
The End of Starsky Robotics - stefan8r
https://medium.com/starsky-robotics-blog/the-end-of-starsky-robotics-acb8a6a8a5f5
======
cjv
This is sad news.

I worked at Starsky Robotics as a perception team intern after graduating high
school. I will always be grateful for the team for the opportunity, it was a
fantastic first job and everyone who worked there was very kind (especially
Stefan).

Unfortunately, Starsky had effectively had no machine learning in 2017 (when I
worked there), using solely classical computer vision techniques. This didn't
match the company's ambitions of not using LIDAR and there was a strong stigma
against switching to a deep learning approach. At the time, very few object
detection models had public implementations and I spent a lot of time trying
to get a YOLO9000 and RetinaNet implementations running at real-time speeds.
Frustrating, as a small startup the labeling services kept screwing us over by
returning poorly annotated images.

I think what I took away from the experience is that deep learning in domains
with long tails requires a enormous investment in a labeling pipeline -
dwarfing the computational aspect - to get decent results. I don't think any
solutions are on the horizon that will allow us to bypass this reality. You
don't see improvements between Comma.ai and Tesla because it's about the
improvements far out on the tail.

~~~
lioeters
For others like me who were as amused by the name, YOLO9000, it's a real
thing, "a state-of-the-art, real-time object detection system that can detect
over 9000 object categories".

YOLO9000: Better, Faster, Stronger -
[https://arxiv.org/abs/1612.08242](https://arxiv.org/abs/1612.08242) (2016)

~~~
nstj
YOLO = “You Only Look Once”

------
chubot
Thank you for the great writeup. It sounds like you took a responsible,
valuable, and even economically viable approach, but the market doesn't want
to hear it.

I wonder when the market will start listening to people who actually WORK on
the problem.

> _which means that no one should be betting a business on safe AI decision
> makers. The current companies who are will continue to drain momentum over
> the next two years_

Sounds about right.

\-----

Here's me over 2 years ago simply quoting people who worked close to the
problem:

[https://news.ycombinator.com/item?id=16353541](https://news.ycombinator.com/item?id=16353541)

 _Here 's my negative scenario: self-driving is "AI-complete"; you can't
really hit all the edge cases without solving AI in general, which is more
than 30 years away (Kurzweil is the wild optimist and predicts 2045)._

 _You CAN use self-driving in limited circumstances, but those limitations are
precisely the ones that make driving yourself around more attractive. The
expense doesn 't go down as quickly as anticipated because of this. They are a
niche technology for DECADES._

This looks about right, and I'm not claiming to be prescient, just basically
saying what Chris Urmson and Bill Gurley already said years ago. It's weird to
me that there's still so much money chasing this pipe dream.

It was a sign when Google spun out Waymo. If they really believed in the
product, it would be called something like "Google Self-Driving Cars", not
"Waymo".

\----

edit: it's easy to be negative, so on the positive (and contrarian) side, I
believe rideshare is undervalued, and has a long way to go. I bought both Uber
and Lyft stock at $16 yesterday (they may go down again, but ping me in 2
years). This comment in this thread is a nice take and makes me even more
optimistic:

[https://news.ycombinator.com/item?id=22631151](https://news.ycombinator.com/item?id=22631151)

~~~
chrisco255
I still think that AI shuttles and buses driving predetermined routes and
schedules would be tremendously useful. Especially if they could operate
continuously 24/7\. And that should be possible, with maybe tele-operators
dialing in to override the edge cases or sending dispatch crews to takeover
for any issues that come up.

~~~
chubot
How's Lyft Shuttle doing? (genuine question, I don't know)

[https://nymag.com/intelligencer/2017/06/lyft-reinvents-
the-b...](https://nymag.com/intelligencer/2017/06/lyft-reinvents-the-bus.html)

The point is that we already have self-driving vehicles. You press a button on
your phone and somebody drives you around. Whether it's a premium ride, a
shared ride, or a bus is an orthogonal issue to whether the driver is human,
which is a matter of cost.

The fact that it's a cost issue makes it look even worse and further out for
driverless.

