We saw this with the Nest folks, which was really a shell company that hired as many talented folks from Apple as possible, built a product, and then put themselves up for sale in the valley: either back to Apple or to Google.
This basically makes joining one of these startups a no-risk opportunity: huge upside if the thing you build actually works out, slide into a bigco job again if it doesn't...
It's been a pattern for a long time. I remember lot of startups back in the 90s built without any conceivable purpose or goal besides "being bought by Microsoft".
I've always thought it would be a great (albeit risky) way for someone who is talented but stuck in a go-nowhere job to get a nice bonus and/or raise:
1. Quit your job doing X
2. Found a company to do some related Y
3. A year layer or so, get purchased by your old company for the technology.
It's also an alternative way to get a new job somewhere where you can't seem to get through the interview funnel. I'd imagine that at some Silicon Valley companies it's easier to get acquired than get hired.
I see parallels between this and lobbying in the US government where lobbied officials will leave for a private sector position as a lobbyist or executive at say a $BIG_TELCO or $BIG_OIL company. Why shouldn't government professionals use their knowledge and expertise to get more leverage going into the private sector?
I think the biggest argument here is that sometimes the end goal becomes not the work that person is currently doing but the payout down the road if their actions line up in a certain way. If your goal at Google is to leave in three years and start a self driving car-company to get acqui-hired, you might for instance spend three years making lists of people to take with you or knowledge that won't violate NDAs or whatever. Though often times that might be acceptable, a.k.a. the 'you don't owe your employer anything' line of logic (which generally I agree with), sometimes it can become morally dubious if for example, it corrupts personal relationships or becomes manipulative.
And then finally you get the case of the Waymo guy who may have planned and conspired to steal information on his way out the door, ironically after having already gained multi-generational wealth.
To your first point, because being part of a government is something you should ideally be doing for a non-monetary altruistic reason, whereas employment at a large corp is clearly about personal gain.
In a vacuum, this isn't a problem. In practice, what you have is people regulating and creating laws for their future employer, and/or legal bribery (knowing you'll get a cushy job for supporting a bill). At this point, you aren't leveraging your knowledge, you are abusing your power.
The bet on maps is interesting. I'm of the personal opinion that in the long run only machine learning can solve autonomous driving, but both MobilEye and now this company both have invested heavily into maps.
MobilEye makes sense, they have vested financial reasons that dictate what they do, so they can't turn their back on maps which they've been using for such a long time.
On the other hand, starting a company in maps for self driving cars, especially by what appears to be industry veterans, is far more interesting.
Cruise (now part of GM) also relies heavily on maps, based on a talk I saw their lead CV guy make. It does make a good deal of sense - maps (at least street-maps) are mostly static and they make the problem way easier, so why not use them. In fact, most people these days are implicitly using maps - how often do people drive to new places without GPS navigation? Of course, vision and likely ML are still a necessary part of the equation.
> "In fact, most people these days are implicitly using maps - how often do people drive to new places without GPS navigation?"
I'd argue also they're using maps in an even more fundamental way - most driving occurs in places where the driver has already been, and relying on a wetware-stored map is a critical part of safe and effective driving.
Local knowledge - traffic patterns, weird traffic signal setups, difficult lane changes, etc, is pretty critical to driving well.
If I have been to the destination multiple of times, I usually don't open map, I leave my phone off, or I let Pokemon Go running. But sometimes I do use map to seek for alternate faster route if I am in a hurry even if I am familiar with some alternate routes just to be sure.
Since I don't use Waze (horrible experience), Google Map won't tell me there's a camera ahead, or police is ahead.
Right - I may have phrased my point badly. The idea is that all effective driving relies on pre-mapping, either via digital means (your phone) or human means (your brain).
The expectation that self-driving can be perfected without any kind of pre-mapping and the system can behave at high reliably in-situ seems unreasonable. Even humans can't do that.
The betting is not only interesting, but actually an excellent bet, in fact, very strategic. Learning to drive is only part of the formulas. As I stated this probably 10th time on HN, we need real data about road condition in order to make self-driving really successful. DeepMap is only part that solution, but we still need real data in real time. We need a real network communication in the transportation space. Take flight control, instead of having a person coordinating, we can make computer programs to do that coordination; now apply that to driving. This is not only a data challenge (because there is very little authentic data to collect from to begin with), but also a huge challenge in network communication.
