Nat has chaired the O'Reilly Open Source Convention and other O'Reilly conferences for over a decade. He ran the first web server in New Zealand, co-wrote the best-selling Perl Cookbook, and was one of the founding Radar bloggers. He lives in New Zealand and consults in the Asia-Pacific region.
Social Intelligence in Mario Bros (YouTube) — collaborative agents built by cognitive AI researchers … they have drives, communicate, learn from each other, and solve problems. Oh, and the agents are Mario, Luigi, Yoshi, and Toad within a Super Mario Brothers clone. No code or papers about it on the research group’s website yet, just a YouTube video and a press release on the university’s website, so appropriately adjust your priors for imminent world destruction at the hands of a rampaging super-AI. (via gizmag)
Simple Anomaly Detection for Weekly Patterns — Rule-based heuristics do not scale and do not adapt easily, especially if we have thousands of alarms to set up. Some statistical approach is needed that is generic enough to handle many different metric behaviours.
How to Design a Robotics Experiment (Robohub) — although there are many good experimental scientists in the robotic community, there has not been uniformly good experimental work and reporting within the community as a whole. This has advice such as “the five components of a well-designed experiment.”
Elemental Machines — Boston startup fitting experiments & experimenters with sensors, deep learning to identify problems (vibration, humidity, etc.) that could trigger experimental failure. [C]rucial experiments are often delayed by things that seem trivial in retrospect. “I talked to my friends who worked in labs,” Iyengar says. “Everyone had a story to tell.” One scientist’s polymer was unstable because of ultraviolet light coming through a nearby window, he says; that took six months to debug. Another friend who worked at a pharmaceutical company was testing drug candidates in mice. The results were one failure after another, for months, until someone figured out that the lab next door was being renovated, and after-hours construction was keeping the mice awake and stressing them out. (that quote from Xconomy)
Usborne Computer and Coding Books — not only do they have sweet Scratch books for kids, they also have their nostalgia-dripping 1980s microcomputer books online. I still have a pile of my well-loved originals.
Powerful People are Terrible at Making Decisions Together — Researchers from the Haas School of Business at the University of California, Berkeley, undertook an experiment with a group of health care executives on a leadership retreat. They broke them into groups, presented them with a list of fictional job candidates, and asked them to recommend one to their CEO. The discussions were recorded and evaluated by independent reviewers. The higher the concentration of high-ranking executives, the more a group struggled to complete the task. They competed for status, were less focused on the assignment, and tended to share less information with each other.
MyBinder — turn a GitHub repo into a collection of interactive notebooks powered by Jupyter and Kubernetes.
Shmoocon 2016 Videos (Internet Archive) — videos of the talks from an astonishingly good security conference.
TipTalk — Samsung watchstrap that is the smart device … put your finger in your ear to hear the call. You had me at put my finger in my ear. (via WaPo)
Ecorithms — Leslie Valiant at Harvard broadened the concept of an algorithm into an “ecorithm,” which is a learning algorithm that “runs” on any system capable of interacting with its physical environment. Algorithms apply to computational systems, but ecorithms can apply to biological organisms or entire species. The concept draws a computational equivalence between the way that individuals learn and the way that entire ecosystems evolve. In both cases, ecorithms describe adaptive behavior in a mechanistic way.
Dataflow/Beam vs Spark (Google Cloud) — To highlight the distinguishing features of the Dataflow model, we’ll be comparing code side-by-side with Spark code snippets. Spark has had a huge and positive impact on the industry thanks to doing a number of things much better than other systems had done before. But Dataflow holds distinct advantages in programming model flexibility, power, and expressiveness, particularly in the out-of-order processing and real-time session management arenas.
Old-School PC Fonts — definitive collection of ripped-from-the-BIOS fonts from the various types of PCs. Your eyes will ache with nostalgia. (Or, if you’re a young gun, wondering how anybody wrote code with fonts like that) (my terminal font is VT220 because it makes me happy and productive)
Cognitive Load: Brain Gems — We distill the latest behavioural economics & consumer psychology research down into helpful little brain gems.
Huginn — MIT-licensed system for building agents that perform automated tasks for you online. They can read the Web, watch for events, and take actions on your behalf. Huginn’s Agents create and consume events, propagating them along a directed graph. Think of it as a hackable Yahoo! Pipes plus IFTTT on your own server.
Evidence-Oriented Programming — design programming language syntax and features based on what research shows works. They tested Perl and Java, found apparently not detectably easier to use for novices than a language that my student at the time, Susanna Kiwala (formerly Siebert), created by essentially rolling dice and picking (ridiculous) symbols at random.
LTE Weaknesses (PDF) — ShmooCon talk about how weak LTE is: a lot of unencrypted exchanges between handset and basestation, cheap and easy to fake up a basestation.
Analyzo — Find and Compare the Best Tools for your Startup it claims. We’re in an age of software surplus: more projects, startups, apps, and tools than we can keep in our heads. There’s a place for curated lists, which is why every week brings a new one.
How to Keep the NSA Out — NSA’s head of Tailored Access Operations (aka attacking other countries) gives some generic security advice, and some interesting glimpses. “Don’t assume a crack is too small to be noticed, or too small to be exploited,” he said. If you do a penetration test of your network and 97 things pass the test but three esoteric things fail, don’t think they don’t matter. Those are the ones the NSA, and other nation-state attackers will seize on, he explained. “We need that first crack, that first seam. And we’re going to look and look and look for that esoteric kind of edge case to break open and crack in.”
Chimera (Paper a Day) — the authors summarise six main lessons learned while building Chimera: (1) Things break down at large scale; (2) Both learning and hand-crafted rules are critical; (3) Crowdsourcing is critical, but must be closely monitored; (4) Crowdsourcing must be coupled with in-house analysts and developers; (5) Outsourcing does not work at a very large scale; (6) Hybrid human-machine systems are here to stay.
Microsoft Embedding Research — To break down the walls between its research group and the rest of the company, Microsoft reassigned about half of its more than 1,000 research staff in September 2014 to a new group called MSR NExT. Its focus is on projects with greater impact to the company rather than pure research. Meanwhile, the other half of Microsoft Research is getting pushed to find more significant ways it can contribute to the company’s products. The challenge is how to avoid short-term thinking from your research team. For instance, Facebook assigns some staff to focus on long-term research, and Google’s DeepMind group in London conducts pure AI research without immediate commercial considerations.
Google’s Go-Playing AI — The key to AlphaGo is reducing the enormous search space to something more manageable. To do this, it combines a state-of-the-art tree search with two deep neural networks, each of which contains many layers with millions of neuron-like connections. One neural network, the “policy network,” predicts the next move, and is used to narrow the search to consider only the moves most likely to lead to a win. The other neural network, the “value network,” is then used to reduce the depth of the search tree — estimating the winner in each position in place of searching all the way to the end of the game.
The Food Computer (MIT) — open source controlled-environment agriculture technology platform that uses robotic systems to control and monitor climate, energy, and plant growth inside of a specialized growing chamber. Climate variables such as carbon dioxide, air temperature, humidity, dissolved oxygen, potential hydrogen, electrical conductivity, and root-zone temperature are among the many conditions that can be controlled and monitored within the growing chamber. Operational energy, water, and mineral consumption are monitored (and adjusted) through electrical meters, flow sensors, and controllable chemical dosers throughout the growth period. (via IEEE Spectrum)