"ai" entries

Four short links: 25 June 2015

Four short links: 25 June 2015

Enchanted Objects, SE Blogs, AI Plays Mario, and Google's Future of Work

  1. 16 Everyday Objects Enchanted by Technology (Business Insider) — I want a Skype cabinet between our offices at work.
  2. Software Engineering Blogs — ALL the blogs!
  3. MarI/O (YouTube) — clear explanation of how an evolutionary algorithm figures out how to play Mario.
  4. Google’s Monastic Vision for the Future of Work (New Yorker) — But it turns out that future-proofed life looks a lot like the vacuum-packed present. […] Inside, it is about turning Google into not only a lifestyle but a fully realized life. The return of the Company Town.
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Four short links: 15 June 2015

Four short links: 15 June 2015

Streams at Scale, Molecular Programming, Formal Verification, and Deep Learning's Flaws

  1. Twitter Heron: Stream Processing at Scale (Paper a Day) — very readable summary of Apache Storm’s failings, and Heron’s improvements.
  2. Molecular Programming Projectaims to develop computer science principles for programming information-bearing molecules like DNA and RNA to create artificial biomolecular programs of similar complexity. Our long-term vision is to establish molecular programming as a subdiscipline of computer science — one that will enable a yet-to-be imagined array of applications from chemical circuitry for interacting with biological molecules to nanoscale computing and molecular robotics.
  3. The Software Analysis Workbenchprovides the ability to formally verify properties of code written in C, Java, and Cryptol. It leverages automated SAT and SMT solvers to make this process as automated as possible, and provides a scripting language, called SAW Script, to enable verification to scale up to more complex systems. “Non-commercial” license.
  4. What’s Wrong with Deep Learning? (PDF in Google Drive) — What’s missing from deep learning? 1. Theory; 2. Reasoning, structured prediction; 3. Memory, short-term/working/episodic memory; 4. Unsupervised learning that actually works. … and then ways to get those things. Caution: math ahead.
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Four short links: 1 June 2015

Four short links: 1 June 2015

AI Drives, Decent Screencaps, HTTP/2 Antipatterns, Time Series

  1. The Basic AI Drives (PDF) — Surely, no harm could come from building a chess-playing robot, could it? In this paper, we argue that such a robot will indeed be dangerous unless it is designed very carefully. Without special precautions, it will resist being turned off, will try to break into other machines and make copies of itself, and will try to acquire resources without regard for anyone else’s safety. These potentially harmful behaviors will occur not because they were programmed in at the start, but because of the intrinsic nature of goal-driven systems.
  2. PreTTY — how to take a good-looking screencap of your terminal app in action.
  3. Why Some of Yesterday’s HTTP Best Practices are HTTP/2 Antipatterns — also functions as an overview of HTTP/2 for those of us who didn’t keep up with the standardization efforts.
  4. Tiseana software project for the analysis of time series with methods based on the theory of nonlinear deterministic dynamical systems. (via @aphyr)
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Four short links: 28 May 2015

Four short links: 28 May 2015

Messaging and Notifications, Game Postmortem, Recovering Robots, and Ethical AI

  1. Internet Trends 2015 (PDF) — Mary Meeker’s preso. Messaging + Notifications = Key Layers of Every Meaningful Mobile App, Messaging Leaders Aiming to Create Cross-Platform Operating Systems That Are Context-Persistent Communications Hubs for More & More Services. This year’s deck feels more superficial, less surprising than in years past.
  2. When the Land Goes Under the SeaAs it turns out: People really despise being told to not replay the game. Almost universally, the reaction to that was a kernel of unhappiness amidst mostly positive reviews. In retrospect, including that note was a mistake for a number of reasons. My favorite part of game postmortems is what the designers learned about how people approach experiences.
  3. Damage Recovery Algorithm for Robots (IEEE) — This illustrates how it’s possible to endow just about any robot with resiliency via this algorithm, as long as it’s got enough degrees of freedom to enable adaptive movement. Because otherwise the Terminators will just stop when we shoot them.
  4. The Counselor — short fiction with ethics, AI, and how good things become questionable.
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Four short links: 27 May 2015

