"cs" entries

Four short links: 3 February 2015

Four short links: 3 February 2015

Product Trends, Writing Code, Simple Testing, and Quantum Gotchas

  1. Frog Design Predictions (Wired) — designers pick product trends, arrayed from probable to speculative.
  2. Making Wrong Code Look Wrong (Joel Spolsky) — This makes mistakes even more visible. Your eyes will learn to “see” smelly code, and this will help you find obscure security bugs just through the normal process of writing code and reading code.
  3. Simple Testing Can Prevent Most Critical FailuresWe found the majority of catastrophic failures could easily have been prevented by performing simple testing on error handling code – the last line of defense – even without an understanding of the software design. We extracted three simple rules from the bugs that have lead to some of the catastrophic failures, and developed a static [Java] checker, Aspirator, capable of locating these bugs. One of the tests is a FIXME or TODO in an exception handler.
  4. Quantum Machine Learning Algorithms: Read the Fine Print (Scott Aaronson) — In the years since HHL, quantum algorithms achieving “exponential speedups over classical algorithms” have been proposed for other major application areas […]. With each of them, one faces the problem of how to load a large amount of classical data into a quantum computer (or else compute the data “on-the-fly”), in a way that is efficient enough to preserve the quantum speedup.
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Four short links: 2 February 2015

Four short links: 2 February 2015

Weather Forecasting, Better Topic Modelling, Cyberdefense, and Facebook Warriors

  1. Global Forecast System — National Weather Service open sources its weather forecasting software. Hope you have a supercomputer and all the data to make use of it …
  2. High-reproducibility and high-accuracy method for automated topic classificationLatent Dirichlet allocation (LDA) is the state of the art in topic modeling. Here, we perform a systematic theoretical and numerical analysis that demonstrates that current optimization techniques for LDA often yield results that are not accurate in inferring the most suitable model parameters. Adapting approaches from community detection in networks, we propose a new algorithm that displays high reproducibility and high accuracy and also has high computational efficiency. We apply it to a large set of documents in the English Wikipedia and reveal its hierarchical structure.
  3. Army Open Sources Cyberdefense Codegit push is the new “for immediate release”.
  4. British Army Creates Team of Facebook Warriors (The Guardian) — no matter how much I know the arguments for it, it still feels vile.
Comment: 1
Four short links: 30 January 2015

Four short links: 30 January 2015

FAA Rules, Sports UAVs, Woodcut Data, and Concurrent Programming

  1. FAA to Regulate UAVs? (Forbes) — and the Executive Order will segment the privacy issues related to drones into two categories — public and private. For public drones (that is, drones purchased with federal dollars), the President’s order will establish a series of privacy and transparency guidelines. See also How ESPN is Shooting the X Games with Drones (Popular Mechanics)—it’s all fun and games until someone puts out their eye with a quadrocopter. The tough part will be keeping within the tight restrictions the FAA gave them. Because drones can’t be flown above a crowd, Calcinari says, “We basically had to build a 500-foot radius around them, where the public can’t go.” The drones will fly over sections of the course that are away from the crowds, where only ESPN production employees will be. That rule is part of why we haven’t seen drones at college football games.
  2. Milestones for SaaS Companies“Getting from $0-1m is impossible. Getting from $1-10m is unlikely. And getting from $10-100m is inevitable.” —Jason Lemkin, ex-CEO of Echosign. The article proposes some significant milestones, and they ring true. Making money is generally hard. The nature of the hard changes with the amount of money you have and the amount you’re trying to make, but if it were easy, then we’d structure our society on something else.
  3. Woodcut Data VisualisationRecently, I learned how to operate a laser cutter. It’s been a whole lot of fun, and I wanted to share my experiences creating woodcut data visualizations using just D3. I love it when data visualisations break out of the glass rectangle.
  4. Why is Concurrent Programming Hard?on the one hand there is not a single concurrency abstraction that fits all problems, and on the other hand the various different abstractions are rarely designed to be used in combination with each other. We are due for a revolution in programming, something to help us make sense of the modern systems made of more moving parts than our feeble grey matter can model and intuit about.
Comment: 1
Four short links: 13 January 2015

Four short links: 13 January 2015

Slack Culture, Visualizations of Text Analysis, Wearables and Big Data, and Snooping on Keyboards

  1. Building the Workplace We Want (Slack) — culture is the manifestation of what your company values. What you reward, who you hire, how work is done, how decisions are made — all of these things are representations of the things you value and the culture you’ve wittingly or unwittingly created. Nice (in the sense of small, elegant) explanation of what they value at Slack.
  2. Interpretation and Trust: Designing Model-Driven Visualizations for Text Analysis (PDF) — Based on our experiences and a literature review, we distill a set of design recommendations and describe how they promote interpretable and trustworthy visual analysis tools.
  3. The Internet of Things Has Four Big Data Problems (Alistair Croll) — What the IoT needs is data. Big data and the IoT are two sides of the same coin. The IoT collects data from myriad sensors; that data is classified, organized, and used to make automated decisions; and the IoT, in turn, acts on it. It’s precisely this ever-accelerating feedback loop that makes the coin as a whole so compelling. Nowhere are the IoT’s data problems more obvious than with that darling of the connected tomorrow known as the wearable. Yet, few people seem to want to discuss these problems.
  4. Keysweepera stealthy Arduino-based device, camouflaged as a functioning USB wall charger, that wirelessly and passively sniffs, decrypts, logs, and reports back (over GSM) all keystrokes from any Microsoft wireless keyboard in the vicinity. Designs and demo videos included.
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Four short links: 12 January 2015

Four short links: 12 January 2015

Designed-In Outrage, Continuous Data Processing, Lisp Processors, and Anomaly Detection

