Brad Ideas

Robocars & More

I'm waiting at CDG in Paris, so it's time to add a new article to my series about fixing money in politics by looking at another thing campaigns spend money on (and thus raise money for), namely management of their campaigns.

A modern campaign is a complex thing. And yes, most of the money is spent on advertising, GOTV, events and staff. But there's also a lot of logistics, and a fair amount of software.

There's been a lot of press recently about an article in Slate by Lee Gomes which paints a pessimistic picture of the future of robocars, and particularly Google's project. The Slate article is a follow-on to a similar article in MIT Tech Review

Gomes and others seem to feel that they and the public were led to believe that current projects were almost finished and ready to be delivered any day, and they are disappointed to learn that these vehicles are still research projects and prototypes. In a classic expression of the Gartner Hype Cycle there are now predictions that the technology is very far away.

Both predictions are probably wrong. Fully functional robocars that can drive almost everywhere are not coming this decade, but nor are they many decades away. But more to the point, less-functional robocars are probably coming this decade -- much sooner than these articles expect, and these vehicles are much more useful and commercially viable than people may expect.

There are many challenges facing developers, and those challenges will keep them busy refining products for a long time to come. Most of those challenges either already have a path to solution, or constrain a future vehicle only in modest ways that still allow it to be viable. Some of the problems are in the "unsolved" class. It is harder to predict when those solutions will come, of course, but at the same time one should remember that many of the systems in today's research vehicles were in this class just a few years ago. Tackling hard problems is just what these teams are good at doing. This doesn't guarantee success, but neither does it require you bet against it.

And very few of the problems seem to be in the "unsolvable without human-smart AI" class, at least none that bar highly useful operation.

Gomes' articles have been the major trigger of press, so I will go over those issues in detail here first. Later, I will produce an article that has even more challenges than listed, and what people hope to do about them. Still, the critiques are written almost as though they expected Google and others, rather than make announcements like "Look at the new milestone we are pleased to have accomplished" to instead say, "Let's tell you all the things we haven't done yet."

Gomes begins by comparing the car to the Apple Newton, but forgets that 9 years after the Newton fizzled we had the success of the Palm Pilot, and 10 years after that Apple came back with the world-changing iPhone. Today, the pace of change is much faster than in the 80s.

Here are the primary concerns raised:

Maps are too important, and too costly

Google's car, and others, rely on a clever technique that revolutionized the DARPA challenges. Each road is driven manually a few times, and the scans are then processed to build a super-detailed "ultramap" of all the static features of the road. This is a big win because big server computers get to process the scans in as much time as they need, and see everything from different angles. Then humans can review and correct the maps and they can be tested. That's hard to beat, and you will always drive better if you have such a map than if you don't.

Any car that could drive without a map would effectively be a car that's able to make an adequate map automatically. As things get closer to that, making maps will become cheaper and cheaper.

Naturally, if the road differs from the map, due to construction or other changes, the vehicle has to notice this. That turns out to be fairly easy. Harder is assuring it can drive safely in this situation. That's still a much easier problem than being able to drive safely everywhere without a map, and in the worst case, the problem of the changed road can be "solved" by just the ability to come to a safe stop. You don't want to do that super often, but it remains the fail-safe out. If there is a human in the car, they can guide the vehicle in this. Even if the vehicle can't figure out where to go to be safe, the human can. Even a remote human able to look at transmitted pictures can help the car with that -- not live steering, but strategic guidance.

This problem only happens to the first car to encounter the surprise construction. If that car is still able to navigate (perhaps with human help,) the map can be quickly rebuilt, and if the car had to stop, all unmanned cars can learn to avoid the zone. They are unmanned, and thus probably not in a hurry.

The cost of maps

In the interests of safety, a lot of work is put into today's maps. It's a cost that somebody like Google or Mercedes can afford if they need to, (after all, Google's already scanned every road in many countries multiple times) but it would be high for smaller players.

A recent newspaper column where people complained about carpool cheats got me thinking -- could cheating actually be a solution to some carpool problems?