Four short links: 27 May 2015

Domo Arigato Mr Google, Distributed Graph Processing, Experiencing Ethics, and Deep Learning Robots

  1. Roboto — Google’s signature font is open sourced (Apache 2.0), including the toolchain to build it.
  2. Pregel: A System for Large Scale Graph Processing — a walk through a key 2010 paper from Google, on the distributed graph system that is the inspiration for Apache Giraph and which sits under PageRank.
  3. How to Turn a Liberal Hipster into a Global Capitalist (The Guardian) — In Zoe Svendsen’s play “World Factory at the Young Vic,” the audience becomes the cast. Sixteen teams sit around factory desks playing out a carefully constructed game that requires you to run a clothing factory in China. How to deal with a troublemaker? How to dupe the buyers from ethical retail brands? What to do about the ever-present problem of clients that do not pay? […] And because the theatre captures data on every choice by every team, for every performance, I know we were not alone. The aggregated flowchart reveals that every audience, on every night, veers toward money and away from ethics. I’m a firm believer that games can give you visceral experience, not merely intellectual knowledge, of an activity. Interesting to see it applied so effectively to business.
  4. End to End Training of Deep Visuomotor Policies (PDF) — paper on using deep learning to teach robots how to manipulate objects, by example.
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Four short links: 25 May 2015

Four short links: 25 May 2015

8 (Bits) Is Enough, Second Machine Age, LLVM OpenMP, and Javascript Graphs

  1. Why Are Eight Bits Enough for Deep Neural Networks? (Pete Warden) — It turns out that neural networks are different. You can run them with eight-bit parameters and intermediate buffers, and suffer no noticeable loss in the final results. This was astonishing to me, but it’s something that’s been re-discovered over and over again.
  2. The Great Decoupling (HBR) — The Second Machine Age is playing out differently than the First Machine Age, continuing the long-term trend of material abundance but not of ever-greater labor demand.
  3. OpenMP Support in LLVMOpenMP enables Clang users to harness full power of modern multi-core processors with vector units. Pragmas from OpenMP 3.1 provide an industry standard way to employ task parallelism, while ‘#pragma omp simd’ is a simple yet flexible way to enable data parallelism (aka vectorization).
  4. JS Graphs — a visual catalogue (with search) of Javascript graphing libraries.
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Four short links: 14 May 2015

Four short links: 14 May 2015

Human-Machine Cooperation, Concurrent Systems Books, AI Future, and Gesture UI

  1. Ghosts in the Machines (Courtney Nash) — People are neither masters of machines, nor subservient to their machine-learning outcomes — we cannot, and should not, separate the two. We are actors, together, in a very complex system. David Woods calls this “joint cognitive systems.”
  2. TLA+ (Leslie Lamport) — two tutorials: “Principles of Concurrent Computing” and “Specification of Concurrent Systems.” Ironically, I see people grizzling that the book on distributed systems hasn’t been linearised. I wonder if you can partition it into the two tutorials and still have full availability…
  3. Deep Learning vs Probabilistic vs LogicAs of 2015, I pity the fool who prefers Modus Ponens over Gradient Descent.
  4. Touché (Disney Research) — measur[es] capacitive response of object and human at multiple frequencies, a technique that we called Swept Frequency Capacitive Sensing. The signal travels through different paths depending on its frequency, capturing the posture of human hand and body as well as other properties of the context. The resulted data is classified using machine learning algorithms to identify gestures that are then used to trigger desired responses of the user interface.
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Creative computing with Clojure

Exploring Clojure as a tool to generate music, visual art, poetry, and dance.

creative_clojure

Clojure is gaining traction and popularity as a programming language. Both enterprises and startups are adopting this functional language because of the simplicity, elegance, and power that it brings to their business. The language originated on the JVM, but has since spread to run on the CLR and Node.js, including web browsers and mobile devices. With this spread of practical innovation, there has been another delightful development: a groundswell of people making art with Clojure.

