What is it?


What is it? is a free iPhone app for recognizing objects. You point it at things and the app will recognize the stillness of the scene, vibrate, take a photo and tell you what the object is. It’s “always on” and watching on purpose, just point your phone at something and it will attempt to recognize it.

And if it’s wrong, you can fix it by tapping the flashing text and typing what it is.

The app relies heavily on ImageIdentify[] from Wolfram Research. You can play with their website here on a phone, tablet or desktop device. The backend of the app is powered by the rather wonderful Wolfram Cloud which makes building something like this very easy.

Using Wolfram Cloud isn’t far from using Mathematica, and you can deploy APIs trivially from both:

APIFunction[{“image” -> “Image”}, ImageIdentify[#image] &]]

That’s about all it takes. The system returns a URL and you can then use that to make requests against. Mathematica and the Wolfram Cloud go way, way beyond this basic example of course. I can’t recommend enough that you play with this stuff. In a couple of weeks there’s a new book coming out on it too!

Today, this app has some decent if limited capabilities. The goal is something better than a star trek tricorder – something that will tell you the species of a leaf or the model year and trim of a car.


Lending Club & OpenStocks

Lending Club

I’ve been researching a few stocks recently including LendingClub which I now own. It got me thinking – why isn’t there a wiki of all this information?

For example, one of the interesting things for me to follow is the SEC Form 4 filings of a firm. This is where people who have some major position in a public company have to make public if they buy or sell shares. For example, if you learnt that the CEO was selling or buying shares that would be useful to know. It’s an indication of whether they’re personally invested or not. Similarly, if the whole leadership team is buying or selling then that tells you more and so on.

I just read through all of LendingClub’s Form 4s going back to when they went public in December 2014. I’ve summarized them in the OpenStocks wiki here. Each Form 4 is pretty dull. It contains who’s selling or buying, what it is they’re selling or buying (stocks, options etc), when and for how much. There can be footnotes to explain transfers and other things like that.

Aren’t there things that automatically parse these forms and spit this stuff out? Not really. Yes, they exist, but they tend to be terrible at interpreting the information. For example when someone in the leadership team of a company gets some shares they will often put them in a bunch of trusts. This can make the automated software misreport their holdings and lead you to think they have less at stake than they do.

What we’re doing is compressing information and time. It took about 4 hours to read the Form 4s for the last year, wikifi them, do a bit of research on the people and so on. We need to compress that time and energy in to a buy/sell. The first intermediary step is to tell a story using the Form 4’s as recovered DNA in Jurassic Park, and then filling in the holes. And hoping no dinosaurs eat you.

Thus. LendingClub went public after giving hundreds of millions of shares to their VCs who acquired rights to them in the A, B and C rounds. Some of the VCs also bought some at discount. The IPO price was $15. Six months or so later they gave a bunch of shares to their board. Then the VCs started selling them in lots of 2 or 10 million shares here or there. All this selling probably depressed the price, but the VCs have to do it to return capital to their investors. It’s likely this selling will continue.

In the last couple of months a few insiders have been selling shares for “new Tesla” to “new apartment” levels of cash ($100k to $500k or so). But those sales are dwarfed by their options and holdings across their trusts and so on. They’re sitting on tens to hundreds of millions of dollars. Incidentally, all the leadership team plus their board have excellent careers and lots of credibility to lose. This kind of selling looks acceptable. Maybe they just want a new Tesla or to send a child to college or whatever.

The quarterly earnings were a few weeks ago. They turned a small profit of about $1MM on profit of $110MM or so on $2.something billion in loans for the quarter. The decimal places don’t matter to me much. The graph with all the numbers screaming upward does.

The costs are all flat as a percentage of revenue if you go look at their filings. But, the revenue has been going up. A lot. So they’re hiring like crazy. If you look at glassdoor, the reviews are all pretty good modulo complaints about the rate of growth. At some point they’ll amortize the staff and other costs over growing revenues (e.g. they won’t need to keep hiring).

