Five short links

numberfivecat

Photo by Brian Schoonover

Understanding genre in a collection of a million volumes – This project achieved 97% precision in identifying whether a book was poetry, prose, or non-fiction. Machines are never going to replace human scholars, but I know they can help them answer questions that would have been impossible to tackle in the past.

OpenAddresses – A wonderful resource for building geocoding tools, and one we’ve needed for a long time, I’m excited to see this collection growing.

Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture – I know I’m a broken record on deep learning, but almost everywhere it’s being applied it’s doing better than techniques that people have been developing for decades. This example is particularly exciting because the results can be fed in to other image processing algorithms, it’s a big improvement in the foundations of our understanding of natural scenes.

Book Review: On the Road – Looking back on my reading growing up, I realize that the underlying appeal of a lot of books was a world where life would be easy, at least for the heroes and by extension me. I’ll always remember the review of Phillip K. Dick’s work that pointed out his protagonist always had jobs, and they were often pretty unglamorous, and how unusual that was in sci-fi.

It’s not an asshole problem – it’s a bystander problem – More food for thought from Cate Huston, talking about some practical ways for men to help our industry’s awful gender ratio without making a big song and dance of it.

Five Short Links

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Picture from Wikipedia

The Documentary Hypothesis – When I get frustrated by my lack of data when I’m trying to track down a bug or build a machine learning system, I try to think about how much historians manage to do with a tiny amount of information. This is a great example, the sheer amount of thought that has gone into analyzing the authors of the Old Testament over the last few centuries is mind-boggling. Scholars have created a vast structure of interlocking ideas, and are constantly rearranging the pieces, all by squeezing out clues from between the lines of the texts. I get the same sense of awe when I see archaeologists reconstructing the past, nobody can squeeze more meaning out of ‘data exhaust’ than they can.

Your telltale video wobble can identify you – On a related topic, it’s not just your camera’s noise pattern that’s unique, now footage from body cameras can be matched to people based on movement patterns. As we gather greater volumes of more precise data from all kinds of sensors, this kind of problem is going to come up more and more often.

How transferable are features in deep neural networks? – To save you a click, the answer is “Very”! I spent decades skeptical of neural networks, they seemed theoretically elegant but useless in practice, but over the last couple of years they’ve astonished me. They really have matured into general purpose tools for turning almost any noisy ‘natural’ data source, sound, text, images, into clean information. Suddenly everything’s machine-readable!

The other side of diversity – An honest, frank, and depressing account of what it’s like to be a black woman in my world.

Weaving a very visual web – Om captures a lot of why photos and cameras are becoming so important.

A Newbie’s Guide to the San Francisco Mission Swimming Pool

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Years ago I lived in Dundee, Scotland. During the long winters exercise was hard to come by, and bridies weren’t, so I had to find some kind of workout before I keeled over. Thankfully the city had a wonderful public swimming pool. It was 50 meters long, had plenty of lanes, was open late so I could use it after work, and was indoors and heated which made a welcome change from the freezing rain outside.

I’ve had trouble finding anything as good in the American cities I’ve lived in, but after some detective work I have found a public pool I like here in San Francisco, the Mission Pool. There’s not much good information about it online though, and I found it a bit intimidating to go the first time, so I want to share what I discovered to help any other newbies who might find it daunting, and help it live up to its ‘Inclusion Center’ title!

It’s located between Guerrero and Valencia off 19th Street (technically on Linda Street, but that’s just an alley), and you’ll see a sign for the Mission Pool and Playground outside. It’s an outdoor pool, but so far it hasn’t been too cold, even in chilly weather. It is closed December to March though, so it’s only got a couple of weeks left as I write this. There’s a schedule online of the sessions they run, I’ve only ever attended the lane swimming myself though.

Here’s what you need to know if you’re going for the first time:

– The fee is $6, and you need exact change! There’s a corner store on 19th and Guerrero that I’ll often buy some water at to get the right money. The attendants push the money into a sealed box, so they really don’t have any change to give.

– The lockers have no locks. I bought a cheap padlock that I use, but it’s also pretty common to bring your bag out to the poolside. It’s only accessible to other swimmers, so that feels pretty safe.

– The two outside lanes tend to be used by slower swimmers, the two center ones are faster-paced. I’m not all that speedy so I usually hang in the slow lane. As a 25 meter public pool, most people are pretty chill recreational swimmers, so don’t worry if you’re slow too, you won’t feel out of place.

