"research" 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.
Comment
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: 20 January 2015

Four short links: 20 January 2015

Govt IoT, Collective Intelligence, Unknown Excellence, and Questioning Scalability

  1. Matt Webb Joining British Govt Data Service — working on IoT for them.
  2. Reading the Mind in the Eyes or Reading between the Lines? Theory of Mind Predicts Collective Intelligence (PLoS) — theory of mind abilities are a significant determinant of group collective intelligence even when, as in many online groups, the group has extremely limited communication channels. Phone/Skype calls, emails, and chats are all intensely mental activities, trying to picture the person behind the signal.
  3. MIT Faculty Search — two open gigs at MIT, one around climate change and one “undefined.” Great job ad.
  4. Scalability at What Cost?evaluation of these systems, especially in the academic context, is lacking. Folks have gotten all wound-up about scalability, despite the fact that scalability is just a means to an end (performance, capacity). When we actually look at performance, the benefits the scalable systems bring start to look much more sketchy. We’d like that to change.
Comment
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.
Comment
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)
Comment
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.
Comment
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.
Comment
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.
Comment
Four short links: 23 December 2014

Four short links: 23 December 2014

Useful Metrics, Trouble at Mill, Drug R&D, and Disruptive Opportunities

  1. Metrics for Operational Performance — you’d be surprised how many places around your business you can meaningfully and productively track time-to-detection and time-to-resolution.
  2. Steel Mill Hacked — damage includes a blast furnace that couldn’t be shut down properly.
  3. Cerebros — drug-smuggling’s equivalent of corporate R&D. (via Regine Debatty)
  4. Ramble About Bitcoin (Matt Webb) — the meta I’m trying to figure out is: when you spot that one of these deep value chains is at the beginning of a big reconfiguration, what do you do? How do you enter it as a small business? How, as a national economy, do you help it along and make sure the transition happens healthily?
Comment
Four short links: 8 December 2014

Four short links: 8 December 2014

Systemic Improvement, Chinese Trends, Deep Learning, and Technical Debt

  1. Reith Lectures — this year’s lectures are by Atul Gawande, talking about preventable failure and systemic improvement — topics of particular relevance to devops cultural devotees. (via BoingBoing)
  2. Chinese Mobile App UI Trends — interesting differences between US and China. Phone number authentication interested me: You key in your number and receive a confirmation code via SMS. Here, all apps offer this type of phone number registration/login (if not prefer it). This also applies to websites, even those without apps. (via Matt Webb)
  3. Large Scale Deep Learning (PDF) — Jeff Dean from Google. Starts easy! Starts.
  4. Machine Learning: The High-Interest Credit Card of Technical Debt (PDF) — Google research paper on the ways in which machine learning can create problems rather than solve them.
Comment: 1