Toyota Investing $500M in Uber in Driverless Car Pact
wsj.com
wsj.com
Of course, there are many caveats to comparing disengagement rates. These are self-reported by companies, and each company may have different policies about which disengagements are serious enough to report. Also, not all miles are equal. Cruise likes to emphasize that its SF miles are more difficult than Waymo's more suburban Mountain View miles.
Here's a nice summary of the 2017 data I found for you: https://thelastdriverlicenseholder.com/2018/02/01/disengagem...
If it didn't work this way you would be incentivizing operators to train their drivers to take risks in order to hit disengagement metrics which would be bad.
I'm sure unprotected (i.e. no arrow) left hand turns remain one of the more difficult routine scenarios to fine tune. What works in (I assume) Chandler Arizona and San Francisco are probably two very different things. A large busy city like San Francisco simply requires a degree of aggression--Pittsburgh lefts, cutting through fairly small gaps, etc.--that would be inappropriate in a calmer and less busy environment.
Note: I've already got a negative opinion of Cruise regardless of their purported abilities. I followed up on some headhunter spam from Cruise a year or so ago. I bailed before even getting to a phone screen because as persistent as they were, they bailed or were late every time I agreed to one of their proposed times.
Being prepared as a second mover once a trailblazer demonstrates a good path can be good business. It even has some advantages over trying to lead and possibly wasting lots of R&D money on dead ends.
The first iPhone was revolutionary and ahead of its time, but copying a user experience, a grid of square icons, fancy animations and double touch is a lot easier than copying Waymo. You can't just copy Waymo by looking at it like you could by looking at an iPhone. Waymo's code is all in a black box of compiled code and how it works really is anyone's guess besides neural network and all the captors and millions of hours of simulations and drives etc.
The point is that this data would have been collected by the first-movers the entire time they are on the road. Such data would not be made available to newcomers.
If a new self driving car company would join the scene, they would need to gather all this data again themselves, somehow. This is the "uncopyable advantage" mentioned by OP.
Other aspects of a self-driving car business are more easily observed, including the significant regulatory and public perception risks. Here's one scenario: Waymo creates a technically excellent self-driving car, but it kills a handful of people in particularly gruesome way that causes the public to lose trust in a fully autonomous vehicle. As a result, "partially autonomous" vehicles are perceived as "just as good", and a company that has a massive ride-hailing business through which to monetize the technology has an advantage over another that has only a theoretical technology advantage.
Where would you put the odds of a regulatory or PR catastrophe causing an existential threat to Waymo?
And Comma.ai is cameras only, so it’s not fair to say all the others believe LIDAR is necessary.
Also, just because someone has LIDAR on their test rig, that doesn’t mean they think it’s necessary for production vehicles. They could just be using it for validation. They also might start off using it, and wean themselves off as they progress through development.
Waymo I believe had explicitly said they think LIDAR is needed but I haven’t heard anyone else say that explicitly.
The last major Tesla crash in California was a clear situation where LIDAR would've prevented a crash and yet the Tesla team continues to insist that cameras and radar (sonar really doesn't help much...) are all that is needed.
You just described Palm, Blackberry, and Windows Mobile...all of which Apple was copying. The iPhone was evolutionary, but not revolutionary by any means.
Back on topic: It's more about letting the first mover spend the money on figuring out the business plan. The second mover can then jump in with a more efficient business model based on the lessons learned from the first mover.
The biggest hurdles are at the start, but any company that can demo an autonomous vehicle that can, on average, drive a few miles in urban traffic without getting hung up is off and running. After those initial big hurdles, it's small hurdles stretching off further than the eye can see.
Uber had never really learned the first big hurdles. They scaled too big, too fast, and the whole operation was a clusterfuck. The rumour is that Uber was having trouble getting simulation working for them. So early on with Uber, driving around Philly, they were disengaging every block or two, and 2 years later they weren't doing much better.
In the wake of their accident they've had some time to reevaluate everything, and we'll see if they've actually managed to sort out their problems.
Waymo leads right now with 7 million miles driven.
If you wanted to drive that many miles in the next year, how much would it cost?
