Bruce Scott, the co-founder of Oracle says, “I remember Larry very distinctly telling me one time: Bruce, we can’t be successful unless we lie to customers.” And adds: “All the things that you would read in books of somebody being a leader, he wasn’t. But he was tenacious; he would never give up on anything.” [0]
Elon stretches the truth constantly. Should be a good fit.
That's putting it gently. Putting aside his twitter spats, Tesla is still prominently advertising "Full Self-Driving Hardware on All Cars"[0] even though their cars do not contain LIDAR, which essentially every expert in the field unconnected to Tesla seems to agree is necessary to implement Level 5 self driving cars[1][2].
Level 5 self driving is still theoretical at this point, and theoretically speaking, there is no reason to assume LIDAR is absolutely necessary for it. Computer vision based pipelines are theoretically capable of providing the same depth information as LIDAR, using stereo, camera arrays or even monocular SLAM.
The main obstacle for self-driving car is much more on the processing side than on the sensor side. After all, humans are able to drive with audio + stereo vision that's not even 360 degrees.
It could very well be that the reason Tesla's statement about "full self-driving car HW" is inaccurate is because of the lack of sufficient onboard computing power rather than the lack of sensors (IIRC they have an Nvidia X2 and GP106 onboard, which only have a total of about 4 SPFP TFLOPs).
No matter which way you slice it, Tesla should not be claiming the hardware required is present if the hardware requirements are, at best, theoretical.
They've given themselves enough wiggle room to never roll out Level 5 automation (and thus never admit they were wrong about what hardware it would require.)
>"Please note that Self-Driving functionality is dependent upon extensive software validation and regulatory approval, which may vary widely by jurisdiction. It is not possible to know exactly when each element of the functionality described above will be available, as this is highly dependent on local regulatory approval."
Tesla will in some form, though it’s hard to guess what color the money will be from the outside. It would be a goodwill jesture, so probably out of a marketing, customer retention or warrenty account.
If they upgrade hardware more than once I would worry about where the money came from.
>"Computer vision based pipelines are theoretically capable of providing the same depth information as LIDAR, using stereo, camera arrays or even monocular SLAM."
Are there any companies that are taking the purely computer vision approach then?
>"(IIRC they have an Nvidia X2 and GP106 onboard, which only have a total of about 4 SPFP TFLOPs)."
Can you say how far off is that compute power from what is actually required for a "full self-driving" car?
Human eyes don't work anything like cameras. The eye processes information that isn't just intensities of photons and their wave lengths—which is the only information collected by cameras. See Walter Pitt's "What the Frog Eyes Tell the Frog Brain" for an introduction: 'Fundamentally it shows that the eye speaks to the brain in a language already highly organized and interpreted, instead of transmitting some more or less accurate copy of the distribution of light on the receptors.'
A simple abstraction here: we put two high-quality monitors before our eyes and get all the data from them. Can we continue driving this way? Absolutely. This means that no matter how our eyes actually work, an array of RGB pixels is enough. I'd go further and say that a 64 x 64 grayscale camera at 10 fps is enough to drive a car. The real magic happens in the brain that reconstructs the 3D model and predicts what happens next.
> "64 x 64 grayscale camera at 10 fps is enough to drive a car."
If you had vision that bad, the State of California would not let you get a drivers license, they require at least one of your eyes to be 20/40. Anyway, the point of the GP is that the brain isn't the only piece of wetware doing image processing, but more to the point the current state of the art CV really is not up to the task.
And it really doesn't seem like it's going to be there anytime soon.
That is an analogy not an abstraction but if you had read the paper or the single quote I provided, you would know that even relatively simple eyes (such as those of the frogs which cannot see still objects) don't only process a distribution of light intensity and frequency. The eye measures other information that is lost by the camera including photon phase, arrival time, polarization, orbital angular momentum, linear momentum, and probably many more measurements. More so, this is done by specialized organelles of the eye rather than by the brain.
Humans can do a lot of things we don't understand how to convince software (...or other humans who don't intrinsically learn it very well) to do.
Lidar lets you get a high degree of accuracy for certain variables in your model - because you can know fairly accurately when and how strong the signal you sent out is, you can have a fairly high degree of confidence when you get reflection of how far away the object is, and feed that into your persistent idea of the world, versus having to use a bunch of heuristics to try and extract that from purely audiovisual data.
(That's my understanding, at least - I don't work in that industry.)
A good way IMO to think about it is by looking at airplanes. Birds fly by flapping their wings to generate thrust, but planes use turbines to generate thrust.
Just because humans use vision to drive, doesn't mean that we should restrict ourselves to vision for cars. Also, as another comment points out, our visual system does a lot more than just 'see' in the literal light/color processing sense that a camera does
Tesla's marketing team wants people buying cars to believe their Tesla will support Level 5 automation sometime within the usable lifespan of that car. They're not bold enough to claim it's a near future inevitability, but they're leaving that implied possibility open to get consumers excited about it.