– The etiquette is that you stay on the right side of your lane, so other people in it can pass you going the other way, or overtake if they need to. This does require a bit of cooperation, but everyone I’ve swum with has been very thoughtful and so it has worked surprisingly well. If you’re worried, hang out by the poolside first for a few minutes and you’ll see how it works. There’s usually only three or four swimmers in each lane, so it doesn’t feel crowded.

– The pool is open to the elements so you get a few leaves blown in, but otherwise the water has been clean and not too chlorinated. If you forget your goggles, there’s a box of spares available too, they are a big help.

After a long break from swimming it’s been fun to get back into it at the Mission Pool, so I hope this trail of breadcrumbs helps some other newbies discover this neighborhood gem. It’s turned into one of my favorite outings in the city, so I hope you get a chance to give it a try too!

How to run the Caffe deep learning vision library on Nvidia’s Jetson mobile GPU board

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Photo by Gareth Halfacree

My colleague Yangqing Jia, creator of Caffe, recently spent some free time getting the framework running on Nvidia’s Jetson board. If you haven’t heard of the Jetson, it’s a small development board that includes Nvidia’s TK1 mobile GPU chip. The TK1 is starting to appear in high-end tablets, and has 192 cores so it’s great for running computational tasks like deep learning. The Jetson’s a great way to get a taste of what we’ll be able to do on mobile devices in the future, and it runs Ubuntu so it’s also an easy environment to develop for.

Caffe comes with a pre-built ‘Alexnet’ model, a version of the Imagenet-winning architecture that recognizes 1,000 different kinds of objects. Using this as a benchmark, the Jetson can analyze an image in just 34ms! Based on this table I’m estimating it’s drawing somewhere around 10 or 11 watts, so it’s power-intensive for a mobile device but not too crazy.

Yangqing passed along his instructions, and I’ve checked them on my own Jetson, so here’s what you need to do to get Caffe up and running.

Setup

The first step once you’ve unboxed your Jetson is logging in. You can attach a monitor and keyboard, but I prefer just plugging it into a local router and ssh-ing in. elinux.org/Jetson/Remote_Access has more details, but it should show up as tegra-ubuntu.local on your local network, and the username is ubuntu:

ssh ubuntu@tegra-ubuntu.local

The default password is ubuntu. Next we need to run Nvidia’s installer that comes with the device, and reboot.

sudo NVIDIA-INSTALLER/installer.sh
sudo shutdown -r now

Once the board has rebooted, you can log back in and continue installing all the packages you’ll need for Caffe.

ssh ubuntu@tegra-ubuntu.local
sudo add-apt-repository universe
sudo apt-get update
sudo apt-get install libprotobuf-dev protobuf-compiler gfortran \
libboost-dev cmake libleveldb-dev libsnappy-dev \
libboost-thread-dev libboost-system-dev \
libatlas-base-dev libhdf5-serial-dev libgflags-dev \
libgoogle-glog-dev liblmdb-dev gcc-4.7 g++-4.7

You’ll need the Cuda SDK to build and run GPU programs, and elinux.org/Tegra/Installing_CUDA has a good general guide. The summary is that you’ll need to register as an Nvidia developer,  on a logged-in browser download the Cuda 6.0 for ARM package to your local machine and then copy it over to the Jetson from there.

scp ~/Downloads/cuda-repo-l4t-r19.2_6.0-42_armhf.deb ubuntu@tegra-ubuntu.local:

Then back on the ssh connection to your Tegra, run these Cuda installation steps.

sudo dpkg -i cuda-repo-l4t-r19.2_6.0-42_armhf.deb
sudo apt-get update
sudo apt-get install cuda-toolkit-6-0
sudo usermod -a -G video $USER
echo "# Add CUDA bin & library paths:" >> ~/.bashrc
echo "export PATH=/usr/local/cuda/bin:$PATH" >> ~/.bashrc
echo "export LD_LIBRARY_PATH=/usr/local/cuda/lib:$LD_LIBRARY_PATH" >> ~/.bashrc
source ~/.bashrc

If everything’s installed correctly, running ‘nvcc -V’ should give you a compiler version message. Now you need to grab the Tegra versions of OpenCV. On your main machine, download developer.nvidia.com/rdp/assets/opencv-run-tegra-k1 and developer.nvidia.com/rdp/assets/opencv-dev-tegra-k1 from your logged-in browser and copy them over to the Jetson.

scp ~/Downloads/libopencv4tegra* ubuntu@tegra-ubuntu.local:

On the Jetson, install those packages.