If there is demand for a shuttle along predetermined routes, it would already
exist with a driver, and that's what Lyft Shuttle is if I understand
correctly. I haven't seen it in SF or heard of anyone using it. It's
definitely possible that they could figure out the product and it will become
popular, but that has little to do with self-driving.

~~~
IanCal
> The fact that it's a cost issue makes it look even worse and further out for
> driverless.

I see it the other way, they slot immediately and easily into already existing
businesses and if the only difference is cost consumers are likely to swap
over.

------
ssivark
> _There are too many problems with the AV industry to detail here [...] The
> biggest, however, is that supervised machine learning doesn’t live up to the
> hype [...] It’s widely understood that the hardest part of building AI is
> how it deals with situations that happen uncommonly, i.e. edge cases. In
> fact, the better your model, the harder it is to find robust data sets of
> novel edge cases. Additionally, the better your model, the more accurate the
> data you need to improve it. Rather than seeing exponential improvements in
> the quality of AI performance (a la Moore’s Law), we’re instead seeing
> exponential increases in the cost to improve AI systems_

This is _exactly_ the problem with data hungry machine learning approaches,
specifically deep learning (and that’s without even mentioning the compute
resources necessary to learn). The only way to circumvent that is plausibly
apply better inductive biases, and fundamentally rethink what the field
considers important.

~~~
Barrin92
I think the obvious problem is that induction (which is what learning from
data is), is simply only one tool in the huge space that is intelligence, and
it will never be enough to emulate the skill of a human driver, which is more
or less what is necessary for autonomy in an open environment.

~~~
ibeckermayer
The "induction" that machine learning algorithms do also isn't the same as the
induction that humans preform. We induce new concepts from experience (data)
-- The description itself assumes consciousness in both "concepts" and
"experience".

Thinking of computers as getting more "intelligent" like humans is a category
error -- computers are dumb matter configured in an intelligent way by actual
intelligence (humans) to preform certain tasks for us. We get better at
telling them how to preform certain tasks (software), but there's no reason to
think we're moving along some continuum of intelligence towards us.

~~~
visarga
> We induce new concepts from experience (data)

That's the premise of deep learning - inducing high level concepts from
experience, without manual feature engineering.

DL models are good at induction, what they can't handle is generalisation
(being accurate outside of distribution). And self driving has a long tail,
that's why it's so hard.

------
DanFeldman
Ah well, it was great while it lasted.

Most of the engineering team has spread throughout the AV industry, with most
folks going to our neighbors and fellow YC company Cruise Automation. Some are
at Waymo, Zoox, AutoX, and some purposefully exited the AV space entirely.

I joined Applied Intuition to help build out Simulation and Infra for other
companies producing AVs/robotics.

There are a few folks I know of who are still looking for their next roles in
the BizOps/PplOps side, which has been especially hard during COVID-19 season
if anyone wants to do some linkedin stalking.

~~~
KKKKkkkk1
_Most of the engineering team has spread throughout the AV industry, with most
folks going to our neighbors and fellow YC company Cruise Automation._

Sounds like most of the engineering team does not share the founder's
perspective on the AV industry.

~~~
jnwatson
I've worked for 2 hopeless industries. It doesn't prevent me from collecting a
paycheck.

------
cyanoacry
Thank you for the write-up! It's a little depressing (but not entirely
surprising) to hear that you couldn't get folks excited about safety -- I work
in the aerospace field, and our day-to-day is all about risk management: how,
why, when. It's frustrating that high-reliability systems aren't seen as
exciting when really they're what makes the magic run.

Best of luck, and I'm looking forward to your next venture!

~~~
smabie
Ironically, in my experience, finance is the field that probably cares most
about risk management. That and maybe healthcare (though less than you would
think, surprisingly).

------
csours
Disclaimer up front: I work for General Motors. I don't work on AV. Any
opinions are my own. I have no special knowledge of GM's AV strategy.

> It didn’t matter that that jump from “sometimes working” to statistically
> reliable was 10–1000x more work.

There's 2 states of functionality:

1) It doesn't work

2) It sometimes works

The inverse, for disk drives: Failing and Failed.

Think about apps/services. You could say that your app is working, but over a
long enough time period, it is only sometimes working. It's working while you
have disk space, free memory, and a working network connection. It's working
while your business assumptions hold true. It's working while your datacenter
has power. We've developed strategies for managing all of these things; for
load balancing and Active/Active hosting. But even with that, it only
sometimes works.

\---

With all that, I think it may be useful to think of self driving in terms of
tasks.

If you can put a box around what you expect a computer to be able to do, you
can define tasks that will always return a reasonable output.

The more tasks a computer handles, the easier it is for the human in control
(think driver assist, like lane keeping and automatic cruise control).

If you add enough tasks, and perform them well enough, maybe you can take the
human in control out of the vehicle.

I think I'm in agreement with the authors that I don't see the day when there
isn't a human in control. Or the other way to say that is that if there isn't
a human in control, sometimes your AV will just stop.