Minimum Viable Product. He means that until self driving cars are not even as good as human drivers, it is pointless to discuss features that make them even better than human drivers. I.e. "one step at the time".
Well it probably is, but it would be too late if we don't start investing into the data collection. Convincing government to build infrastructure and services what I am suggesting is going to be a long investment. I know some states are working on toward that goal, and IBM's SmartCity project is one such example experimenting how to use technology to allow services to subscribe to data.
We have a MVP. Google has a MVP, Telsa is a MVP already. I feel we focus too much on building sensors.
Again, I never said we don't need good sensor. I have been saying we need to start thinking outside of just sensor. The forumla can't just rely on sensors alone. I don't dispute we need to be able to recongize surroundings. Because we human drive with eyes open.
We humans also do fine with a our eyes, our brain, and a crappy GPS or Map. If you want to say that's not enough for computers and you need really good maps to get level 5 automation then I disagree. If you think you can be first to market with Level 5 automation while splitting your focus onto irrelevant details, again I disagree.
Your view on self-driving car is different than mine. I am not sure who came up with the five levels of self-driving car automation, but let me reiterate the last time before I give up trying to convince anyone on this thread.
First, for a computer to be able to navigate safely on the road the computer needs to be able to recongize and understand its surroundings. Checked.
Next, for computers to be able to be good at driving, we need to train the computer both in the real world and in simulations.
Moreover, to ensure we can optimize route, plan ahead we need data about road condition far ahead of us (and sometimes behind us). To be able to make turns on an intersection safely and swiftly, unlike humans who are terrible at making turns and confusing when to turn, computers can coordinate with one another. This requires good network communication. Bluetooth is weak and unstable. In my earlier example, if an ambulance says it is driving heading my direction, my car can coordinate how to empty up a lane for the ambluance to pass. This level of automation is what one sees in a sci-fi movie, which is really what you want besides being able to avoid obstacles like Bat mobile.
My point is, we should explore how to make traffic data accessible. There is so much one can do with such data. It takes a good amount of time to get the government onboard and help them build such infrastructure. To finish off my point, meter data is not available, right now apps use crowd source to determine whether a parking spot is available or not. Instead of driving around which causes
more congestion and sometimes accident, governement should make meter data available, and we can still crowd source by using driver's camera to recongize whether a spot is opened and send back to datastore.
This is essentially the goal of Internet of Things, at rhe city scale. As I mentioned, IBM's SmartCities supposed to do stuff above but I really am not sure if IBM will ever pull off given many of their projects ended up on someoen's desk covering in dust.
Trafic analysis based on cellphone tracking is already part of free GPS apps like: https://itunes.apple.com/us/app/waze-gps-navigation-maps-soc... Even one user per 100 drivers is plenty to locate traffic issues and we are well past that. Now sure, the situation is improvable but the reality is knowing about bad traffic is more or less solved.
For higher precision tragic flow that's going to fail while their is still a high percentage of human drivers. So sure when there are 50+% AI drivers it's a useful optimization. However, for the first decade or so it's not going to happen making it a waste of time for now.
As to finding a parking space, again mostly a non issue for self driving cars, because they don't need to park near people they are better off going to a garage which already tracks open spaces than using street level parking when it's hard to find. Can you slightly optimize this sure, but again it's not a hard problem relative to driving without a person in the car.
Every car could observe its environment, refer to the map, and send back any conflicting information to DeepMap, so that the map database would be updated in real-time, and pushed to all cars in the area.
Not quite. We need data from toll, from government on planned events, getting data about where emergnecy vehicles are going. Obseving environmebt is only as reliable as the recongition. For example if I knew ambluancs is coming from behind I would pull over. But often this is last minute reaction and often we can barely make way for ambluancs. However, if dispatcher publishes signal and ambluance publishes its GPS then cars where the ambluance is heading can get that data in advance and calculate how far and when to pull over. Relying on doppler effect to calculate siren then get twenty cars to slow down is not a great design.
When companies pay each engineer X and earn 10 times X on each engineer, this is inevitable. Near as I can tell, this is a strategy that is helping engineers retain more of the value they are creating.
If the difference was more subtle such as 2 to 3 times X, then the incentive to go through this much trouble to retain much of the value you create is much smaller.
nit: self-driving talent doesn't currently earn anything, but rather holds some long-term strategic value
I would summarize this effect as BigCorp HR being much more disciplined/constrained on individual compensation than the M&A department. Naturally, well-positioned and clever employees will capitalize on this.