The earnings call laid lots of heavy hints about a new product in 2016. My bet is that will be mortgages. Eventually LendingClub will offer every aspect of finance and they want to ship 2 products a year. So far they have personal loans and business loans. There’s a lot more out there from credit cards to kickstarter. Mortgages just feel kind of big and obvious and leverage the existing client base really well. Plus, they have so much (p2p) money they need to find places to put it.

LC aren’t at war with the banks, which is very nice. Instead they’re partnering all over the place to help banks find uses for their capital and help their customers find loans. All very win-win.

There’s negative stuff to find too which I leave as an exercise for the reader.


So – why not put all this stuff in a wiki? I can’t find anything like it so I built one at OpenStocks. It’s very early.

It’s interesting to think what an open source community would look like, blended in to the investment space. Well it would have a wiki, and a mailing list right? And it would have some sort of chat area and a github repository. And it would have code and tools.

I view the wiki as the first step, informing the next things to be built. It’s fairly obvious that the public lack the tooling to understand investments, and open source code would fix that. If you’re a huge investment bank then you can pay people to read all those forms or write code to summarize them. It would be interesting to see what happens when you do that in a community.

Part research tool, part opinion, part software, part community. And google ads or something to pay for it. Mainly it’s just the things I want available when figuring out to buy or sell.


Via blogging about this I found Rank and filed, Sumzero and Value Investors Club which are all way more advanced and already running compared to the wiki idea.


The Book of OSM, now available!

bookThe Book of OSM is now shipping on Amazon Kindle and in paperback (uk, de)!

This book contains 15 interviews conducted by OSM founder Steve Coast with the people who were there as the project began and grew. Starting in 2004, the interviews trace how a rag tag collection of volunteers was able to produce a map which compares in quality to maps produced by multi-billion dollar corporations. Learn how such an ambitious project got started and then succeeded at mapping the world, for free!

The book was the result of a kickstarter that raised just under $10k.

The Book of OSM – nearly available

My kickstarter project for the book of OSM is nearly done. Kickstarter backers already have the PDF of the book: The contents are final and the cover has some bugs being fixed:


Notice the white lines on the back cover. Once that is done, it’ll be available on Amazon.com and Kindle. If you want to stay up to date, there is a mailing list on the website for the book.

Tesla Maps and the exploding future of map data

Out of a job!

Out of a job!

Tesla are making maps, and why not? It used to cost billions of dollars to go collect the data, now the customers do it for free. The sensor packages in phones, let alone in the car, have put the power of geography in everyone’s hands.

We used to do this with volunteers in OpenStreetMap but now even that will be superseded. Armed with cameras, GPS, radar and sonar, a car can just capture all the data and (pretty much) make a map automatically, for free. It’s happening for two reasons:

  1. The costs are now so low. The old model of paying people to drive around expensive vehicles to capture data is too expensive and takes too long. Even if you did drive every road, every year, it still isn’t good enough for autonomous driving.
  2. The incentives are so high. If you were Tesla would you want a dependency in Google for maps? Really, would you want a dependency on anyone now that the cost is zero?

I was talking to someone recently who’s 18 or so. They literally thought “encyclopedia” meant “wikipedia”. Digging in their memory they remembered that there used to be sets of books (Britannica) too, but not anything else. That’s how maps are going to go, in a sense.

When proprietary map companies drive around expensive cars to collect data they had to pay for the car, the equipment and the people. Tesla has their customers to pay for all of that. They’ll have a fixed cost in building software to capture the data and then amortize that very quickly so the effective cost for them to build one of the best maps of the world is going to be… zero dollars.

StreetView cars are going to go away, it will just be every car taking photos all the time.


The number of maps is going to explode. It used to be that pretty much just two companies held map data for the US and EU; NavTeq and TeleAtlas. Now there are five: Google, Waze, OSM, TomTom and Nokia. Correction, now there are six with Tesla. We can argue over their relative qualities, OSM lacks geocoding, Tesla probably does too and so on. But it’s coming.

And those are just the public ones. There are a bunch of logistics companies and governments who have their own maps.