~~~
stefan8r
Just stopping is ok is ok in some use cases, but not others. It will be a long
time before robotaxis "just stop" less frequently than uberdrivers, but AV
trucks can already be more reliable than contemporary drivers.

------
edshiro
Thank you for sharing this very candid article on the Starsky Robotics and
generally the autonomous vehicle space. It's a real eye opener. I've been
following your progress for the last few years (and I also read about your
company through Reilly Brennan's "Trucks - FOT" newsletter).

I am sorry you could not get investors to believe more in what you and your
team, especially as you required a lot less funds than many other companies in
this arena. I also thought you had a clear business case (I worked in ride-
hailing and also logistics so understand some of the problems in this space).

I wanted to ask you a question: I am building a startup in the dash cam video
analysis space. We are building a large and geographically diverse dataset of
road videos, where our users can annotate/label the data. We then are going to
look at detecting specific events like accidents and edge cases on videos. Do
you feel this type of business, the data we collect, and insights we generate
would have value for a AV startup?

All the best in your next move. Stay strong - you can be proud of what you and
your team did.

~~~
stefan8r
Hard to say.

We had really strict rules on what we wanted our data to look like, and were
very specific about subject matter. We probably wouldn't have been able to be
a customer.

Our intention to deal with accidents/edge cases was that if anything looked
outside of ODD (as in, not perfect driving conditions) we'd execute a MRC
(pull to side of the road, or stop at next exit). Relatively easy way to solve
most of the really hard edge cases.

~~~
edshiro
Understood and makes total sense given the ODD at Starsky.

------
tnorthcutt
> Around November 12 of 2019, our $20m Series B fell apart. We furloughed most
> of the team on the 15th (probably the worst day of my life), and then
> started work on selling the company and making sure the team didn’t go
> without shelter (or visa status, or healthcare for the new and expectant
> parents). We were able to land many of the vulnerable jobs by the end of
> January and I’m in the process of selling the assets of the company (which
> includes a number of patents essential to operating unmanned vehicles). Like
> the captain of a sinking ship, I’ve gotten most of the crew on lifeboats and
> am now noticing the icy waters at my ankles while I start to think about
> what I do next.

Well done.

------
putroce
I’ve been developing software for self driving (both road and offroad) the
past two years and what I’ve noticed is that there isn’t much innovation in
the field. It seems like everyone follows the exact same design paradigm which
is using something like Autoware. It’s pretty disheartening to see how much
money has been poured into this field and what do we have out of it now? GM
Supercruise came out in like 2013 [0] with similar performance to the level of
autonomy we’re at in 2020. To clarify, this was in a production cadillac in
2013, so anyone who knows about automotive products knows how long this must
have been in development before they were allowed to put it in production.

To the author, it’s interesting to read how quick you rose and fell, but it’s
good you got out now instead of holding on for years and years.

What do you think is next?

I’m honestly tired of the lack of progress in self driving, and was wondering
what anyone’s thoughts were on home robotics. I feel like that’s the next big
thing that VC’s will pour billions into.

[0][https://media.gm.com/media/us/en/gm/news.detail.html/content...](https://media.gm.com/media/us/en/gm/news.detail.html/content/Pages/news/us/en/2013/Apr/0429-cadillac-
super-cruise.html)

------
jedberg
> Instead, the consensus has become that we’re at least 10 years away from
> self-driving cars.

I'm going to assume the founder of a self-driving truck company knows what
he's talking about.

But at the same time, I have a hard time reconciling that with the fact that I
sat in a car that drove itself all around San Francisco, dealing with a ton of
edge cases.

Maybe we won't get to a 100% drive-anywhere-you-want-car in 10 years, but to
be fair, a lot of humans aren't capable of driving a car anywhere either.