In light of this observation, Google's current lawsuit could be viewed as an attempt to deter employee defection by signaling liabilities for potential acquirers, which will suppress the valuation of any acquisition.
Google was already at the center of the high-tech employee wage-fixing earlier this decade, so filing lawsuits to create deterrence wouldn't be that surprising.
either way, google needs to tread carefully. more people are starting to recognize google as a monopoly, and if that continues they will either be broken up or turned into a utility.
Wasn't Google recently on the opposite end of this? They paid their engineers so much that some of them left because they had the financial security to take riskier options.
The logic on this statement doesn't really check out, as if this were the case it would be impossible to retain CEOs, they would all leave after a month. Yet somehow companies do so ...
At some point, the work becomes the hobby. If you had fyou money, what would you do? Presumably not sit and stare at a wall all day. You'd do something you enjoy I assume. And for some, running one of the world's most powerful entities is enjoyable.
lol, you know its not possible to learn everything! There is no "then what?". Then entropy catches up with us all and we die eating at The Restaurant At The End Of The Universe.
If your job involves hearing smart people talking to you about amazing ventures before getting into a fancy restaurant the night before you take a plane to some foreign headquarters it earned the right to be called a hobby.
If you have certain goals in life e.g. building certain large infrastructures, it might be beneficial to do these in an existing company than starting your own or doing it in a nonprofessional environment.
Plus, yes, there are other goals than "not working".
Because in most cases, your needs rise together with your salary. Once you start earning 200-500k/year, you just get a house/car/boat that costs nearly that much to maintain. Obviously there are people who keep their cost of living low and stash that money in a saving account so that after 10 years they can realistically stop working altogether, but that's not the pattern that I'm usually seeing.
> The logic on this statement doesn't really check out, as if this were the case it would be impossible to retain CEOs, they would all leave after a month.
Or, CEOs don't have the same set of options engineers have, or, CEOs are drawn from a pool with different preferences than engineers have, or...
Well, lots of other reasons your dismissal of the claim about engineers based on CEO behavior is unconvincing.
The general point is valid, though, and often comes up in discussions about basic income or similar programs: if the hypothesis is that someone whose needs are already met will refuse to work, then we can look at the existing population of people whose needs are already met as a way to verify the hypothesis. And we find the hypothesis is falsified by observation: some people who don't need to work don't work. Some people who don't need to work do work.
A lot of comments suggesting this is cynical compensation arbitrage by the DeepMap founders. I don't buy it.
I expect a startup was the only option to execute on the idea with a decent level of autonomy. Google/Alphabet already have well established teams in the areas of mapping & autonomous driving so you can't just go ahead and start your own multi-engineer effort.
From their website https://www.deepmap.ai/ it seems they are focusing on high-definition, centimeter-accuracy maps. Why is that important? It seems with a rough map and training, a robot can find its destination.
This might have changed since it's been a few years, but I think Google used to use high resolution 3D maps together with LIDAR on their cars to do accurate positioning. If I understood it correctly, it was basically a 3D pattern matching.
Traditional maps help a driver get from A to B over a long distance with the user being responsible for the details in between. These types of 3D lidar style maps are meant so the car knows detailed information about roads to inform minute details about the precise section of road to take, etc.
This kind of articulates a larger attitude I feel about startups in general - too many people are going for too much. Right now, a bunch of companies are going for too much of the metaphorical self-driving pie.
But, there's a lot of niches with less competition - yeah, the slice might be smaller, but I'd rather have a 90% chance at 10% of the pie than a 10% chance at 90% of the pie.
People need to corner some niche of the self driving X market then expand. Going for the whole pie is foolharder unless you already have name recognition.
Self driving cars will fundamentally change society. By the time we figure out self driving cars, we'll have enough tech for autonomous drones, trucks, planes, mail delivery bots, fork lifts, tractors.
I bet whoever capitalizes on this will end up becoming the world's most valuable company. This is a horse-> horseless transformation again.
> Self driving cars will fundamentally change society.
They said the same about internet shopping way back before the dot com bubble burst. There were hundreds of web-vans, but only one Amazon. I guess everyone thinks of themselves as the Amazon of self driving rather than CueCat[1].
Am I the only person genuinely shocked Google doesn't slap their self driving car engineers with non-competes?
I realize that non-competes are illegal by CA law, but perhaps they should do the engineering in a different state to stop hemorrhaging talent that tries to compete with them?