In late August, I visited Singapore to give an address at a special conference announcing a government sponsored collaboration involving their Ministry of Transport, the Land Transport Authority and A-STAR, the government funded national R&D centre. I got a chance to meet the minister and sit down with officials and talk about their plans, and 6 months earlier I got the chance to visit A-Star and also the car project at the National University of Singapore.

Some recent announcements have caused lots of press stir, and I have not written much about them, both because of my busy travel schedule, but also because there is less news that we might imagine.

Here's an interview with me in the latest Wall Street Journal on the subject of robocars and seniors.

This has always been a tricky question. Seniors are not early adopters, so the normal instinct would be to expect them to fear a new technology as dramatic as this one. Look at the market for simplified cell phones aimed at seniors who can't imagine why they want a smartphone. Not all are like this, but enough are to raise the question.

I've been on the road a lot, talking in places like Singapore, Shenzen and Hong Kong, and visiting Indonesia which is a driving chaos eye-opener. In a bit over 10 hours I will speak at Swiss Re's conference on robocars and insurance in Zurich. While the start will be my standard talk, in the latter section we will have some new discussion of liability and insurance.

There's another video presentation by me that I did while visiting Big Think in NYC.

This one is on The NSA, Snowden and the "tradeoff" of Privacy and Security.

Earlier, I did a 10 minute piece on Robocars for Big Think that won't be news to regular readers here but was reasonably popular.

Earlier this year, I started a series on fixing U.S. democracy. Today let me look at the problem I identified as #3: Voter turnout and the excessive power of GOTV.

In a big political campaign, fundraising is king, and most of the money goes to broadcast advertising. But a lot of that advertising, a lot of the other money, and most of the volunteer effort goes to something else called GOTV or "Get Out the Vote." Come to help a campaign and it's likely that's what you will be asked to do.

US elections have terrible turnout. Under 50% in the 1996 Presidential election, and only 57% in more recent contested elections. In off-years and local elections, the turnout is astonishingly low. Turnout is very low in certain minorities as well.

Because turnout is so low, the most cost effective way to gain a vote for your side is to convince somebody who weakly supports you to show up at the polls on election day. Your ads may pretend to attempt to sway people from the other side, or the small number of "undecideds," but a large fraction of the ads are just trying to make sure your supporters take the trouble to vote. Most of them won't, but those you can get count as much as any other vote you get. So you visit and phone all these mild supporters, you offer them rides to the polling place, you do everything legal you can to identify them and get them out, and in some cases, to scare the supporters of your opponent.

Is this how a nation should elect its leaders? By who can do the best job at getting the lukewarm supporters to make the trip on election day? It seems wrong. I will go even further, and suggest that the 45% or more who don't vote are in some sense "disenfranchised." Clearly not in the strong sense of that word, where we talk about voter suppression or legal battles. But something about the political system has made them feel it is too much of a burden to vote and so they don't. Those who do care find that hard to credit, they think of them as just lazy, or apathetic, and wonder if we really want to hear the voice of such people.

GOTV costs money, and as such, it is a large factor in what corrupts our politics. If GOTV becomes less effective, it can help reduce the influence of money in politics. It's serious work. Many campaigns send out people to canvass the neighbourhoods not to try to sway you, but just to figure out who is worth working on for GOTV.

Compulsory voting

Many countries in the world make it compulsory to vote. If your name is not checked off at the polling place, you get fined. Australia is often given as an example of this, with a 91% turnout, though countries like Austria and New Zealand do better without compulsory voting. But it does seem to make a difference.

Last month I wrote about paradoxes involving bitcoin and other cryptocurrency mining. In particular, I pointed out that while many people are designing alternative coins so that they are hard to mine with ASICs -- and thus can be more democratically mined by people's ordinary computers or GPUs -- this generates a problem. If mining is done on ordinary computers, it becomes worthwhile to break into ordinary computers and steal their resources for mining.

Ok, I'm not really much of a fan of banning anything, but the continued reports of massive thefts of password databases from web sites are not slowing down. Whether the recent Hold Security report of discovering a Russian ring that got a billion account records from huge numbers of websites is true or not, we should imagine that it is.