There are a lot of LA drivers who can't drive in snow, for example. I was one
of them, until I got practice, and even then, I'm not that safe at it.

I think as long as we set the bar at "drive anywhere a car can go with 100%
safety" we will never reach that bar.

But if the bar is at "drive as well as a human in most of the places humans
drive", well, I've already seen a car that can do that.

~~~
stefan8r
What's hard about this comparison is knowing exactly what you saw. If the
safety driver disengaged 1-3x, it might have felt like a robotaxi drove you
all over; but the effort to get that system safe for unmanned regular service
might take another decade.

If it was super mapped and following a fixed route with object avoidance; the
difference between a car that can go on an HD-map track and one that can go
point-to-point in a city is also maybe a decade.

We humans have limited empathy for what is really really really hard for
computers. Many know that's true for an app, but somehow ignore that knowledge
when it comes to autonomy.

~~~
greglindahl
Even if jedberg observed 0 disengagements, it's still not the millions of
miles of data you'd want to prove something.

------
ChuckMcM
Such an excellent and cogent discussion of the challenges of making an
autonomous vehicle startup work.

I really resonate with the challenge they had making safety "sexy" from a
coverage point of view. It seems it shares that attribute with "security"
which, when done well, means nothing happens.

I had a lot of hope that we would get four lane (two each way) "freight
ways"[1]. These would be paved roads designed specifically for autonomous
trucks to move freight from one point to another. With sufficient freight ways
between key cities on the coast and further inland, and efficient way to move
goods with somewhat worse costs than rail and quite a bit better in terms of
reaction time.

[1] Like a free way but designed specifically to exclusively service
autonomous trucks carrying standard containers.

~~~
Arbalest
This begs the question, how much does it cost to lay road than to lay rail? If
it's going to be exclusively autonomous, the more narrow confines of the rail
should be well suited.

~~~
stefan8r
Another common fallacy. The US actually has a better rail network than Europe
- most people just think it's worse because passenger rail here sucks. That's
the case because we prioritize freight trains over passenger (in America
Business is #1).

To paraphrase Churchill, trucking is the worst form of transportation, besides
all the others. If you can put freight on a train, you do. It's slower, point-
to-point, and less good a less-than-trainload freight than trucks are.

------
notlukesky
I always thought that autonomous driving was more than 10 years off (if not
20) for cars in city traffic. But I thought trucking in the US had a chance
for intersate traffic till the proverbial last mile, because there are less
edge cases that you need to train the model. Were you off by just 3 years for
interstate “driving” till the last mile?

Will investors lose their loss memory and a whole new set will invest in the
space in say 3 years.

~~~
stefan8r
System worked. Problem was investors have mostly bet on full autonomy, and
when that failed to materialized they got scared out of the space.

Full autonomy isn't necessary. And I don't know if it's even profitable for
trucks.

~~~
ozborn
Does the current coronavirus pandemic assist you in promoting a teleop model?
I'm not sure how much human to human contact there is in the business.

~~~
stefan8r
Hard to say. Truck drivers will be hit hard by this - they can't really stop
interacting with people, almost never get paid time off, are older and in poor
health, and are paycheck to paycheck.

My bet is that nearly all of them get COVID, with a higher hospitalization /
mortality rate. Could knock 30% of capacity off the road in the next 2
quarters, which would mean food shortages.

------
xiaolingxiao
This is a very good and honest retrospective. He shows clear thinking, and
surprising technical understanding for someone who is not technical. And most
importantly he shows humility. A+

------
rsp1984
_There are too many problems with the AV industry to detail here: the
professorial pace at which most teams work, the lack of tangible deployment
milestones, the open secret that there isn’t a robotaxi business model, etc._

Just curious, why would there not be a business model for robotaxis?

~~~
Animats
Uber: the drivers own the cars, the drivers maintain the cars, the drivers
clean the cars, the drivers store the cars when not in use.

Driverless: the company needs an operation, real estate, and staff comparable
to a big auto rental company to do all that. Plus the engineering and
technical staff required for autonomy.

