- mlcomp — a free website for objectively comparing machine learning programs across various datasets for multiple problem domains.
- Printing Code: Programming and the Visual Arts (Vimeo) — Rune Madsen’s talk from Heroku’s Waza. (via Andrew Odewahn)
- What Data Brokers Know About You (ProPublica) — excellent run-down on the compilers of big data about us. Where are they getting all this info? The stores where you shop sell it to them.
- Subjective Impressions Do Not Mirror Online Reading Effort: Concurrent EEG-Eyetracking Evidence from the Reading of Books and Digital Media (PLOSone) — Comprehension accuracy did not differ across the three media for either group and EEG and eye fixations were the same. Yet readers stated they preferred paper. That preference, the authors conclude, isn’t because it’s less readable. From this perspective, the subjective ratings of our participants (and those in previous studies) may be viewed as attitudes within a period of cultural change.
ENTRIES TAGGED "machine learning"
Comparing Algorithms, Programming & Visual Arts, Data Brokers, and Your Brain on Ebooks
Drug Interactions from Search History, Web Satire, Visible Peer Review, and Rights-based Copyright
- Pharmacovigilance — Signals from The Crowd (PDF) — in the NY Times’ words: Using automated software tools to examine queries by 6 million Internet users taken from Web search logs in 2010, the researchers looked for searches relating to an antidepressant, paroxetine, and a cholestorol lowering drug, pravastatin. They were able to find evidence that the combination of the two drugs caused high blood sugar. (via New York Times)
- The World Wide Web is Moving to AOL — best satire you’ll read this month.
- Review History for Perceptual elements in Penn & Teller’s “Cups and Balls” magic trick — PeerJ makes peer review history available for the articles it publishes. Not only does this build reputation for peer reviewers who want it, but it is also a wonderful insight into how paranoid science must be to defend against mistakes in data interpretation. (The finished paper is fun, too)
- A New Basis for Copyright — NZ’s most technically-literate judge floats an idea for how copyright might be reimagined in a more useful way for the modern age by considering it in terms of human rights. Perhaps there should be consideration of a new copyright model that recognises content user rights against a backdrop of the right to receive and impart information and a truly balanced approach to information and expression that recognises that ideas expressed are building blocks for new ideas. Underpinning this must be a recognition on the part of content owners that the properties of new technologies dictate our responses, our behaviours, our values and our ways of thinking. These should not be seen as a threat but an opportunity. It cannot be a one-way street with traffic heading only in the direction dictated by content owners.
Handmade Hardware, Tab Silencer, Surprise and Models, and Sciencey GIFs
- Your USB Sticks Are Made With Chopsticks (Bunnie Huang) — behind-the-scenes on how USB sticks are made.
- mutetab — find and kill the Chrome tab making all the damn noise! (via Nelson Minar)
- Visualization, Modeling, and Surprises (John D Cook) — paraphrases Hadley Wickham: Visualization can surprise you, but it doesn’t scale well. Modelling scales well, but it can’t surprise you.
- Head Like an Orange — science animated GIFs, assembled from nature documentaries. (via Ed Yong)
Google's Autonomous Cars, DIY BioPrinter, Forms Validation, and Machine Learning Workflow
- Google’s Driverless Car is Worth Trillions (Forbes) — Much of the reporting about Google’s driverless car has mistakenly focused on its science-fiction feel. [...] In fact, the driverless car has broad implications for society, for the economy and for individual businesses. Just in the U.S., the car puts up for grab some $2 trillion a year in revenue and even more market cap. It creates business opportunities that dwarf Google’s current search-based business and unleashes existential challenges to market leaders across numerous industries, including car makers, auto insurers, energy companies and others that share in car-related revenue.
- DIY BioPrinter (Instructables) — Think of it as 3D printing, but with squishier ingredients! How to piggyback on inkjet printer technology to print with your own biomaterials. It’s an exciting time for biohackery: FOO Ewan Birney is kicking ass and taking names, he was just involved in a project storing and retrieving data from DNA.
- ADAMS — open sourced workflow tool for machine learning, from the excellent people at Waikato who brought you WEKA. ADAMS = Advanced Data mining And Machine learning System.
Tweet Cred, C64 History, Performance Articles, Return of Manufacturing
- Credibility Ranking of Tweets During High Impact Events (PDF) — interesting research. Situational awareness information is information that leads to gain in the knowledge or update about details of the event, like the location, people affected, causes, etc. We found that on average, 30% content about an event, provides situational awareness information about the event, while 14% was spam. (via BoingBoing)
- The Commodore 64 — interesting that Chuck Peddle (who designed the 6502) and Bob Yannes (who designed the SID chip) are still alive. This article safely qualifies as Far More Than You Ever Thought You Wanted To Know About The C64 but it is fascinating. The BASIC housed in its ROM (“BASIC 2.0″) was painfully antiquated. It was actually the same BASIC that Tramiel had bought from Microsoft for the original PET back in 1977. Bill Gates, in a rare display of naivete, sold him the software outright for a flat fee of $10,000, figuring Commodore would have to come back soon for another, better version. He obviously didn’t know Jack Tramiel very well. Ironically, Commodore did have on hand a better BASIC 4.0 they had used in some of the later PET models, but Tramiel nixed using it in the Commodore 64 because it would require a more expensive 16 K rather than 8 K of ROM chips to house.
- The Performance Calendar — an article each day about speed. (via Steve Souders)
- Mr China Comes to America (The Atlantic) — long piece on the return of manufacturing to America, featuring Foo camper Liam Casey.
Networked sensors and machine learning make it easy to see when things are out of the ordinary.
Who will own the data the industrial Internet generates, and how will users fare under an onslaught of optimization problems?
Cheap sensors and sophisticated software keep expensive machines running smoothly
Medical Data Commons, Verizon Sell You, Doctor Watson, and Weedkilling Drones
- Let’s Pool Our Medical Data (TED) — John Wilbanks (of Science Commons fame) gives a strong talk for creating an open, massive, mine-able database of data about health and genomics from many sources. Money quote: Facebook would never make a change to something as important as an advertising with a sample size as small as a Phase 3 clinical trial.
- Verizon Sells App Use, Browsing Habits, Location (CNet) — Verizon Wireless has begun selling information about its customers’ geographical locations, app usage, and Web browsing activities, a move that raises privacy questions and could brush up against federal wiretapping law. To Verizon, even when you do pay for it, you’re still the product. Carriers: they’re like graverobbing organ harvesters but without the strict ethical standards.
- IBM Watson About to Launch in Medicine (Fast Company) — This fall, after six months of teaching their treatment guidelines to Watson, the doctors at Sloan-Kettering will begin testing the IBM machine on real patients. [...] On the screen, a colorful globe spins. In a few seconds, Watson offers three possible courses of chemotherapy, charted as bars with varying levels of confidence–one choice above 90% and two above 80%. “Watson doesn’t give you the answer,” Kris says. “It gives you a range of answers.” Then it’s up to [the doctor] to make the call. (via Reddit)
- Robot Kills Weeds With 98% Accuracy — During tests, this automated system gathered over a million images as it moved through the fields. Its Computer Vision System was able to detect and segment individual plants – even those that were touching each other – with 98% accuracy.