(1) When most of your existing operations are already in CA, moving to a different state isn't exactly trivial. And if the primary reason you're moving is to enforce a non-compete, I bet it'd make recruitment of the better engineers more difficult.
(2) Even if Google did their engineering in another state, let's say the engineer in question then moves to CA. There's a good chance that CA law would still apply.
#2 Really depends on how bad they want to come after you. There have been cases where non-competes originating out of state have been enforced here in California. I personally wouldn't want to go up against Google's legal team and their war chest.
It's exactly this type of thinking that lead to the decline of Route 128 in the post-war years and the rise of Silicon Valley. If Google were to do this, they'd be cutting off their nose to spite their face. They could not enforce such a contract with existing employees and all new employees would look at such a provision and join an employer who doesn't do this.
The truth is that Google lost this market (or never really had it to begin with). At best they will end up like Microsoft, simply extracting rent via their patent licensing program.
For more information about Route 128 vs Silicon Valley, I cannot recommend the book Regional Advantage by AnnaLee Saxenian enough. It's a bit dated and academic, but it's fascinating if you want to understand why the tech industry in and around Boston lost to Silicon Valley despite having a huge head start.
Or maybe Google should put out a self driving car product of some kind? They don't seem very business savvy at Google, imagine if they didn't have their ad revenue to fall back on.
> I realize that non-competes are illegal by CA law, but perhaps they should do the engineering in a different state to stop hemorrhaging talent that tries to compete with them?
Doing engineering in a different state might make it more problematic to attract talent, as might the non-competes separately.
OTOH, maybe Waymo needs to be spun off and be able to offer employees Waymo stock, so it can be a "high-upside startup" option for engineers.
A bit unrelated to the subject I have a question. As far as I know Google started self-driving tech development much earlier (?) than any other group. However Tesla did it in much quicker timeframe and it is used now as opposed to Google which is still in the lab (?). What took so long for Google? or there is some nuance from their competitors?
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[ 4.7 ms ] story [ 145 ms ] threadWe saw this with the Nest folks, which was really a shell company that hired as many talented folks from Apple as possible, built a product, and then put themselves up for sale in the valley: either back to Apple or to Google.
This basically makes joining one of these startups a no-risk opportunity: huge upside if the thing you build actually works out, slide into a bigco job again if it doesn't...
I've always thought it would be a great (albeit risky) way for someone who is talented but stuck in a go-nowhere job to get a nice bonus and/or raise:
1. Quit your job doing X
2. Found a company to do some related Y
3. A year layer or so, get purchased by your old company for the technology.
It's also an alternative way to get a new job somewhere where you can't seem to get through the interview funnel. I'd imagine that at some Silicon Valley companies it's easier to get acquired than get hired.
I think the biggest argument here is that sometimes the end goal becomes not the work that person is currently doing but the payout down the road if their actions line up in a certain way. If your goal at Google is to leave in three years and start a self driving car-company to get acqui-hired, you might for instance spend three years making lists of people to take with you or knowledge that won't violate NDAs or whatever. Though often times that might be acceptable, a.k.a. the 'you don't owe your employer anything' line of logic (which generally I agree with), sometimes it can become morally dubious if for example, it corrupts personal relationships or becomes manipulative.
And then finally you get the case of the Waymo guy who may have planned and conspired to steal information on his way out the door, ironically after having already gained multi-generational wealth.
MobilEye makes sense, they have vested financial reasons that dictate what they do, so they can't turn their back on maps which they've been using for such a long time.
On the other hand, starting a company in maps for self driving cars, especially by what appears to be industry veterans, is far more interesting.
I don't doubt that 2d maps would be needed like how humans drive with a GPS.
I'd argue also they're using maps in an even more fundamental way - most driving occurs in places where the driver has already been, and relying on a wetware-stored map is a critical part of safe and effective driving.
Local knowledge - traffic patterns, weird traffic signal setups, difficult lane changes, etc, is pretty critical to driving well.
Since I don't use Waze (horrible experience), Google Map won't tell me there's a camera ahead, or police is ahead.
The expectation that self-driving can be perfected without any kind of pre-mapping and the system can behave at high reliably in-situ seems unreasonable. Even humans can't do that.
We have a MVP. Google has a MVP, Telsa is a MVP already. I feel we focus too much on building sensors.
First, for a computer to be able to navigate safely on the road the computer needs to be able to recongize and understand its surroundings. Checked.