The list of people who might want their own map, and be in a position to build it, is large. Every car company, every decent-sized tech company, every location company (Garmin to Strava). The arms race is now on.

As the number of maps goes up, the value per-map is going down. That means that you should probably short anyone reliant on proprietary map revenue for their future. OpenStreetMap is pretty comfortable because the dollar cost of OSM is already zero so there aren’t any adjustments to be made, except perhaps that the incentives to help complete a free map of the world are going away, if everyone has maps and the value is dropping so precipitiously.

You could argue that price of maps won’t change since Google, Waze and Tesla will keep their maps to themselves. And yes, maybe. But it’s more likely not since they are removing themselves (and their dollars) from the customer pool. One of the new maps will be made available at some point too, they won’t all be locked up.

So the value that used to be in the map data will move up the stack, right?

Actually I’m not so sure. Charlie Munger has this nice story about textiles where some factory making fabric bought some machine that made them 20% cheaper, or whatever. They were proud of this. But of course, every other factory does the same thing and the value doesn’t go to the factories but to the consumer. The consumer wins not the factory.

The primary way map service companies got their valuations was waving around the Nokia acquisition as a bellwether for value. But Nokia actually owned something – map data. If you’re providing services then you need something else, like large long-term customer deals to provide map services to anchor you.

The cost for anyone to start doing basic map service work is… zero. So we should expect a bunch of competition in that sector. And of course, thanks to Google making maps free to the consumer, everyone thinks maps are free so the actual dollars you get from developers or whatever are pretty thin.

So at the top end, your customers are going to go make their own maps and at the bottom end, Google, Apple and so on are making maps free. It’s a tough spot, but luckily there’s probably a decade in there to figure it out.

Further Out, 10-30 years

The interesting implication is that creating a map will cost zero for Tesla, doesn’t mean it’s zero for everyone. It’s very beneficial to have a convenient fleet of sensors out on the roads. But that too is changing. Everyone and their brother is building self-driving cars.

But will there be a market for them?

It’s deeply interesting. A lot of the models seem to be predicated upon everyone buying two self-driving cars like today every household buys two cars. That just seems really unlikely. It looks more likely that instead of two cars I buy one self-driving car and rearrange life a tiny bit, since when I’m done with it, it can drive home and help someone else.

So the market could easily drop 50%. But wait, there’s more!

Why would I have one at all? Pizza Hut will have them. They’ll send a car to pick me up and run an errand so long as I stop in for pizza. Or if I want to visit a friend, they can just send their car to pick me up. Or, one of the ride-sharing services. So, really, would I buy a self-driving car at all? So if it’s mostly fleets buying the things, you can kiss goodbye to the network of dealers. And since most of these things will be electric, the current network of maintenance shops is going to go away.

At minimum the landscape around driving is going to change dramatically. It’s hard to see drive-thrus working out like they do today, or taxi companies… or mapping companies.

Because in a world of self-driving cars, why do we need traffic lights? Why would we need stop signs or lane markings? How much paint do we use every year to mark lines on roads? Will we need roads? No – we won’t need roads covered in asphalt, we only need the parts the wheels go on covered and can leave a gap in the middle of weaker, or no, material. So the cost of building or maintaining a freeway is going to drop off a cliff too.

And in that world, maps themselves are going to be completely different. Why would you need street signs? In fact, why name anything at all? The name of the highway you’re on is completely meaningless since you don’t use that information, the car does.

Fun times.

Glass Business Cards


I had this idea a while ago – why not take the incredibly strong glass we use on phones and make business cards out of them?

After some iterations on the process, I now have some! I can get them down to just 2 millimeters thin and mass laser etch them. They look incredible, you’re going to want to lick them:


I have a website mockup and name (Clarity Cards):


Sound interesting? The website is over here. Sign up for the mailing list to keep in the loop, it will be a kickstarter project soon:

License Ascent

Copyright when first envisaged granted a limited-term monopoly on a work which then later fell in to the public domain, or PD. This would give the author some amount of time to make money and pay the mortgage, balanced with allowing people later on to take the work and build upon it. So you write a book, you can sell it but nobody else can, and then some number of years later everybody can do as they please with your book.