Google/Waymo has obviously been throwing a ton of resources at nailing computer vision, their recaptcha that's plainly training such a system is doubtlessly just the publicly visible tip of an iceberg. Yet they're still investing into LIDAR as well. If Google/Waymo is bearish on a pure CV solution, I don't see any justification for Tesla thinking they can do it. Not in any near future.
LIDAR doesn't compute solutions, it's a sensor that gives you accurate information about the environment. Far more precise and accurate than any current computer vision system. What you do with that data is up to the rest of the system.
Elon has publicly trashed LIDAR plenty of times. I think you should treat his rants as defenses of his products' reputation, not earnest impartial engineering appraisals. If Elon were to admit that LIDAR will play a vital role in Level 5 automation, he'd be admitting that his company has been mistaken or lying for years. I think Elon's personality precludes him coming clean on something like this.
> "it's not enough to build a full self-driving vehicle."
As far as I know, nobody is trying to build a Level 5 system using only LIDAR. The serious teams who are working on this problem are all using LIDAR in addition to cameras and radars. LIDAR can't read a street sign; cameras and computer vision will obviously play an important role in Level 5 systems for that reason and more. But the teams that aren't trying to use automation hype to sell luxury cars don't share Elon's enthusiasm for CV/radar with no LIDAR.
> their cars do not contain LIDAR, which essentially every expert in the field unconnected to Tesla seems to agree is necessary to implement Level 5 self driving cars
Calm down a second.
Elon/Tesla are trying to do things differently/do things that other people are not or think can't be done.
To name a few"
Every "export in the field" said you can't land an orbital class booster vertically.
Every "expert in the field" has not figured out how to save billions and years digging tunnels.
Every "expert in the field" seems to design electric cars that look like a cartoon joke.
Every "expert in the field" was pretty sure Tesla could never be profitable.
Don't confuse "has never been done before" with "Can't be done". Let the results speak for what's possible.
Besides, the fact that I can drive my car relying primarily on two eyes and a brain suggests that it must be possible to extract and process the information to drive a car with stereo vision, and without LIDAR. LIDAR may become cheap and small enough that it should be added purely from a safety perspective - more better information is better. However, I think plenty of experts would agree that theoretically it is possible without.
Even if they can make it work, they note that Tesla's hardware is still inadequate. Tesla boast 8 cameras providing 360 degree coverage, but the authors of that paper are unimpressed:
>"The autopilot feature [19] in cars produced by Tesla Motors enables autonomous driving on highways through a combination of a forward-looking camera and radar. Due to the limited field-of-view, these cars cannot execute autonomous driving in cities which require surround perception."
So while you may have found some experts who think Level 5 automation can be done using only CV, you've only reinforced my main point that Elon Musk is not a trustworthy person.
I'm saying that when you ask people not getting a paycheck from Tesla, they say that LIDAR is required. Very notably including Mobileye, who severed their connection with Tesla over this disagreement. Mobileye is particularly notable since they invested heavily into camera-only solutions; Mobileye has a strong financial incentive to dismiss LIDAR, yet they don't.
It's obvious why Tesla doesn't either put LIDAR in all their cars or remove the self driving hardware claims from their advertising; Elon wants to have his cake and eat it too.
More from mobileye:
> Level 3 – Autonomous Under Certain Circumstances [...] Mobileye expects this additional redundancy to be covered by additional sensors like radar and lidar (for shape and object detection) and by Mobileye’s REM™ localization map for identification of safe drivable paths and knowledge of intersections and other traffic signage or instructions.
Harsher words than mine, from GM’s director of autonomous vehicle integration Scott Miller:
>“The level of technology and knowing what it takes to do the mission, to say you can be a full Level 5 with just cameras and radars is not physically possible,” said Miller. He went on to add that Musk is “full of crap.”
An article about the angular resolution limitations of radar (overcoming this is exactly what LIDAR is for):
>Raj Rajkumar, who researches autonomous driving at Carnegie Mellon University, thinks those assumptions concern one of Tesla's key sensors. “The radars they use are apparently meant for detecting moving objects (as typically used in adaptive cruise control systems), and seem to be not very good in detecting stationary objects," he says.
>That's not nearly as crazy as it may seem. Radar knows the speed of any object it sees, and is also simple, cheap, robust, and easy to build into a front bumper. But it also detects lots of things a car rolling down the highway needn't worry about, like overhead highway signs, loose hubcaps, or speed limit signs. So engineers make a choice, telling the car to ignore these things and keep its eyes on the other cars on the road: They program the system to focus on the stuff that's moving.