Next, for computers to be able to be good at driving, we need to train the computer both in the real world and in simulations.
Moreover, to ensure we can optimize route, plan ahead we need data about road condition far ahead of us (and sometimes behind us). To be able to make turns on an intersection safely and swiftly, unlike humans who are terrible at making turns and confusing when to turn, computers can coordinate with one another. This requires good network communication. Bluetooth is weak and unstable. In my earlier example, if an ambulance says it is driving heading my direction, my car can coordinate how to empty up a lane for the ambluance to pass. This level of automation is what one sees in a sci-fi movie, which is really what you want besides being able to avoid obstacles like Bat mobile.
My point is, we should explore how to make traffic data accessible. There is so much one can do with such data. It takes a good amount of time to get the government onboard and help them build such infrastructure. To finish off my point, meter data is not available, right now apps use crowd source to determine whether a parking spot is available or not. Instead of driving around which causes more congestion and sometimes accident, governement should make meter data available, and we can still crowd source by using driver's camera to recongize whether a spot is opened and send back to datastore.
This is essentially the goal of Internet of Things, at rhe city scale. As I mentioned, IBM's SmartCities supposed to do stuff above but I really am not sure if IBM will ever pull off given many of their projects ended up on someoen's desk covering in dust.
For higher precision tragic flow that's going to fail while their is still a high percentage of human drivers. So sure when there are 50+% AI drivers it's a useful optimization. However, for the first decade or so it's not going to happen making it a waste of time for now.
As to finding a parking space, again mostly a non issue for self driving cars, because they don't need to park near people they are better off going to a garage which already tracks open spaces than using street level parking when it's hard to find. Can you slightly optimize this sure, but again it's not a hard problem relative to driving without a person in the car.
If the difference was more subtle such as 2 to 3 times X, then the incentive to go through this much trouble to retain much of the value you create is much smaller.
I would summarize this effect as BigCorp HR being much more disciplined/constrained on individual compensation than the M&A department. Naturally, well-positioned and clever employees will capitalize on this.
Google was already at the center of the high-tech employee wage-fixing earlier this decade, so filing lawsuits to create deterrence wouldn't be that surprising.
https://en.wikipedia.org/wiki/High-Tech_Employee_Antitrust_L...
Between these, which do you think is more likely?
Learn everything.
I have a goal, it is to be better than average at every "skill".
Plus, yes, there are other goals than "not working".
Or, CEOs don't have the same set of options engineers have, or, CEOs are drawn from a pool with different preferences than engineers have, or...
Well, lots of other reasons your dismissal of the claim about engineers based on CEO behavior is unconvincing.
I expect a startup was the only option to execute on the idea with a decent level of autonomy. Google/Alphabet already have well established teams in the areas of mapping & autonomous driving so you can't just go ahead and start your own multi-engineer effort.
Has to be fascinating AND deflating if one of your data points was "holy shit we can make $700m in 6 months if we get a team + MVP out the door!".
But, there's a lot of niches with less competition - yeah, the slice might be smaller, but I'd rather have a 90% chance at 10% of the pie than a 10% chance at 90% of the pie.
I bet whoever capitalizes on this will end up becoming the world's most valuable company. This is a horse-> horseless transformation again.
They said the same about internet shopping way back before the dot com bubble burst. There were hundreds of web-vans, but only one Amazon. I guess everyone thinks of themselves as the Amazon of self driving rather than CueCat[1].
1. I'm embarrassed to say I badly wanted one. http://content.time.com/time/specials/packages/article/0,288...
I realize that non-competes are illegal by CA law, but perhaps they should do the engineering in a different state to stop hemorrhaging talent that tries to compete with them?
(2) Even if Google did their engineering in another state, let's say the engineer in question then moves to CA. There's a good chance that CA law would still apply.
The truth is that Google lost this market (or never really had it to begin with). At best they will end up like Microsoft, simply extracting rent via their patent licensing program.
For more information about Route 128 vs Silicon Valley, I cannot recommend the book Regional Advantage by AnnaLee Saxenian enough. It's a bit dated and academic, but it's fascinating if you want to understand why the tech industry in and around Boston lost to Silicon Valley despite having a huge head start.
Doing engineering in a different state might make it more problematic to attract talent, as might the non-competes separately.
OTOH, maybe Waymo needs to be spun off and be able to offer employees Waymo stock, so it can be a "high-upside startup" option for engineers.
https://www.linkedin.com/in/mark-wheeler-081882/