As I've written before there are two main kinds of password using sites. The sites that keep a copy of your password (ie. any site that can e-mail you your password if you forget it) and the sites who keep an encrypted/hashed version of your password (these can reset your password for you via e-mail if you forget it.) The latter class is vastly superior, though it's still an issue when a database of encrypted passwords is stolen as it makes it easier for attackers to work out brute-force attacks.

Sites that are able to e-mail you a lost password should be stamped out. While I'm not big on banning, it make make sense that a rule require that any site which is going to remember your password in plain form have a big warning on the password setting page and login page:

This site is going to store your password without protection. There is significant risk attackers will someday breach this site and get your ID and password. If you use these credentials on any other site, you are giving access to these other accounts to the operators of this site or anybody who compromises this site.

Sites which keep a hashed password (including the Drupal software running this blog, though I no longer do user accounts) probably should have a lesser warning too. If you use a well-crafted password unlikely to be checked in a brute-force attack, you are probably OK, but only a small minority do that. Such sites still have a risk if they are taken over, because the taken over site can see any passwords typed by people logging in while it's taken over.

Don't feel too guilty for re-using passwords. Everybody does it. I do it, in places where it's no big catastrophe if the password leaks. It's not the end of the world if one blog site has the multi-use password I use on another blog site. With hundreds of accounts, there's no way to not re-use with today's tools. For my bank accounts or other accounts that could do me harm, I keep better hygene, and so should you.

But in reality we should not use passwords at all. Much better technology has existed for many decades, but it's never been built in a way to make it easy to use. In particular it's been hard to make it portable -- so you can just go to another computer and use it to log into a site -- and it's been impossible to make it universal, so you can use it everywhere. Passwords need no more than your memory, and they work for almost all sites.

Even our password security is poor. Most sites use your password just to create a session cookie that keeps you authenticated for a long session on the site. That cookie's even easier to steal than a password at most sites.

I've been musing more on the future of the city under the robocar, and many visions suggest we'll have more sprawl. Earlier I have written visions of Robocar Oriented Development and outlined all the factors urban planners should look at.

In the essay linked below, I introduce the concept of a medium density urban neighbourhood that acts like a higher density space thanks to robocars functioning like the elevators in the high-rises of high density development.

A whole raft of recent robocar news.

UK to modify laws for full testing, large grants for R&D

The UK announced that robocar testing will be legalized in January, similar to actions by many US states, but the first major country to do so. Of particular interest is the promise that fully autonomous vehicles, like Google's no-steering-wheel vehicle, will have regulations governing their testing. Because the US states that wrote regulations did so before seeing Google's vehicle, their laws still have open questions about how to test faster versions of it.

Combined with this are large research grant programs, on top of the £10M prize project to be awarded to a city for a testing project, and the planned project in Milton Keynes.

Jerusalem's MobilEye going public in largest Israeli IPO

The leader in doing automated driver assist using cameras is Jerusalem's MobilEye. This week they're going public, to a valuation near $5B and raising over $600 million. MobilEye makes custom ASICs full of machine vision processing tools, and uses those to make camera systems to recognize things on the road. They have announced and demonstrated their own basic supervised self-driving car with this. Their camera, which is cheaper than the radar used in most fancy ADAS systems (but also works with radar for better results) is found in many high-end vehicles. They are a supplier to Tesla, and it is suggested that MobilEye will play a serious role in Tesla's own self-driving plans.

As I have written, I don't believe cameras are even close to sufficient for a fully autonomous vehicle which can run unmanned, though they can be a good complement to radar and especially LIDAR. LIDAR prices will soon drop to the low $thousands, and people taking the risk of deploying the first robocars would be unwise to not use LIDAR to improve their safety just to save a few thousand for early adopters.

Chinese search engine Baidu has robocar (and bicycle) project

Baidu is the big boy in Chinese search -- sadly a big beneficiary of Google's wise and moral decision not to be collaborators on massive internet censorship in China -- and now it's emulating Google in a big way by opening its own self-driving car project.

Various stories suggest a vehicle which involves regular handoff between a driver and the car's systems, something Google decided was too risky. Not many other details are known.