I estimate it would cost maybe $60M or so:
-$30M on cars (assuming a fleet of 200 cars driving 100 miles a day, costing $150K each)
-$5M on safety drivers (assuming $20/hr, 30 mph)
-$1M on fuel (assuming 30 mpg, $4/gal)
-$5M on insurance (no idea)
-$5M for a garage
-$5M for a couple dozen techs/engineers working in the garage
-$10M overhead, supplies, other costs?
And this total of ~$60M is with a bunch of upfront fixed costs (mostly cars, but also the garage). Year two the cost would drop in half to ~$30M.
By my math, if you had a working system and were bottlenecked only by data, you could catch up to Waymo's 7M miles for just $60M. Maybe my estimates are way off and actually it's $100M. Or even $200M. That's expensive, but I'm not so sure it's a moat when we're talking about companies with 10s of billions of cash on hand chasing a market that could eventually be a trillion dollars.
At this stage, I think if you have a working system, then by my math the cost per training mile is well under $10 per mile.
I wouldn't call that a moat, but maybe you do.
You did miss in your cost estimate scaling the compute costs of ML training to ingest that data. Also test courses and simulation to amplify and elaborate on tricky cases found in the data. Adding those things in adds 10's of millions to the estimate but doesn't change the fundamental analysis.
I think the real moat is in fleet networked data. If you have a lot of cars on the road and they are sharing info about strange situations to expect, it could be a big advantage for how "smart" the driving seems. I am thinking things like broken stoplights or badly placed traffic cones. A networked solution can alert other cars of the puzzling condition and the interpretation. Then later cars passing that location can proceed more confidently than if each vehicle has to work out an interpretation itself.
Just like how we see all newer cars coming out with the same types of tech e.g. lane change alerting or backup camera monitoring or Android auto/Apple carplay etc, as standard features? Or is automation tech more of a first mover monopoly in and of itself since it's so unique and patentable?
A lot of the current driving assist features are made by the same companies (e.g. mobileye, bosch) and then installed/licensed to car manufacturers. The same thing could happen with self-driving depending on who develops it first.
I think in general, it's easy to overestimate the long-term value of a first-mover advantage.
Sure, anyone can build a search engine. But as billions of dollars in spending has shown, no one can create one better than Google
1. Driving automation is orders of magnitude more expensive
2. Improperly-tested vehicles are much more likely to have fatal consequences, meaning a 90% perfect smartphone is OK, but 90% perfect driving software would kill people
3. It's much, much easier to clone an iPhone than Waymo hardware + software
Plus the amount of patents involved in this mean even if you're burning money down a dead end you might stumble upon an insight / patent that would help regardless of the approach taken. Often time with engineering a good design comes out of a known shortcoming of some other subsystem.
Only if you pretend it didn't take decades of gradual improvement to make the iPhone possible, and ignore the epic manufacturing cost of the components. Basically only if you ignore everything that has / does go into smartphones. It took hundreds of billions of dollars of investment into the underlying iPhone components and their near ancestors, to make the iPhone possible.
What's the total cost of the specific driving automation segment so far? A fraction of all the money plowed just into semiconductor fabrication development and construction over the last ~25 years so we could have smartphones at all. Then move on to the investment into storage, software, glass, communication chips, security, glass, etc.
It'd be equivalent to pretending that we're going to leap from Tesla's hands-free to full automation without anything inbetween. The iPhone didn't materialize out of nowhere.
There are billions invested into electric cars, too, but every large company has access to that technology (either with acquisition or licensing).
To understand what the difficulty is, it's important to consider that the size of the sensor input is very large. Don't think of it like twenty range finders around the car, rather a 360 degree medium resolution color + depth image (about 0.5 million data points coming at 30 fps).
It's difficult because you will never encounter the same set of sensor inputs twice, so you can't treat it like a search space problem. Once you've accepted that, you're in AI/ML territory where you might try to reason about what the closest set of known sensor inputs and action would be (classical AI, expert system), but that is impractically difficult with as 0.5 million dimensional search space, or train an ML model to 'reason' about the sensor space to make a decision about the appropriate action.