If you search around for this, you'll find there are A LOT of people calling BS on Tesla's claims that cameras and radar are adequate sensors for Level 5 automation. Tesla's website hints at none of this. The only caveats I see from them are concerning software and regulation:
>Please note that Self-Driving functionality is dependent upon extensive software validation and regulatory approval, which may vary widely by jurisdiction. It is not possible to know exactly when each element of the functionality described above will be available, as this is highly dependent on local regulatory approval. Please note also that using a self-driving Tesla for car sharing and ride hailing for friends and family is fine, but doing so for revenue purposes will only be permissible on the Tesla Network, details of which will be released next year.
Required for what, the self driving cars that don't exist yet? Radar and computer vision is simply a separate approach, not a wrong one. Tesla is as much an expert in the field as anyone, given that, you know, they have the best self driving commercial product by far.
>"Required for what, the self driving cars that don't exist yet?"
Required for Level 5 automation. Tesla claims to be selling the required hardware, waiting only on the software and legislation allowing it. All other players in this field are focusing on a combination of cameras, radar and LIDAR.
Since LIDAR is expensive and the self-driving hype is real, Tesla have a strong short term financial incentive to forgo the former while claiming to sell the later. Combine that with virtually every other expert in the field saying they're full of BS, and I think the picture becomes crystal clear. Elon covers for himself by promoting conspiracy theories about grand industry-wide plots to keep an underdog down, and that has worked very well for him so far. But like most conspiracy theories, this is one you should think critically about.
I work for an automotive tech company and have installed an L2 self driving system into my friends Camry, I don't think you've thought critically about this. LIDAR is currently a prohibitively expensive technology that provides a point map of the surrounding area. The LIDAR that Waymo uses is nearly as expensive as the car itself. This same point map can be done with computer vision/cameras, and good software. There are many other "experts" that think this is equally viable e.g. George Hotz at Comma AI or Anthony Levandowski at Pronto.
I am not opposed to LIDAR. I just think it is unnecessary and that computer vision is likely to get good enough before LIDAR gets cheap enough.
The last time I looked into it (which was admittedly a few months ago) Comma.ai was by their own admission a Level 2 system, and a somewhat sketchy one at that. While it's obviously really cool, it's a long way off from Level 5.
LIDAR currently being very expensive (and a bit bulky) is obviously the reason Tesla hasn't put LIDAR in their cars. I don't really fault them for that, I fault them for their deceptive advertising. The LIDAR industry has not yet progressed to the point where it makes sense to bring a car to market with hardware ready for Level 5 automation, so Tesla should stop claiming they've done so.
Assuming the current Level 5 automation hype doesn't fizzle then smoulder for decades like the AI craze of the 60s, then it's success will coincide with rapid advances in size and price of LIDAR.
I'm curious, because I honestly dont know, how does LIDAR perform in suboptimal environments such as heavy fog , a Midwest downpour or a blizzard? So far, everything I've read has these cars testing in sunny day (no pun intended) scenarios, with the worst environmental threat being night-time.
Every system known to man, including man, struggles in those sort of conditions.
But this is an important factor to consider when evaluating safety statistics. Humans operate cars in all sort of adverse conditions and human accident rates include accidents in those kind of conditions. Accident rates for autonomous systems that refuse to attempt operation under anything less than ideal conditions won't be directly comparable to human accident rates... but expect this to be glossed over by automotive marketing departments who will eagerly compare apples to oranges as soon as the opportunity presents itself.
This is basically my concern with the hype over automated driving. I live in the upper Midwest. 6 months or more of the year have unideal driving conditions. A purely autonomous vehicle is worthless to me if it can't get me to where I need to go half the time.
> But he was tenacious; he would never give up on anything.
To be fair, in my mind this is the one most common trait I find in successful entrepreneurs and leaders. I've seen leaders who I didn't think were particularly bright, or extroverted, or empathic, but man, did they not get stressed out by obstacles that came in their way. They either sidestepped them or overcame them, but they did not dwell on them and let those obstacles lead to self doubt.
This is one reason why I think sociopaths are over-represented in leadership positions. They are not burdened by a conscience that can lead to self doubt in times of stress. Of course, it's possible to have this "does not get discouraged by big obstacles" attitude and not be a sociopath, but it is certainly an area where sociopaths have a natural advantage.
I think there's a driver there that "the rest" of us just don't have. I enjoy an easy life. I don't want to work hard; that's not my driver in life. Therefore by this measure I will never be "successful".
Fortunately for me I'm happy with my own definition of "success".
Is it that they don't get stressed, or that they are great at hiding it to project an air of confidence at all times. And how would you tell the difference?
> Is it that they don't get stressed, or that they are great at hiding it to project an air of confidence at all times.
I wouldn't say it's that they don't get stressed, but that they are able to quickly compartmentalize it and move on without dwelling on it.