Also rumoured is a project with bicycles. Unknown if that's something like the "bikebot" concept I wrote about 6 years ago, where a small robot would clamp to a bike and use its wheels to deliver the bicycle on demand.

Why another search engine company? Well, one reason Google was able to work quickly is that it is the world's #1 mapping company, and mapping plays a large role in the design of robocars. Baidu says it is their expertise in big data and AI that's driving them to do this.

Velodyne has a new LIDAR

The Velodyne 64 plane LIDAR, which is seen spinning on top of Google's cars and most of the other serious research cars, is made in small volumes and costs a great deal of money -- $75,000. David Hall, who runs Velodyne, has regularly said that in volume it would cost well under $1,000, but we're not there yet. He has released a new LIDAR with just 16 planes. The price, while not finalized, will be much higher than $1K but much lower than $75K (or even the $30K for the 32 plane version found on Ford's test vehicle and some others.)

As a disclaimer, I should note I have joined the advisory board of Quanergy, which is making 8 plane LIDARs at a much lower price than these units.

Nissan goes back and forth on dates

Conflicting reports have come from Nissan on their dates for deployment. At first, it seemed they had predicted fairly autonomous cars by 2020. A later announcement by CEO Carlos Ghosn suggested it might be even earlier. But new reports suggest the product will be less far along, and need more human supervision to operate.

FBI gets all scaremongering

Many years ago, I wrote about the danger that autonomous robots could be loaded with explosives and sent to an address to wreak havoc. That is a concern, but what I wrote was that the greater danger could be the fear of that phenomenon. After all, car accidents kill more people every month in the USA than died at the World Trade Center 13 years ago, and far surpass war and terrorism as forms of violent death and injury in most nations for most of modern history. Nonetheless, an internal FBI document, released through a leak, has them pushing this idea along with the more bizarre idea that such cars would let criminals multitask more and not have to drive their own getaway cars.

I have many more comments pending on my observations from the recent AUVSI/TRB Automated Vehicles Symposium, but for today I would like to put forward an observation I made about two broad schools of thought on the path of the technology and the timeline for adoption. I will call these the aggressive and conservative schools. The aggressive school is represented by Google, Induct (and its successors) and many academic teams, the conservative school involves car companies, most urban planners and various others.

It's a big week for Robocar conferences.

In Berkeley, yesterday I attended and spoke at the "Robotics: Science and Systems" conference which had a workshop on autonomous vehicles. That runs to Wednesday, but overlapping and near SF Airport is the Automated Vehicles Symposium -- a merger of the TRB (Transportation Research Board) and AUVSI conferences on the same topic. 500 are expected to attend.

Yesterday's workshop was pretty good, with even a bit of controversy.

Yesterday saw:

In the last few months, I have found myself asked many times about a concept for solar roadways. Folks from Idaho proposing them have gotten a lot of attention with FHWA funding, a successful crowdfunding and even an appearance at Solve for X. Their plan is hexagonal modules with strong glass, with panels and electronics underneath, LED lights, heating elements for snow country and a buried conduit for power cables, data and water runoff. In addition, they hope for inductive charging plates for electric vehicles.

Everybody knows about bitcoin, but fewer know what goes on under the hood. Bitcoin provides the world a trustable ledger for transactions without trusting any given party such as a bank or government. Everybody can agree with what's in the ledger and what order it was put there, and that makes it possible to write transfers of title to property -- in particular the virtual property called bitcoins -- into the ledger and thus have a money system.

Satoshi's great invention was a way to build this trust in a decentralized way. Because there are rewards, many people would like to be the next person to write a block of transactions to the ledger. The Bitcoin system assures that the next person to do it is chosen at random. Because the winner is chosen at random from a large pool, it becomes very difficult to corrupt the ledger. You would need 6 people, chosen at random from a large group, to all be part of your conspiracy. That's next to impossible unless your conspiracy is so large that half the participants are in it.

