Believe About Addresses0 Egmont Road, Middlesbrough. lolwut?
  2. Future of the AI-Powered Application (Matt Turck) — we’re about to witness the emergence of a number of deeply focused AI-powered applications that will achieve commercial success by solving in a definitive manner very specific issues. (via Matt Webb)
  3. Three Things a City In Charge of its Destiny Ought to Know About Software (Matt Edgar) — Instead of asking “will it scale”, ask a better question: “Does it gracefully handle massive diversity?” […] The diversity question accommodates scaling; the scaling question tramples all over diversity. (via Tom Armitage)
  4. gibbera creative coding environment for audiovisual performance and composition. It contains features for audio synthesis and musical sequencing, 2d drawing, 3d scene construction and manipulation, and live-coding shaders. If you’re looking for more ways to interest teens in code …
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Four short links: 25 December 2015

Four short links: 25 December 2015

Smart Cities, Blockchain Innovation, Brain Interfaces, and Knowledge Graphs

  1. Smartest Cities Rely on Citizen Cunning and Unglamorous Technology (The Guardian) — vendors like Microsoft, IBM, Siemens, Cisco and Hitachi construct the resident of the smart city as someone without agency; merely a passive consumer of municipal services – at best, perhaps, a generator of data that can later be aggregated, mined for relevant inference, and acted upon. Should he or she attempt to practise democracy in any form that spills on to the public way, the smart city has no way of accounting for this activity other than interpreting it as an untoward disruption to the orderly flow of circulation.
  2. Second Wave of Blockchain Innovation — the economic challenges of innovating on the blockchain.
  3. Introduction to the Modern Brain-Computer Interface Design (UCSD) — The lectures were first given by Christian Kothe (SCCN/UCSD) in 2012 at University of Osnabrueck within the Cognitive Science curriculum and have now been recorded in the form of an open online course. The course includes basics of EEG, BCI, signal processing, machine learning, and also contains tutorials on using BCILAB and the lab streaming layer software.
  4. Machine Learning with Knowledge Graphs (video) — see also extra readings.
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Four short links: 15 December 2014

Four short links: 15 December 2014

Transferable Learning, At-Scale Telemetry, Ugly DRM, and Fast Packet Processing

  1. How Transferable Are Features in Deep Neural Networks? — (answer: “very”). A final surprising result is that initializing a network with transferred features from almost any number of layers can produce a boost to generalization that lingers even after fine-tuning to the target dataset. (via Pete Warden)
  2. Introducing Atlas: Netflix’s Primary Telemetry Platform — nice solution to the problems that many have, at a scale that few have.
  3. The Many Facades of DRM (PDF) — Modular software systems are designed to be broken into independent pieces. Each piece has a clear boundary and well-defined interface for ‘hooking’ into other pieces. Progress in most technologies accelerates once systems have achieved this state. But clear boundaries and well-defined interfaces also make a technology easier to attack, break, and reverse-engineer. Well-designed DRMs have very fuzzy boundaries and are designed to have very non-standard interfaces. The examples of the uglified DRM code are inspiring.
  4. DPDKa set of libraries and drivers for fast packet processing […] to: receive and send packets within the minimum number of CPU cycles (usually less than 80 cycles); develop fast packet capture algorithms (tcpdump-like); run third-party fast path stacks.
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Four short links: 18 November 2014

Four short links: 18 November 2014

A Worm Mind Forever LEGO Voyaging, Automatic Caption Generator, ELK Stack, and Amazonian Deployment

  1. A Worm’s Mind in a Lego Body — the c. elegans worm’s 302 neurons has been sequenced, modelled in open source code, and now hooked up to a Lego robot. It is claimed that the robot behaved in ways that are similar to observed C. elegans. Stimulation of the nose stopped forward motion. Touching the anterior and posterior touch sensors made the robot move forward and back accordingly. Stimulating the food sensor made the robot move forward. There is video.
  2. Show and Tell: A Neural Image Caption Generator — Google Research paper on generating captions like “Two pizzas sitting on top of a stove top oven” from a photo. Wow.
  3. Big Data with the ELK Stack — ElasticSearch, logstash, and Kibana. Interesting and powerful combination of tools!
  4. Apollo: Amazon’s Deployment EngineApollo will stripe the rolling update to simultaneously deploy to an equivalent number of hosts in each location. This keeps the fleet balanced and maximizes redundancy in the case of any unexpected events. When the fleet scales up to handle higher load, Apollo automatically installs the latest version of the software on the newly added hosts. Lust.
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Four short links: 6 November 2014

Four short links: 6 November 2014

Javascript Testing, Dark Data, Webapp Design, and Design Trumps Data

  1. Karma — kick-ass open source Javascript test environment.
  2. The Dark Market for Personal Data (NYTimes) — can buy lists of victims of sexual assault, of impulse buyers, of people with sexually transmitted disease, etc. The cost of a false-positive when those lists are used for marketing is less than the cost of false-positive when banks use the lists to decide whether you’re a credit risk. The lists fall between the cracks in privacy legislation; essentially, the compilation and use of lists of people are unregulated territory.
  3. 7 Principles of Rich Web Applications — “rich web applications” sounds like 2007 wants its ideas back, but the content is modern and useful. Predict behaviour for negative latency.
  4. Collaborative Filtering at LinkedIn (PDF) — This paper presents LinkedIn’s horizontal collaborative filtering infrastructure, known as browsemaps. Great lessons learned, including context and presentation of browsemaps or any recommendation is paramount for a truly relevant user experience. That is, design and presentation represents the largest ROI, with data engineering being a second, and algorithms last. (via Greg Linden)
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Four short links: 30 September 2014

Four short links: 30 September 2014

Continuous Testing, Programmable Bees, Deep Learning on GPUs, and Silk Road Numbers

  1. Continuously Testing Infrastructure — “infrastructure as code”. I can’t figure out whether what I feel are thrills or chills.
  2. Engineer Sees Big Possibilities in Micro-robots, Including Programmable Bees (National Geographic) — He and fellow researchers devised novel techniques to fabricate, assemble, and manufacture the miniature machines, each with a housefly-size thorax, three-centimeter (1.2-inch) wingspan, and weight of just 80 milligrams (.0028 ounces). The latest prototype rises on a thread-thin tether, flaps its wings 120 times a second, hovers, and flies along preprogrammed paths. (via BoingBoing)
  3. cuDNN — NVIDIA’s library of primitives for deep neural networks (on GPUS, natch). Not open source (registerware).
  4. Analysing Trends in Silk Road 2.0If, indeed every sale can map to a transaction, some vendors are doing huge amounts of business through mail order drugs. While the number is small, if we sum up all the product reviews x product prices, we get a huge number of USD $20,668,330.05. REMEMBER! This is on Silk Road 2.0 with a very small subset of their entire inventory. A peek into a largely invisible economy.
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Four short links: 26 September 2014

Four short links: 26 September 2014

Good Communities, AI Games, Design Process, and Web Server Library

  1. 15 Lessons from 15 Years of Blogging (Anil Dash) — If your comments are full of assholes, it’s your fault. Good communities don’t just happen by accident.
  2. Replicating DeepMind — open source attempt to build deep learning network that can play Atari games. (via RoboHub)
  3. ToyTalk — fantastic iterative design process for the product (see the heading “A Bit of Trickery”)
  4. h2oan optimized HTTP server implementation that can be used either as a standalone server or a library.
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