On the "are they just great at hiding" question, at least in my experience this isn't really possible. Personally, I have severe negative physical effects in response to long term, chronic stress. I sleep poorly, get severe intestinal issues, etc. At some point it becomes pretty impossible for me to just "hide it" - I'd LOVE to be able to quiet my body's physiological responses, but I'm just not capable. In seeing how some of my colleagues dealt with the same stressors, I can assure you they weren't just "hiding it" - if they were experiencing the same physical effects I was, at some point it would have been impossible to hide.
I agree but I'd like to add that in my opinion "successful" is probably quite risky to use in general, meaning that there are multiple levels (e.g. successful for yourself, for the company/government, for the investors/people, for the future maintainability, etc...) and timelines (e.g. now, in 1 year, in 10 years, ...). For example Stephen Elop can probably be considered "successful" as having managed to be CEO of Nokia for a while, but not the same could be said for the company itself (not sure about its investors)?
In any case I think that it would be safe to say that sociopaths have at least the embedded advantage of being "quicker", as they most probably ponder less than other people about in/direct consequences of their actions.
Agreed. I was referring to people that are able to get to the top of their games because they are able to "get shit done." Whether that shit is good or bad is another issue entirely.
Without getting too political, take Donald Trump, who in my mind kind of exemplifies this definition of success. Whatever your thoughts about Trump, he's definitely not lazy, and his early morning tweet storms seem to signify that he gets by on little to no sleep. Of course, he may cause WWIII in the process.
I hear this a lot, and while I generally agree with it, I feel like it ignores the significant counterexamples. You can argue whether Elon Musk and Steve Jobs were good leaders, but I think it's difficult to argue they weren't able to accomplish something uniquely remarkable. In my experience, good leaders may not micromanage but the best leaders are able to, and often do, "get into the weeds" and are actually able to understand and act on the nitty-gritty details even better than the people doing those jobs.
Whenever I hear those names I personally link immediately Elon Musk to "genuinely enthusiastic & a bit crazy", but in the case of Larry Ellison I get only "dark side"-thoughts... .
Edit: I would be absolutely interested in hearing Larry's wished next steps, but I don't think that board members usually release statements (I think that they only "steer" the CEO, help "facilitating" whenever issues arise and perform overseeing activities), right?
They do whatever the bylaws of the corp allow/require them to do, but yes, in general they are steering thr CxOs. And if we hear anything about what he says/does it'll be through Elon, I guess.
Larry Ellison is a visionary. Seems like all visionaries have been called liars by some. Steve Jobs is said to have had a “reality distortion field”. Elon Musk is a visionary. Are they all “liars” or do “visions” seem like stretching of the truth to us? Are visions simply extensions of the “truth”?
Where should I start? Ellison made the first commercial implementation of SQL. (Granted, Ellison didn't invent SQL, but he instantly recognized the importance of it and made it commercially successful, just like Steve Jobs didn't invent graphical interfaces, but instantly recognized its importance when he saw it Xerox Parc.)
Ellison has been talking about what he called "Network Computing" since the mid 1990s. He said "We need computers that do less not more". He was laughed at and ridiculed, but today Chromebooks are the implementation of his "Network Computer" vision. "Computers that do less" are now a reality.
What we know today as "cloud computing" was first envisioned by Ellison in the mid 1990s. He called it "network computing". He talked about why it is important to "centralize complexity" and keep the end-user devices simple. Meanwhile Steve Ballmer was touting the "power of the local hard drive". Ellison's vision seems like commonsense today, but it wasn't back then.
There are lots of other things. For example he was the first to move Enterprise applications to the Web when web-based applications weren't a thing yet. Oracle Parallel Server was his idea. He even wrote the first implementation himself.
I think you'll find that Ellison's "vision" of network computing was literally acquired when Oracle bought Sun Microsystems. Sun's fifth employee, John Gage, coined the phrase "the network is the computer" in 1984 [0].
Ken Olsen (Digital Equipment Corp) is also reputed to have shared this view as far back as 1987 [1].
>I think you'll find that Ellison's "vision" of network computing was literally acquired when Oracle bought Sun Microsystems.
That’s incorrect. Acquisition of Sun cane much later. “Network is the computer” is very different from Ellison’s Network Computing because in Ellison’s vision complexity is centralized and end-user devices are glorified dumb terminals which is very different from Sun’s “Network is the computer”
He wanted to buy Apple just to be able to put Steve Jobs back in charge. He did not/could not buy it, but was given a board seat when Jobs was back. I remember him speaking very clearly at MacWorld about what Apple should do next.
Elon stretches the truth constantly. Should be a good fit.
[0]: https://techcrunch.com/2010/12/01/larry-ellison-hearsay-we-c...