Approaches using a small number of sensors can do automatic breaking and smarter cruise control, but haven't been seen to be successful about navigating and making strategic decisions. The current belief is that more can be done by using denser sensors and more data and seems to be the case. There are people working on reducing the sensor density requirement, but the main focus right now is building a successful and safe self driving car, regardless of sensor and compute costs.
It's probably a very valid tradeoff.
In the future we'll likely have super-human spatial and temporal resolution, right now more improvements have been gained from highest possible spatial resolution with minimal plausible temporal resolution.
I hope there is a better, more technical explanation that ML researchers are using, because as someone who is somewhat of an expert on human vision and building products around it, this foundation is godawful if it is to be taken at face value. Which again, I am sure this is a simplification. Or at least, that's what I am telling myself.
File the promises and the problems under fiction because it appears to be more important to keep the world order, its financial system and these ridiculous media darling fluff piece corporations alive while they bleed money.
And no, im not closed to the idea of successful work being done on automated driving but 30 fps, WTF? too much going on in the larger context of the world, this shit isn't happening in 2020 or 2024 or whatever else many might say.
Because of this I'm leaning towards thinking waymo isn't trying to mimic actual human input.
https://www.theatlantic.com/technology/archive/2017/08/insid...
The problem with Uber is that they already operate on a trust deficit. They've had a long history of ignoring local rules and had a string of high-profile exits - including the CEOs - after workplace harassment issues.
That's not exactly a company I want to trust with my life.
Waymo, otoh, is operated by a company known for its "braininess". Self-driving is a computationally challenging problem. I trust Google to solve it much more than Uber.
There's also the fact that Waymo doesn't have to be a profit center for Google at all. They can afford to incur losses for years until they get the technology perfect.
For Uber, self-driving cars HAVE to be a profit center. If the company's existence depends on it, can I trust them to not cut corners?
Car manufacturers have decades of experience in shifting danger from inside to outside. Passengers are not the ones we need to worry about.
Passengers are not the ones we need to worry about.
Driving is very dangerous, and most drivers don't even carry enough insurance to pay for a couple months time off if they hit me. This, essentially, make my injuries an externality that isn't priced into the cost of transportation.
For that matter, if I'm injured in an accident and it's my fault, I don't have a lot of coverage for myself; I mean, through work, I have a long-term disability package, but that's still not great compared do what I'd make were I not disabled, and disability, as I understand it, is a huge pain in the ass when it comes to you being, you know, 'partially disabled' - still able to work, but not able to make nearly what you made before.
Carrying adequate insurance insures that the total cost of the injuries caused is rolled into the operating cost of the vehicle, and helps to price it rationally.
What chances does a regular human driver have in killing someone else while they cross the street? Its pretty high, given the number of casualties per day. All the people on their phones while driving and being otherwise distracted it's an enormous risk... Chances will never be 0, but autonomous cars have the potential to be safer then majority of human drivers.
At least you're honest. Low number statistics so far but AV's have been worse per car per year compared to human drivers. And you certainly can't trust Uber's engineering department given they literally raised the detection threshold because their computer vision sucked.
I think it's not nearly as exciting a dream if they're just buying the tech like everybody else. Aside from a strong brand and a lot of customer relationships, Uber doesn't have much in the way of assets. Google's got a stronger brand [1] and a lot more customer relationships, as do many others. If Uber is just one of many companies slapping labels on other people's tech, I'm not sure what makes it worth $75-100bn.
I suppose I should clarify since I was downvoted, Forbes wrote a story "what Ubers crash tells us about Japan's silent strategy for driverless cars"
"it illustrates a very important distinction between how U.S. and Japanese companies are approaching the research and deployment of autonomous vehicles.
Japanese firms have maintained a much lower profile in autonomous vehicles than their American counterparts, and many outside the industry assume this lack of publicity is a sign of lagging technology. Speaking with several industry leaders, however, makes it clear that this is not the case.
"While American firms have been grabbing the headlines, Japanese firms have been making steady progress behind the scenes. The fact that they have been less anxious to promote that progress outside of Japan is more a reflection of go-to-market strategy than the state of the underlying technology.""