This is no longer the case. Copyright is effectively infinite. This means that while we can take old works and build upon them (Pinocchio) we cannot do the same with even pretty old works (Mickey Mouse). Edge cases exist of course, for example you can in many places use old works for parody.

Some people wish to make their work available under less restrictive terms than owning it forever. For them, there are a set of licenses which they can use to release their works.

  • They can claim attribution. Broadly, this means you can use my work but you have to say where it came from.
  • They can claim share-alike. Broadly, this means you can use my work, but any derivative works need to also be sharable. So you can’t take my book and then rewrite portions and claim it for yourself.
  • They can claim commercial rights. Essentially this means you can use my work for anything but profit.
  • You can use some combination of the above.

Thus instead of claiming copyright forever for your new book, photograph or software, you could instead for example say “use it however you wish but all changes must be shared-alike and you can’t use it commercially”. This allows individuals and companies to put works out there and allow them to spread more easily than if they retained all the copyrights.

Two basic methods of making money have emerged while using these open licenses:

  1. The intellectual piece is free, but any physical product costs money. For example, 3D Robotics software for drones is freely downloadable and you can change it. But if you want a physical, flying drone then that costs money. Very similar is this: the basic software is free but some critical piece required for some use case requires payment.
  2. The work is available publicly under a difficult open license, but privately under some commercial agreement. This is known as dual licensing. The downside is that to encourage commercial usage, the open license tends to be as painful as possible. This way, a student at home is unaffected but a company might find a license difficult. Perhaps it requires a legal review, or places burdens on the company like open sourcing everything they do. To avoid this pain, they pay for the commercial license.

The trouble here is we still don’t have things leaking in to the public domain over time. It’s seen that once a work is licensed under some license that it’s stuck there until the end of man.Capture

What if we changed that?

I propose we engage in some kind of license ascent over time. Perhaps descent would be better. Under this scheme, some work starts out under a restrictive and painful license and over time makes it’s way in to the public domain. For example:

  1. I write a book. For the first year, it is available under a attribution, share-alike non-commercial license.
  2. After the first year, it is available attribution, non-commercial.
  3. After the second year, it is available under attribution.
  4. After the third year, it is available public-domain.

We are reintroducing the concept of the work leaking in to the public domain gradually. So when I first create some piece of work I own it outright and then over time it becomes less and less burdened.

For static works like a book, the timelines may be longer. Say, two or five years per step. For works which changed all the time, like datasets about the world, perhaps each step lasts a year. Why would we want to do this? Two reasons: Because otherwise it’s really hard to make money from open source, and otherwise open projects don’t benefit the public domain.

There are classes of works which require “giving back” like OpenStreetMap in order to attract people to contribute. That is, why would you contribute to OSM if you couldn’t access the data? OSM has now existed for 11 years and the state of mapping in the public domain is still essentially the same as it was 11 years ago. But what if OSM data dropped in to a more liberal license, or the public domain, over time? Perhaps we could have a PD version of OSM but it was 5 years old. It wouldn’t compete with OSM itself, but it would enrich what people could build on without restrictions.

Put another way, do we want OSM to be perfect in another 10 years and the public domain still be essentially unusable? Wouldn’t it be nice to improve both OSM and (for free!) the public domain maps available?

Now imagine you have some new project which requires crowdsourcing to succeed. Dual licensing has the downside that picking the open license has many difficulties. You want to pick something that encourages people to contribute yet allows you to retain space to sell things, and this isn’t easy. If instead you practiced license ascent then everybody gets the data at some point in the future. Perhaps if you are a PD person you wait 3 years, and a share-alike person you have to wait two years. But either way, it’s better than never getting the data under a license that you would consider useful.

And, it does this whilst allowing the project or company to make money off the freshest data. It also creates an incentive to make the data fresher, all the time, because otherwise the old data will be good enough for people.