How do you win this lottery to be the next randomly chosen ledger author? You need to burn computer time working on a math problem. The more computer time you burn, the more likely it is you will hit the answer. The first person to hit the answer is the next winner. This is known as "proof of work." Technically, it isn't proof of work, because you can, in theory, hit the answer on your first attempt, and be the winner with no work at all, but in practice, and in aggregate, this won't happen. In effect, it's "proof of luck," but the more computing you throw at the problem, the more chances of winning you have. Luck is, after all, an imaginary construct.

Because those who win are rewarded with freshly minted "mined" bitcoins and transaction fees, people are ready to burn expensive computer time to make it happen. And in turn, they assure the randomness and thus keep the system going and make it trustable.

Very smart, but also very wasteful. All this computer time is burned to no other purpose. It does no useful work -- and there is debate about whether it inherently can't do useful work -- and so a lot of money is spent on these lottery tickets. At first, existing computers were used, and the main cost was electricity. Over time, special purpose computers (dedicated processors or ASICs) became the only effective tools for the mining problem, and now the cost of these special processors is the main cost, and electricity the secondary one.

Money doesn't grow on trees or in ASIC farms. The cost of mining is carried by the system. Miners get coins and will eventually sell them, wanting fiat dollars or goods and affecting the price. Markets, being what they are, over time bring closer and closer the cost of being a bitcoin miner and the reward. If the reward gets too much above the cost, people will invest in mining equipment until it normalizes. The miners get real, but not extravagant profits. (Early miners got extravagant profits not because of mining but because of the appreciation of their coins.)

What this means is that the cost of operating Bitcoin is mostly going to the companies selling ASICs, and to a lesser extent the power companies. Bitcoin has made a funnel of money -- about $2M a day -- that mostly goes to people making chips that do absolutely nothing and fuel is burned to calculate nothing. Yes, the miners are providing the backbone of Bitcoin, which I am not calling nothing, but they could do this with any fair, non-centralized lottery whether it burned CPU or not. If we can think of one.

(I will note that some point out that the existing fiat money system also comes with a high cost, in printing and minting and management. However, this is not a makework cost, and even if Bitcoin is already more efficient doesn't mean there should not be effort to make it even better.)

CPU/GPU mining

Naturally, many people have been bothered by this for various reasons. A large fraction of the "alt" coins differ from Bitcoin primarily in the mining system. The first round of coins, such as Litecoin and Dogecoin, use a proof-of-work system which was much more difficult to solve with an ASIC. The theory was that this would make mining more democratic -- people could do it with their own computers, buying off-the-shelf equipment. This has run into several major problems:

• Even if you did it with your own computer, you tended to need to dedicate that computer to mining in the end if you wanted to compete
• Because people already owned hardware, electricity became a much bigger cost component, and that waste of energy is even more troublesome than ASIC buying
• Over time, mining for these coins moved to high-end GPU cards. This, in turn caused mining to be the main driver of demand for these GPUs, drying up the supply and jacking up the prices. In effect, the high end GPU cards became like the ASICs -- specialized hardware being bought just for mining.
• In 2014, vendors began advertising ASICs for these "ASIC proof" algorithms.
• When mining can be done on ordinary computers, it creates a strong incentive for thieves to steal computer time from insecure computers (ie. all computers) in order to mine. Several instances of this have already become famous.

The last point is challenging. It's almost impossible to fix. If mining can be done on ordinary computers, then they will get botted. In this case a thief will even mine at a rate that can't pay for the electricity, because the thief is stealing your electricity too.

Five years ago, I posted a rant about the excess of customer service surveys we're all being exposed to. You can't do any transaction these days, it seems, without being asked to do a survey on how you liked it. We get so many surveys that we now just reject these requests unless we have some particular problem we want to complain about -- in other words, we're back to what we had with self-selected complaints.

Some recent press and talks:

Earlier in June I sat down with "Big Think" for an interview they have titled "Robocars 101" explaining some of the issues around the cars.

So far it's been big players like Google and car companies with plans in the self-driving space. Today, a small San Francisco start-up named Cruise, founded by Kyle Vogt (a founder of the web video site Justin.tv) announces their plans to make a retrofit kit that will adapt existing cars to do basic highway cruise, which is to say, staying in a lane and keeping pace behind other cars while under a driver's supervision.