sudo dpkg -i libopencv4tegra_2.4.8.2_armhf.deb
sudo dpkg -i libopencv4tegra-dev_2.4.8.2_armhf.deb

We need to download and install Caffe. Yangqing has put in a few recent tweaks and fixes so at the moment you’ll need to grab the dev branch, but those should soon be rolled into master.

sudo apt-get install -y git
git clone https://github.com/BVLC/caffe.git
cd caffe && git checkout dev
cp Makefile.config.example Makefile.config
sed -i "s/# CUSTOM_CXX := g++/CUSTOM_CXX := g++-4.7/" Makefile.config

We have to use gcc version 4.7 because nvcc hits some problems with the default 4.8, but otherwise we’re using a pretty standard setup. You should be able to kick off the build.

make -j 8 all

Once that’s complete, you should check things are working properly by running Caffe’s test suite. This can take quite a while to finish, but hopefully it should report a clean bill of health.

make -j 8 runtest

Finally you can run Caffe’s benchmarking code to measure performance.

build/tools/caffe time --model=models/bvlc_alexnet/deploy.prototxt --gpu=0

This should take about 30 seconds, and output a set of statistics. It’s running 50 iterations of the recognition pipeline, and each one is analyzing 10 different crops of the input image, so look at the ‘Average Forward pass’ time and divide by 10 to get the timing per recognition result. I see 337.86 ms as the average, so it takes 34 ms for each image. You can also try leaving off the –gpu=0 flag to see the CPU results, in my case is about 585 ms, so you can see how much Cuda helps!

Why nerd culture must die

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Photo by Attila Acs

My first girlfriend was someone I met through a MUD, and I had to fly 7,000 miles to see her in person. I read a paper version of the Jargon File at 15 and it became my bible. Just reading its descriptions of the internet I knew it was world-changing, even before the web, and as soon as I could I snuck into the local university computer labs with a borrowed account to experience the wonder of Usenet, FTP, and Gopher. I chose my college because Turing had once taught there, and the designer of the ARM chip would be one of my lecturers. My first job out of college was helping port the original Diablo to the first Playstation, and I spent five years writing games. I’ve dived deep into GPU programming. I’ve worked for almost two decades at both big tech companies and startups. I’ve spent countless hours writing about coding for the pure love of it. I’m a grown man who still plays Dungeons and Dragons!

My point is that if anyone can claim to be a nerd, it’s me. As a lonely teenager growing up in the English countryside, reading the Portrait of J. Random Hacker gave me a wonderful jolt of excitement and recognition. I’d never met anyone like that, but knowing that there were others out there like me gave me hope. As I went through college I started to discover a few more people who took a perverse pride in being geeks, but it was still rare and very much outside mainstream culture. Nobody really understood why I took a poorly-paid job in game programming after college instead of joining a bank, and most people’s eyes would glaze over when I mentioned I worked in computers. Over the years I gradually built a group of friends who shared the same interests in sci-fi, comics, games, and computers. It was nerd culture that brought us together, and their support was life-saving, but they were hard to find, and we were still way outside the cultural mainstream.

Over the last decade, that’s changed. Comic book adaptations are the safest bet in Hollywood. Lord of the Rings and Game of Thrones have made fantasy something anyone can enjoy without embarrassment. Perhaps most importantly, nerds now have money, power, and status. The biggest, fastest-growing companies in the world are run and staffed by us, and mainstream culture has shifted from mocking us to respect. Startups are sexy. We’ve won.

And that’s where the problem lies. We’re still behaving like the rebel alliance, but now we’re the Empire. We got where we are by ignoring outsiders and believing in ourselves even when nobody else would. The decades have proved that our way was largely right and the critics were wrong, so our habit of not listening has become deeply entrenched. It even became a bit of a bonding ritual to attack critics of the culture because they usually didn’t understand what we were doing beyond a surface level. It didn’t used to matter because nobody except a handful of forum readers would see the rants. The same reflex becomes a massive problem now that nerds wield real power. GamerGate made me ashamed to be a gamer, but the scary thing is that the underlying behavior of attacking critics felt like something I’d always seen in our culture, and tolerated. It only shocked me when it was scaled up so massively into rape and death threats, and I saw mainstream corporations like Intel folding in the face of the pressure we can bring to bear.