Now you could argue that any project should be open from the start, but open projects tend to have significant downsides. Open projects are terrible at user interaction and experience. They’re terrible at design. They tend to be incoherent. But they are great at innovation and collecting data. At the other end, private companies which collect data tend to be great at design and so on, but terrible at innovation and collecting data because they don’t have volunteers. I posit that license ascent is a way to achieve both and that it’s better than just picking a license or selling widgets on the side.


Open GeoQuestion – collecting data in the field


Screenshot of Open GeoQuesiton

There are lots of attributes of the world out there that it would be nice to collect in to some structured data. Questions about your environment like these:

  • Is it noisy where you are?
  • Is it safe?
  • What address are you at?
  • Are you in an urban area?
  • What objects are around you?

… and many more. So I built this crazy little web app here. It’s really best if you look at it on your phone. It works really best, if you’re out walking around some place.

You can answer questions about where you are in a quick-fire way. You can also ask new questions for anyone else to answer, all over the world. What will be really interesting is – what questions will you ask everyone else about the environment.

The data is aggregated together and then hopefully we can do meaningful things with it. Subjectivity of course will be interesting, if I think a place is noisy do you think it is quiet? And so on…

There are two special modes. The first, address-only allows you to focus on addresses and is a simple, clean interface to letting you walk around and collect geocode data. It is primed in the United States with data. The second is thing-only mode which lets you focus on taking pictures of objects and naming them. Objects and their names are very useful in machine learning. Both these modes focus on problems with lack of data that nobody is solving right now and each will get their own blog posts later.

There’s some simple game-ification in there too – you accrue points for all the questions you answer. Variable leaderboards (which refresh hourly) show how you’re doing against your peers in collecting data.

I must give a shout out to Yelp. The way the yelp iOS app asks quick questions when you check in to a venue is pretty neat. You check in, and it asks a variety of things like whether it’s a casual place, whether it’s expensive and so on. It does so in a very quick and fun way that almost makes you feel bad for not answering. I’m seeking to expand that to any question, about the whole world.

So give it a try and email me your thoughts. If you want to stay up to date and learn more about the project, sign up below:

Open Encyclopedias


Airline encyclopedia from yesteryear

iOS Simulator Screen Shot Sep 2, 2015, 3.36.41 PM

Airliner article on an iPhone 6

If you go and play with Microsoft Encarta from 20 years ago you’ll discover a ton of fun functionality that doesn’t exist in it’s successor Wikipedia. Games, quizzes, tours and more.

Today’s encyclopedia experience is pretty poor compared to the books I’d immerse myself in as a kid. I used to love trawling through books full of detailed content and serendipity.

The ’90s CD-ROM encyclopedias had tons of features but lacked in content. Today that is reversed. Thanks to wikipedia there is tons of content but very few features by comparison.

So I’ve built something to try and see what a topic-specific encyclopedia would look like today on a modern interface. To try and take what Encarta looked like in terms of features and marry it with open content and design elements from those paper encyclopedias. The result can be downloaded for iPad & iPhone today (Android and Windows coming if iOS works out).

Why airliners? I used to love reading through books full of them. But I could just as well go build an encyclopedia of cats, trains or planets. The point is that it is not the whole of wikipedia. It’s curated and specific to some topic.


Boeing 747 article on an iPad

The encyclopedia includes badges which are granted upon reading certain sets of articles. For example, if you read about Concorde and the TU-144 (the two supersonic commercial airliners) then you get the supersonic badge, and so on.

The content works better the larger the screen (e.g. an iPad) but goes all the way down to an iPhone 4S. You’ll notice there are things beyond wikipedia – for example the title images are also open content and add some color to the page.

The encyclopedia is entirely offline so you can use it for a car trip or plane ride. It’s hard to convey the depth – but there are hundreds of articles in there which means hours of reading and exploring. A portion of the profits of course will go to wikipedia.

Basically, the whole thing is designed for what I would want if I was 7 or 14 again and had plenty of free time and an iPad instead of a dead tree to page through. Maybe nobody will be interested, I don’t know. If you’d like to see something different (a feature, a different encyclopedia) then click here.



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