How to win a fight with God

The breeze whispers of a transformation, a time of great trial and tribulation for mankind. We face an adversary whose complexity is almost unimaginable. Its vast computing power makes the human brain look like a toy. Worse still, it wields against us a powerful nanotechnology, crafting autonomous machines out of thin air. Already, more than one percent of the Earth is under its sway. I’m talking of course about the mighty Amazon rainforest.

But humans have long ago learned to live with our ancient enemies, the plants and the animals. Perhaps we can take some lessons for how to navigate our new friends, the AIs, who may be arriving any day now.

The rainforest is not actively trying to kill us, at least not most of the time. It is locked into a fierce struggle with itself, deploying its vast resources in internal competition. As a side effect, it produces large amounts of oxygen, food and other ecosystem services that are of great benefit to humanity. But the rainforest doesn’t like us, doesn’t care about us, mostly doesn’t even notice us. It exists in a private hell of hyper-competition, honed to a sharp point by the lathe of selection turning for a billion years.

So here is one model for AI safety. Don’t hope for direct control. Don’t dream of singletons. Instead, design a game that locks the AIs in a competition we don’t care about, orthogonal to the human world, perhaps with a few ecosystem services thrown our way as a side-effect. We will only collect scraps from the table of the Gods. But while the Gods are busy with their own games, we can get on with ours.

I think of the Irish proverb: What’s as big as half the Moon? Answer: The other half. Good advice for fighting with God.

Written with assistance from ChatGPT :-)

Google+ Archive

Google is shutting down Google+ in the next few days. I’m archiving my G+ stream here for posterity.

Over 7 years I posted exactly 1,001 times to Google+. I know it was never an especially popular social network, but somewhat to my surprise I found that I enjoyed it a lot. There was a strong set of people on G+ interested in deep learning, robotics and related topics, at least for a period of several years. The unlimited post length meant your could have meaningful conversations in a way you couldn’t on Twitter. For me Google+ was a thoughtful place, with high quality people, interesting content and meaningful discussion. The fact that it was a small, ignored community mostly interested in technical topics provided the conditions for that.

I have now reluctantly moved to Twitter, and I also have this blog for occasional long form content. Twitter is (alas) not much of a substitute for G+. No matter how carefully I curate who I follow, my Twitter stream is invariably full of political anger and culture wars. I am as susceptible to this as anyone else, and a Twitter session is a pretty sure way to make me feel angry and unhappy. I very much wish there was a way to turn down the emotion in my Twitter feed. Unfortunately I am yet to find that setting. Nevertheless, I do still get some useful technical and professional news from Twitter, so I will likely proceed with it and accept the unhappiness tax that it imposes.

So RIP G+, you were not much loved by most, but I will miss you.


Two and a half years ago I left Google and set out to build a new kind of search engine. This may sound a little crazy, but all the best things are like that :-)

We’ve been avoiding the tech press and trying to build things quietly, but this week we’re launched our user-facing app. I’m really proud of what the team has built, so it’s exciting to finally be able to say a bit more about it.

The problem we’ve been working on is finding specific items locally. For example, a light bulb just broke and it’s a strange fitting, where’s the nearest place you can get a new one?  Or you’re half way through a recipe and realise you’re missing an ingredient – where do you get it?



Imagine you’re a road engineer and you’re designing an access road for a new town. The town will soon be built in a previously uninhabited area. You’ve managing the construction project, but unfortunately no one can tell you what the population of the town will be.

Taking your job seriously, you sit down to design the best road that you can build. You settle on constructing a seven lane highway with regular flyovers to minimize traffic. The road will be fully lit with a state-of-the-art LED lighting system. You add crash barriers and regularly spaced emergency telephones. After much consideration you decide to also include a rest area with parking and toilets. This involves designing a self-contained water and sewerage system, but it’s obviously worth it.

With three months to go until launch day, you discover problems with road drainage. After the panic subsides, the construction team agrees to work around the clock to refit a completely new system for surface water management. By a minor miracle, the work is completed on time.

Opening day finally arrives and the excitement is intense. Everyone agrees the finished product is an engineering marvel. The new town will have the best road in the world.

Unfortunately, it turns out that the town is a remote settlement with a population of 57. The road is mainly used by an old man and a donkey.

The next year, you are again given a road construction project for another new town. Having learned your lesson, you build a modest single lane road. It’s well constructed but nothing special.

Opening day comes again, and it’s revealed that this time the “town” is in fact a major city with a population of 14 million. There are 50 mile tailbacks for six years before a larger road can be built. Your face appears on wanted posters throughout the nation, and you flee the country in disgrace.