That’s why Marc Andreessen’s comment that Silicon Valley is nerd culture, and nerds are bro’s natural enemies felt so wrong. Sure, we used to be picked on or ignored by the bro’s, but that was when we had no money or power. Now we have status, bro’s are happy to treat us as buddies instead of victims, to the point that we’re unlikely to think of them as bro’s. I’ve pitched most VC firms in the Valley at one time or another, and a lot of the partners come from business or finance backgrounds. There are nerds in there too of course, and they do control the culture, but they also get along perfectly well with the preppy MBAs. The same holds true across the whole tech industry – they might have tried to steal our lunch money twenty years ago, but now they’re quite happy running biz-dev while we do the engineering.

One of the things I love about nerd culture is how much it values evidence and checking facts. When I’m optimizing code, my intuition about which parts are slowest is often wildly wrong, so I’ve learned the hard way that I have to profile the hell out of it before I try to fix anything. It’s a core skill for dealing with computers, our gut feelings often don’t work in such an alien realm, so skepticism becomes a habit. What has surprised me is how we leave that habit behind when confronted with evidence about ourselves. Pretty much every statistic we can track has shown fewer women getting computer science degrees and working as engineers compared to the 80’s. It’s a basic fact that we’re an incredibly imbalanced industry in all sorts of ways, from race to class and gender, and we’re getting worse.

I’m not claiming to know the answers, but you don’t have to be a social justice warrior to notice something is going very wrong somewhere. Even the Jargon File acknowledged, to paraphrase, that hackers routinely behave like assholes. Is it a crazy leap to imagine that this deeply-rooted tolerance of terrible behavior might drive people away?

When I look around, I see the culture we’ve built turning from a liberating revolution into a repressive incumbency. We’ve built magical devices, but we don’t care enough about protecting ordinary people from harm when they use them. We don’t care that a lot of the children out there with the potential to become amazing hackers are driven away at every stage in the larval process. We don’t care about the people who lose out when we disrupt the world, just the winners (who tend to look a lot like us).

I’d always hoped we were more virtuous than the mainstream, but it turns out we just didn’t have enough power to cause much harm. Our ingrained sense of victimization has become a perverse justification for bullying. That’s why I’m calling time on nerd culture. It’s done wonderful things, but these days it’s like a crawling horror of a legacy codebase so riddled with problems the only rational decision is to deprecate it and build something better.

What would something better look like? The Maker movement gives me hope, because including all the kids we’re missing is built in from the start. Whatever the future becomes, the bottom line is we need to value being a decent human being a hell of a lot more than we do now. Our toleration of asshole behavior must end, and it’s such an integral part of nerd culture that nuking the entire thing from orbit is the only way to be sure.

Untethered, by Jinky de Rivera

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I haven’t made it to much local theatre recently, but thanks to Facebook I heard about an old high school friend of Joanne who’d written a new play. I hadn’t run across Bindlestiff before, but it’s a small theatre on 6th Street that’s focused on Filipino artists and culture, and Jinky’s play came out of a workshop there. Last night we went to see it performed as one of six single-act plays that came out of that process, and her short piece ‘Untethered’ turned out to be one of the highlights for us. There was a lot of acting talent visible in all of the plays, but her piece about love, loss, and family had an amazing script too. It was technically complex, with time-jumping, different actors playing the same characters, and a narrator addressing the audience, so it could easily have been confusing and stilted, but everything came together in a way that was moving and natural. It felt autobiographical, but part of that may just be because the characters felt so fully-drawn and real.

If you get a chance I highly recommend trying to catch the show while it’s still playing. You’ll be seeing works that are raw and in-progress, so you’ll need to be prepared for some ups and downs across the evening, but ‘Untethered’ is a consistent delight, and we came away with something good from all of them.

Five short links

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Picture by Jan van Scorel

A quick programming note – I’m now at Google! This blog will continue to be my personal collection of random things and occasional rants though.

Frida – Greasemonkey for arbitrary binaries! You can hook into all sorts of function calls with Javascript, even on binaries you didn’t build yourself. I love the idea of being able to mash up desktop apps.

Spotting Tumors with Deep Learning – My friend Jeremy Howard has launched a new startup to apply deep learning to medical problems. Great to see the technology being applied to more things that matter.

Mechanical Turk Worker Protection Guidelines – It’s aimed at academics, but anyone who employs human data raters should read this as a guide on how not to be a jerk.

GPU_FFT – Andrew Holmes on how he created his super-fast FFT library on the Raspberry Pi, with lots of detail on the hand-coded assembler and memory access optimizations. Geek heaven!

fork() can fail : this is important – The crazy tale of a pathological edge case with fork(), and how code that doesn’t check return values very carefully will wipe out all the processes on a machine in a mysterious fashion. “Unix: just enough potholes and bear traps to keep an entire valley going.

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