In the US you can commit white collar crimes and still have people invest and give you the benefit of the doubt. There's no sense of shame rather glee and glorification, the i-get-money-fuck-you attitude.
In Japan, people will commit suicide for way less or even perceived wrong because there is a great deal of shame imposed on the individual for fucking up. Tough to innovate when failure is so taboo, people are willing to remove themselves from earth.
Japan has some unique advantage for go to market self driving cars. Japanese highway system is MUCH MUCH simpler to deal with then US one. If Toyota or Nissan or whoever can come up with a system that can drive you from Tokyo IC to wherever on Honshu following highways(mostly 2 lane, clearly marked, meticulously maintained..) this is going to be a huge deal. And few of them do have the whole thing mapped out.. we do know that.
Is Waymo might win.. RIM also seemed unassailable as was Nokia.
Japan also has a developed highway rest areas, you will often see people sleep in the car there, often whole families in vans that been outfitted for it. There is washroom, restaurants, sometimes shower and even hot spring, they are also clean, might have local produce being sold, alcohol etc
Here is a priceless use case for a salaryman from Tokyo. Get off work, get drunk with coworkers, get in the car with family at 10pm on friday. Car delivers you to the closest michi-no-eki to a ski resort and parks itself. Wake up at 6-7am, get to the resort by opening lift, grab breakfast at conbini drive to resort. There are lots fo places less then an hour off highway. Being able to sleep and being driven on highway would be incredible.
Company that delivers that feature in the family van will destroy competition until they can duplicate it.
best of all, no fast n furious wanna be-actually Japan has a thriving car culture and the police never seems to be able to catch those guys.
Waymo/Google is winning and has self-driving vehicles all over Chandler, Tempe and Gilbert Arizona at any given time.
For the most part it is going well, sometimes they act too safe but that isn't a bad idea for now, there have been a few complaints of Waymos going when fire engines or safety vehicles are on the road not slowing and in normal traffic slowing more than needed, or cars partially in a lane and slowing or stopping for them too much. I think the more grandma driving any self-driving is right now is good.
The biggest win of Waymo which is a competitive advantage and huge bonus is that by being Google/Alphabet, they also have access to tons of data and the best maps / map data i.e. speed limits, traffic, routes, dark/light changes to behavior, weather detection, data outside the CV/LIDAR that may be hugely beneficial. Other companies are going to have to pay for that or use Google, which they will collect immensely on in addition to use for free.
Think of that Tesla crash where other Teslas commonly had the same issue by drifting towards the ramp, Waymo/Google could correct that quicker it seems with their access. They need to be autonomous but also a neural network that can learn from other vehicles. They also need to tie into other systems like weather, day/night, emergency vehicles, traffic, routes etc etc. That Uber crash in Tempe, with day/night data and known pedestrian trails nearby + across the road, it may have been more cautious through that area and Waymo has that data with Google. Waymo is leading in multiple ways not just the self-driving part.
So whoever is trying to emulate Tesla is in for a nasty surprise, Tesla is automation 2.89. The last miles is the hardest and requires an ever increasing amount of data. while safer than humans driving Tesla's autopilot failures have done far more damage to the brand than accounted in the stock price.
Google/Alphabet/Waymo figured out their end game was to build the data that their competitors will not be able to emulate easily or costly.
So far Uber is spinning its wheels and Tesla has lost focus of the killer feature of their car, coming dead last in terms of automation ranking when compared to other major luxury brand manufacturers. But this is HN, and they love Don Papi Musk
Also, I don’t think Waymo is guaranteed to be the first to reach fully autonomous driving. What I know of their approach (which is fairly little, but wat does anybody outside Waymo know for sure there?), to me, seems they are building not cars that are autonomous, but networked. That has advantages (if one car notices a bump in the road, one riding the same road 10 minutes later can slow down), but also has the disadvantages that their software may depend too much on always having that network knowledge available. That may leave space for a competitor to grow in regions where roads barely exist.
Waymo also spends a lot on things that, in a few years, autonomous cars may not need not do at all.