  1. The Toxoplasma of RageIt’s in activists’ interests to destroy their own causes by focusing on the most controversial cases and principles, the ones that muddy the waters and make people oppose them out of spite. And it’s in the media’s interest to help them and egg them on.
  2. Samza: LinkedIn’s Stream-Processing EngineSamza’s goal is to provide a lightweight framework for continuous data processing. Unlike batch processing systems such as Hadoop, which typically has high-latency responses (sometimes hours), Samza continuously computes results as data arrives, which makes sub-second response times possible.
  3. Design of LISP-Based Processors (PDF) — 1979 MIT AI Lab memo on design of hardware specifically for Lisp. Legendary subtitle! LAMBDA: The Ultimate Opcode.
  4. rAnomalyDetection — Twitter’s R package for detecting anomalies in time-series data. (via Twitter Engineering blog)
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Four short links: 7 January 2015

Four short links: 7 January 2015

Program Synthesis, Data Culture, Metrics, and Information Biology

  1. Program Synthesis ExplainedThe promise of program synthesis is that programmers can stop telling computers how to do things, and focus instead on telling them what they want to do. Inductive program synthesis tackles this problem with fairly vague specifications and, although many of the algorithms seem intractable, in practice they work remarkably well.
  2. Creating a Data-Driven Culture — new (free!) ebook from Hilary Mason and DJ Patil. The editor of that team is the luckiest human being alive.
  3. Ev Williams on Metrics — a master-class in how to think about and measure what matters. If what you care about — or are trying to report on — is impact on the world, it all gets very slippery. You’re not measuring a rectangle, you’re measuring a multi-dimensional space. You have to accept that things are very imperfectly measured and just try to learn as much as you can from multiple metrics and anecdotes.
  4. Nature, the IT Wizard (Nautilus) — a fun walk through the connections between information theory, computation, and biology.
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Four short links: 2 January 2015

Four short links: 2 January 2015

Privacy Philosophy, Bitcoin Risks, Modelling Emotion, and Opinion Formation

  1. Google’s Philosopher — interesting take on privacy. Now that the mining and manipulation of personal information has spread to almost all aspects of life, for instance, one of the most common such questions is, “Who owns your data?” According to Floridi, it’s a misguided query. Your personal information, he argues, should be considered as much a part of you as, say, your left arm. “Anything done to your information,” he has written, “is done to you, not to your belongings.” Identity theft and invasions of privacy thus become more akin to kidnapping than stealing or trespassing. Informational privacy is “a fundamental and inalienable right,” he argues, one that can’t be overridden by concerns about national security, say, or public safety. “Any society (even a utopian one) in which no informational privacy is possible,” he has written, “is one in which no personal identity can be maintained.”
  2. S-1 for a Bitcoin Trust (SEC) — always interesting to read through the risks list to see what’s there and what’s not.
  3. Computationally Modelling Human Emotion (ACM) — our work seeks to create true synergies between computational and psychological approaches to understanding emotion. We are not satisfied simply to show our models “fit” human data but rather seek to show they are generative in the sense of producing new insights or novel predictions that can inform understanding. From this perspective, computational models are simply theories, albeit more concrete ones that afford a level of hypothesis generation and experimentation difficult to achieve through traditional theories.
  4. Opinion Formation Models on a Gradient (PLoSONE) — Many opinion formation models embedded in two-dimensional space have only one stable solution, namely complete consensus, in particular when they implement deterministic rules. In reality, however, deterministic social behavior and perfect agreement are rare – at least one small village of indomitable Gauls always holds out against the Romans. […] In this article we tackle the open question: can opinion dynamics, with or without a stochastic element, fundamentally alter percolation properties such as the clusters’ fractal dimensions or the cluster size distribution? We show that in many cases we retrieve the scaling laws of independent percolation. Moreover, we also give one example where a slight change of the dynamic rules leads to a radically different scaling behavior.
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Four short links: 24 December 2014

Four short links: 24 December 2014

DRMed Objects, Eventual Consistency, Complex Systems, and Machine Learning Papers

  1. DRMed Cat Litter Box — the future is when you don’t own what you buy, and it’s illegal to make it work better. (via BoingBoing)
  2. Are We Consistent Yet? — the eventuality of consistency on different cloud platforms.
  3. How Complex Systems Fail (YouTube) — Richard Cook’s Velocity 2012 keynote.
  4. Interesting papers from NIPS 2014 — machine learning holiday reading.
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Four short links: 13 November 2014

Four short links: 13 November 2014

Material Design, GitHub Communication, Priority Queues, and DevOps Learnings

  1. Materialize — another web implementation of Material Design.
  2. Communicating at Github — interesting take on making visible and optimising for the conversations and decisions that form culture but are otherwise invisible.
  3. MultiQueues — an approach for parallel access to priority queues.
  4. Devops LearningsWe view DevOps as the missing components of agile – the enabler for getting it out of the door and closing the loop between software engineer and customer.
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Four short links: 22 October 2014

Four short links: 22 October 2014

Docker Patterns, Better Research, Streaming Framework, and Data Science Textbook

  1. Eight Docker Development Patterns (Vidar Hokstad) — patterns for creating repeatable builds that result in as-static-as-possible server environments.
  2. How to Make More Published Research True (PLOSmedicine) — overview of efforts, and research on those efforts, to raise the proportion of published research which is true.
  3. Gearpump — Intel’s “actor-driven streaming framework”, initial benchmarks shows that we can process 2 million messages/second (100 bytes per message) with latency around 30ms on a cluster of 4 nodes.
  4. Foundations of Data Science (PDF) — These notes are a first draft of a book being written by Hopcroft and Kannan [of Microsoft Research] and in many places are incomplete. However, the notes are in good enough shape to prepare lectures for a modern theoretical course in computer science.
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