Twitter, I forgive you the Fail Whale. And I hope to always walk the middle *ahem* road.

Building a DIY Street View Car

A little blast from the past here. Several years ago I built something very like a Google Street View car to gather data for my PhD thesis. At the time I wrote up a blog post about the experience, as a guide for anyone else who might want to build such a thing. But I never quite finished it. Upgrading WordPress today, I came across this old post sitting in my drafts folder from years ago, and decided to rescue it. So here it is. The making of a DIY StreetView car.


The Universal Robotic Gripper

I just saw a video of device that consists of nothing more than a rubber balloon, some coffee grounds and a pump. I’m pretty sure it’s going to change robotics forever. Have a look:

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It’s a wonderful design. It’s cheap to make. You don’t need to position it precisely. You need only minimal knowledge of the object you’re picking up. Robotic grasping has always been too hard to be really practical in the wild. Now a whole class of objects just got relatively easy.

Clearly, the design has it’s limitations. It’s not going to allow for turning the pages of a book, making a cheese sandwich, tying a dasiy chain, etc. But for relatively straightforward manipulation of rigid objects, it’s a beautiful solution. This one little idea could help start a whole industry.

The research was a collaboration between Chicago, Cornell and iRobot, with funding from DARPA. It made the cover of PNAS this month. The research page is here.

Fun with Robots

It’s no secret that I’m a huge fan of Willow Garage. So as they get ready to ship their first PR2 robots, here’s a gratuitous video of the pre-release testing:

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This second video is a nice overview of what Willow Garage and their open source robotics program is all about:

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Posts of the Year

As I make arrangements to close down things in the lab and prepare for a bit of turkey and ham, I thought I’d put up some of my favourite blog posts from the last year:

Finally, for a bit of fun, check out the Austrian Hexapod Dance Competition:

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Silicon Valley Comes to Oxford

I’ll be at Silicon Valley Comes to Oxford all day today. This has been an excellent event in previous years, and there is a strong line-up again this year. Anyone interested in visual search technology, do come say hello.

Update: I heard some great talks today and met lots of interesting people during coffee. Chris Sacca’s pitch workshop was especially good. No bullshit. The most valuable thing was the perspective – all those bits of knowledge that are obvious from the inside but very hard to come by from the outside. And of course hearing Elon Musk was just fantastic.

For those people who were interested in our lab’s visual search engine, there’s an online demo here (scroll down to where it says Real-time Demo). The demo is actually of some older results from about a year ago by a colleague of mine. Things have gotten even better since then.

Computer Vision in the Elastic Compute Cloud

In a datacenter somewhere on the other side of the planet, a rack-mounted computer is busy hunting for patterns in photographs of Oxford.  It is doing this for 10 cents an hour, with more RAM and more horsepower than I can muster on my local machine. This delightful arrangement is made possible by Amazon’s Elastic Compute Cloud.

For the decreasing number of people who haven’t heard of EC2, it’s a pretty simple idea. Via a simple command line interface you can “create” a server running in Amazon’s datacenter. You pick a hardware configuration and OS image, send the request and voilà – about 30 seconds later you get back a response with the IP address of the machine, to which you now have root access and sole use.  You can customize the software environment to your heart’s content and then save the disk image for future use. Of course, now that you can create one instance you can create twenty. Cluster computing on tap.

This is an absolutely fantastic resource for research. I’ve been using it for about six months now, and have very little bad to say about it. Computer vision has an endless appetite for computation. Most groups, including our own, have their own computing cluster but demand for CPU cycles typically spikes around paper deadlines, so having the ability to instantly double or triple the size of your cluster is very nice indeed.

Amazon also have some hi-spec machines available. I recently ran into trouble where I needed about 10GB of RAM for a large learning job. Our cluster is 32-bit, so 4GB RAM is the limit. What might have been a serious headache was solved with a few hours and $10 on Amazon EC2.

The one limitation I’ve found is that disk access on EC2 is a shared resource, so bandwidth to disk tends to be about 10MB/s, as opposed to say 70MB/sec on a local SATA hard drive. Disk bandwidth tends to be a major factor in running time for very big out-of-core learning jobs. Happily, Amazon very recently released a new service called Elastic Block Store which offers dedicated disks, though the pricing is a little hard to figure out.

I should mention that for UK academics there is a free service called National Grid, though personally I’d rather work with Amazon.

Frankly, the possibilities opened up by EC2 just blow my mind. Every coder in a garage now potentially has access to Google-level computation. For tech startups this is a dream. More traditional companies are playing too. People have been talking about this idea for a long time, but it’s finally here, and it rocks!

Update: Amazon are keen to help their scientific users. Great!