For example, countries that want to speed up adoption of autonomous cars may make detecting traffic signs and traffic lights easier (e.g. by superimposing a high-frequency signal on LED traffic lights or by giving cars read access to a city’s traffic light infrastructure), make la e detection easier (e.g. by embedding cat eyes in the center of lanes) or require cars to better signal their intentions. If that happens, a lot of the work Waymo does on detecting all kinds of ‘static’ infrastructure becomes worth less.
IF that really happens, it would take at least a decade and Waymo's lead from network effects, more mature tech, more self-driving data, etc would be enormous by then.
And cost? Not that large, compared to the cost of building roads.
Also, is this really going to be just one "Self Driving Vehicle Systems" market? I can imagine Waymo being great in one segment, and other companies doing well in others.
I just see the inertia uber has with their install base will carry some considerable weight.
but seriously, how can i get a ride in a waymo so i can experience it?
Waymo's Self-Driving Cars Are Near: Meet the Teen Who Rides One Every Day https://www.bloomberg.com/news/features/2018-07-31/inside-th...
There are no such systems, even organic ones. I despair that the conventional wisdom here among the "hacker" intelligencia has pushed the burden so far. Autonomous vehicles are worth it if they are safeER than human drivers, not 100% free of accidents.
And it's noisy data anyway. Waymo is notable for the fact that their measured fatal accident rate is still zero, where the others are hovering in the small integers. That's not the same thing as a true safety advantage (though I'll buy that they're way ahead technologically).
Once those self-driving systems hit around ~99.99% reliability, they will be indistinguishable from each other. Therefore, self-driving systems will be commoditized and sold to any vehicle manufacturer. Generally speaking, existing Tier 1/2 suppliers already plan to do this.
From there, anyone with $25M can probably just lease a bunch of vehicles, software, parking space and routing software to launch a regional TNC. Given a single region focus, these new regional TNCs should be able to outcompete Uber/Lyft. Remember that Uber/Lyft's greatest advantage is their supply of drivers; riders will happily download an app that delivers cheaper rides.
Today, it doesn't make sense to build core self-driving technology unless you have a strong resume to do so. Just wait 4-5 years and you'll be able to buy it off the rack (more or less). I am very happy that Waymo isn't the only one building because otherwise we wouldn't have strong enough market forces to drive down the cost of mobility.
Disclaimer: Founder of an AV related startup.
If you are willing to lose money like uber was, why wouldn't you be able to launch a competitor with drivers? I bet drivers would download a new app to make more money even faster than passengers would download such an app to save money.
I mean, if anything, a system where you own (or lease in an inflexible way) the cars makes your up-front costs higher; I think new driver incentives right now are on the order of a few grand; a lot less than the cost of a new car with top-end tech. I mean, double the signup bonuses of uber, and you'll quickly get drivers to open your app, and you've still spent a lot less up-front.
Of course, your long-term profitability looks a lot better if you can just own the cars, but make no mistake about it; uber's moat is that you have to lose money at first to build up a critical mass of vehicles (and that uber is willing to continue to operate at a loss)
Directly owning/leasing the vehicles rather than paying owner-operators per mile might be cheaper long term, but it doesn't lower the up-front cost of getting a critical mass of vehicles on the road.
My only guess would be Toyota is hoping that when Uber goes full self-driving they would use Toyota vehicles to do it.
A large investment in a potentially very large future customer.
Would Boeing invest money in an autonomous flight project by Southwest Airlines in hopes of locking in a Boeing 737 only fleet?
To summarize what happened - Uber's autopilot makes decisions about when emergency braking is necessary. But the software was braking so often on public roads that overall it's driving was erratic.
So Uber knowingly disabled emergency braking in all cases.
This essentially turned the car into a missile on our public roads.
at the time of the accident, the autopilot detected the pedestrian. Calculated an imminent collision, and initiated emergency braking. Instead of actually breaking, the message to break simply went to the logs.
Combine that with a safety driver that was looking down at the console and not up at the road - and the fatality was the result.