Getting creative with Clojure

Creative Computing combines the power and engineering of the computer with the artistic inspirations of humans. People are using Clojure as a tool to generate music, visual art, poetry, and even dance. This ability to harness technology for creative purposes is both exciting and important. For it not only touches the heart and inspires existing technologists, but it also transcends all barriers. Art is a gateway to bring new people, young and old, from all walks of life, to the field of programming.

Let’s explore some of the areas of Creative Computing with Clojure, and showcase some inspiring examples from a selection of artist/programmers. We’ll look at projects that touch on music, art, games, writing, and even robots.

Read more…

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Four short links: 6 May 2015

Four short links: 6 May 2015

Self-Driving Cars, Cloud BigTable, Define "Uptime," and Continuous Delivery Architectures

  1. Andrew Ng (Wired) — I think self-driving cars are a little further out than most people think. There’s a debate about which one of two universes we’re in. In the first universe it’s an incremental path to self-driving cars, meaning you have cruise control, adaptive cruise control, then self-driving cars only on the highways, and you keep adding stuff until 20 years from now you have a self-driving car. In universe two you have one organization, maybe Carnegie Mellon or Google, that invents a self-driving car and bam! You have self-driving cars. It wasn’t available Tuesday but it’s on sale on Wednesday. I’m in universe one. I think there’s a lot of confusion about how easy it is to do self-driving cars. There’s a big difference between being able to drive a thousand miles, versus being able to drive anywhere. And it turns out that machine-learning technology is good at pushing performance from 90 to 99 percent accuracy. But it’s challenging to get to four nines (99.99 percent). I’ll give you this: we’re firmly on our way to being safer than a drunk driver.
  2. Google Cloud BigTable — Google’s BigTable, with Apache HBase API, single-digit millisecond latency, and “fully managed”. G are hell-bent on catching up with Amazon and Microsoft at this cloud serving thing.
  3. Call Me Maybe: AerospikeWe’re setting a timeout of 500ms here, and operations still time out every time a partition between nodes occurs. In these tests we aren’t interfering with client-server traffic at all. Aerospike may claim “100% uptime”, but this is only meaningful with respect to particular latency bounds. Given Aerospike claims millisecond-scale latencies, you may want to reconsider whether you consider this “uptime”.
  4. 31 Continuous Delivery Architectures (Slideshare) — from a vendor, so one name crops up repeatedly (other than “Jenkins”), but it’s still good devops voyeurism/envy.
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Four short links: 17 April 2015

Four short links: 17 April 2015

Distributed SQLite, Communicating Scientists, Learning from Failure, and Cat Convergence

  1. Replicating SQLite using Raft Consensus — clever, he used a consensus algorithm to build a distributed (replicated) SQLite.
  2. When Open Access is the Norm, How do Scientists Communicate? (PLOS) — From interviews I’ve conducted with researchers and software developers who are modeling aspects of modern online collaboration, I’ve highlighted the most useful and reproducible practices. (via Jon Udell)
  3. Meet DJ Patil“It was this kind of moment when you realize: ‘Oh, my gosh, I am that stupid,’” he said.
  4. Interview with Bruce Sterling on the Convergence of Humans and MachinesIf you are a human being, and you are doing computation, you are trying to multiply 17 times five in your head. It feels like thinking. Machines can multiply, too. They must be thinking. They can do math and you can do math. But the math you are doing is not really what cognition is about. Cognition is about stuff like seeing, maneuvering, having wants, desires. Your cat has cognition. Cats cannot multiply 17 times five. They have got their own umwelt (environment). But they are mammalian, you are a mammalian. They are actually a class that includes you. You are much more like your house cat than you are ever going to be like Siri. You and Siri converging, you and your house cat can converge a lot more easily. You can take the imaginary technologies that many post-human enthusiasts have talked about, and you could afflict all of them on a cat. Every one of them would work on a cat. The cat is an ideal laboratory animal for all these transitions and convergences that we want to make for human beings. (via Vaughan Bell)
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