--
It is completely beyond me why there isn't a battery of government saftey tests that vehicles with autopilot must pass before they get approved for use on our public roads.
How many times have you seen footage of a crash test dummy safely landing in an air bag? I want to see footage of crash test dummies getting pushed out in front of autopilot cars - and hopefully, never getting run down.
Because the inefficiencies of government are catching up with them as they'd rather right each other (different parties) rather than be productive and move the country forward.
You misspelled lobbing.
You misspelled lobbying.
Ah well, I'm nobody anyway, just a guy hungry to see tech companies compete and see less of tech being monopolized between a few companies.
It appears that autonomous vehicle progress has an interesting moat where being good at it (the ability to drive a lot of miles) allows you to get better faster (drive more miles, more quickly). It is similar to a network effect, but with competency rather than number of connections.
Does anyone have a name for this type of advantage, or know of examples in other areas?
This doesn't seem to be the case. Look at the California disengagement statistics over cumulative miles - it looks like it's logarithmic or something, certainly not accelerating. Or look at Waymo in Arizona: they are driving, what, 70,000 miles per month and have racked up cumulative millions there already; if there really were some sort of compound interest or exponential improvement, then after they solved it well enough to go live and started racking up all those miles, self-driving cars should be on the verge of being solved & going global unless you postulate an enormous distance in between 'good enough to drive customers around Arizona' and 'good enough to drive customers around everywhere'.
http://www.safetyresearch.net/blog/articles/tipping-point
Edit: I see this is addressed in updates to the Revisionist History posting, in PDF form.
This is especially true for high technology projects, and only becoming more of a risk as technology becomes more complex.
Can totally see it happening with something like self-driving cars, which is currently still a black art (remember how even Uber apparently needed to filch some IP from Waymo to even get its own project going?)
Any proof? I see a settlement but not an admission or proof of guilt by Uber (not saying the former Google employee wasn't dirty). https://www.theverge.com/2018/2/9/16995254/waymo-uber-lawsui...
"Driver error or pedal misapplication was found responsible for most of the incidents.[28] The report ended stating, "Our conclusion is Toyota's problems were mechanical, not electrical." This included sticking accelerator pedals, and pedals caught under floor mats."
And Malcolm Gladwell's podcast about the subject, http://revisionisthistory.com/episodes/08-blame-game
http://www.latimes.com/local/california/la-fi-toyota-prius-i...
https://en.wikipedia.org/wiki/Michael_Barr_(software_enginee...
T-SB-0172-09
I love the concept of electrical cars but that has to come with a leap forward in software quality and electrical engineering quality, which I am not really seeing happen.
The idea of Quality is still, basically, alien in the software field. Some of that can be blamed on 'the marketplace' but then again, I believe that if people are going to call themselves "Engineers" they should take up that old mantle of the public responsibility inherent in that title, as it was developed after much blood and horror was spilled over the failed bridges and railroads of the 19th century.
If Uber's thesis - that app-hailing will supplant car ownership - is correct, then car manufacturers have an incentive to either create their own hailing networks or partner with existing ones.
https://www.sec.gov/Archives/edgar/data/1094517/000119312518...
> As filed with the U.S. Securities and Exchange Commission on June 25, 2018
> Toyota and Uber Technologies, Inc. have entered into a memorandum of understanding to explore collaboration with respect to ridesharing. As part of the partnership, the companies created new leasing options in which car purchasers can lease vehicles with connected terminals from Toyota Financial Services and cover their payments through earnings generated as Uber drivers
So not their first rodeo, Toyota sells cars after all
Also Toyota Connected is making quite a big splash in Europe at the moment with a London office having been established March 2018 to soak up local talent.
This is a Toyota self-driving vehicle in 2014: https://www.youtube.com/watch?v=x5Qey8ksE18
I think Uber self-driving initiative got serious around 2015.
https://www.freep.com/story/money/cars/2016/05/24/toyota-inv...
As someone who frequently commutes in Teslas, I would say Tesla is closest to actually deploying something close to self-driving to the general population out of all the current self-driving competitors. Furthermore, I imagine they're collecting data on all the Tesla cars currently being driven.
I have seen the model updates substantially improve the auto-pilot capabilities with every update. And as someone who works with lots of quantitative data on a daily basis, I think there is a fundamental difference between training on billions of miles of simulated data vs. actual data. Simulated data may reduce overfitting, but there is still scope to overfit compared to raw data gathered from the field. Simply put, you won't generalize as well to data that's been simulated vs. field-generated data.
This is not for certain. I'm quoting Tesla's CEO, but it's suggested that LIDAR leads to optimizing for local minima. It means that LIDAR can get you 90% of the way there, but there's still going to be a lot of situations where LIDAR might not be capable.
The problem that needs to be solved is vision. Humans only have vision, and they can drive with it. Radar and LIDAR are nice-to-haves, but until you solve vision, you haven't solved self driving.
I'm saying that if you _do_ need LIDAR, a training data set without it ain't worth much, no matter how large it may be.
"Solving vision" is a 10x more harder problem than building a practical self-driving car with LIDAR. We might get it working with LIDAR in 2-5 years, but without LIDAR in 20-50 years.
Arguably Alphabet (Google + Waymo + Deepmind + co) is the largest group of AI and ML experts in the world. If someone is going to figure out general computer vision, then it's likely to be them - and if they are working on LIDAR first then there must be a good reason why.
I believe Tesla is promoting LIDAR-less systems just because it's expensive bulky hardware, and they can't possibly sell cars with it at a reasonable cost. Calling cameras and radars "full self-driving hardware" is a good marketing tactic, but without any guarantees that they can build the software for it in the next 20 years.
It's easy to make a demo with cameras only but to deal with the countless unimaginable edge cases, you need LIDAR.
The other factor is that you need damn near six sigma accuracy for ML algos for robust SDCs, and while it's theoretically possible to match LIDAR with cameras and current DL, it's impossible to do so with the needed 99.99 percent accuracy for autonomy.
Ah yes, the famously practical and emotionally stable CEO.
You might be interested to know that the last Tesla crash in California was pretty much directly caused by lack of LIDAR
We fitted keyboard onto our screens, AR devices normally come with a joystick or something.
I have high hopes for similar projects to Tap Keyboard or the Myo armband, that continue to evolve on something that IMO has large implications on how we can evolve as a society the same way smartphones did. A wearable input device that was _good_ (defined by not being cumbersome, probably even fashionable and functional, as should match current input) would be for me the extra step .
There have also been various alternate input styles for phones but nothing's ever taken off.
I mean, if you could use a pen and paper to interface with a computer, you're standing on the shoulders of centuries of experience about how to produce a nice pen-paper experience, at a really cheap price. A newcomer in the world of interface hardware has to overcome the fact that everybody finds a new interface horrible for years, aside from the crazy technical and industrial challenges of producing something at a price/performance ratio that's better than entrenched technologies.
Uber is a thing that should exist. Profitable or not.
Software is the most unreliable thing that most people use regularly.
Combinging the two is kind of crazy. Especially since no one has even begun to demonstrate a self driving car that can handle inclimate weather (like, say, the 5 months of snow covered pavement for a large part of the USA).
This seems to indicate the complete lack of progress on this front. This'd not be surprising. I think Renault Nissan is the only one with a working system.
It's a hard to predict future. There is at least some possibility that driverless will eat a market fast, and the market changes for car makers. They need a hedge.
Overall though... how much money is going in to autonomous r&d? It's also possible that driverless doesn't get to the making money part for a long time. Is the funding sustainable?
So I don't find this "investment" very surprising at all.
Uber and Cruise kind of feel like that. I'm sure Waymo has a bottomless pit from Google too. I guess that's the reality of moonshot projects.
A lot of them are going to burn billions of dollars throwing lavish office parties and off sites, but one of them will be huge. That's essentially what SoftBank's 100B vision fund is kind of doing.
A lot of investors operate with a "fear of missing out" syndrome and that's probably why Uber gets more funding than 99% of all US startups combined.
Uber looks like it is behind it's competitors.
Uber is a company that I just hate. It doesn't have any ethics whatsoever.