Even with startups doing autonomous shuttle buses, which works at low speed,
nobody is making money in that space. It's all demos.

~~~
edshiro
Add to that the fact that you are _never_ going to get 100% fleet utilisation,
will need to pay for qualified tele-operators, maintain/repair vehicle along
with sensors...

I recently listened to a podcast episode of the Autonocast[1], where they
interviewed a Harvard Researcher who claimed the economics of Robotaxis just
don't work. Very interesting listen.

[1] [http://www.autonocast.com/blog/2020/3/11/177-ashley-nunes-
on...](http://www.autonocast.com/blog/2020/3/11/177-ashley-nunes-on-robotaxi-
economics)

~~~
stefan8r
All transportation businesses are utilization businesses. Empty hours/miles
are never recovered.

Early robotaxis will have tight geofences. Makes them particularly bad
competitors to poorly paid people who are willing to drive wherever.

------
d_burfoot
> The biggest, however, is that supervised machine learning doesn’t live up to
> the hype.

This is the key point. The new DNN approaches can outperform the classical
techniques, but only when they can exploit vast amounts of training data. The
dramatic successes of Deep Learning all depend on either unsupervised learning
against enormous raw datasets (BERT, GPT-2, word2vec, etc) or games, where you
can generate unlimited quantities of labelled data by playing the game against
your own agent (AlphaGo, AlphaStar, OpenAI Five, etc).

~~~
cosmodisk
As someone already mentioned here,I think it's probably not a goood approach.
The way we store info in dstabases is very limited compated to what we can do
in our heads. For instance we know a concept of a table.It can be made of
almost any material,can have whatever shape,size, and colour we want and yet
we can instantly recognise it without having some concrete data points on what
it should look like. I can make a glass cube,put it in a middle of the room
and people would know it's a table.How the hell we operate this way,I have no
idea.

~~~
wolco
On a basic level we all: \- Know what a room looks like. \- Expect certain
objects to exist at certain places and not expect others \- The brain indexes
these \- Seeing one or two datapoints allows us to guess. So seeing a glass
cube in that context gives us few logical chpices (it must be a table) similar
to someone typing a letter in a textbox and having it filter a pre-defined
list.

------
Adams472
Thank you for sharing this. The insights and details you share here will help
many future founders.

I'm sorry things didn't end up in the exact way your team may have hoped. I
hope you can take pride in everything you accomplished. I wish you all the
best!

------
alricb
It took me a while to figure out that "AV" means _autonomous vehicle_... I was
kind of wondering what AV as in AV club had to do with trucking.

------
sitkack
The VSSA (Voluntary Safety Self-Assessment) referenced in the post

[1] [https://uploads-
ssl.webflow.com/599d39e79f59ae00017e2107/5c1...](https://uploads-
ssl.webflow.com/599d39e79f59ae00017e2107/5c1be1791a7332594e0ff28b_Voluntary%20Safety%20Self-
Assessment_Starsky%20Robotics.pdf)

------
pj_mukh
Great read! And thanks to the author for all the candor.

The business case always seemed clear to me and now reading this, I wonder if
there is a case to be made for an engineer and a trucking operations veteran
to build a business that requires minimal capital (or maybe even is
bootstrapped?!), to take it across the finish line?

~~~
stefan8r
There are a couple of people working on that, notably CloudTrucks.

It's not for the faint of heart - truck drivers and engineers follow a very
different set of social norms. It's hard to be the hardass boss drivers don't
want to fuck with while being the cuddly CEO engineers like the culture of.
That might be a future blogpost.

~~~
ngcc_hk
Waiting for it. Sad but good read.

------
baylessj
Thank you for the excellent write-up here. I'm sad to hear that Starsky is
dissolving, but I have hope that the lessons learned here will be applicable
elsewhere.

The point about safety being a low priority with investors makes sense but is
unfortunate. I hoped that Google's investment in Waymo would push past this
hurdle, but they're latest funding round makes it clear that they also have to
deal with investor wants over the success of the technology. Really hoping to
see someone get the funding to make this tech work reliably in the future and
apply the same safety-first design that Starsky used.

------
mrfusion
Why not an aquihire? Surely lots of companies would want to augment their av
teams?

~~~
savrajsingh
I’m sure it was explored but it didn’t close. Stuff like this is annoying for
a founder to hear because he’s like “aw yeah, why didn’t I think of that
earlier?!” Of course he thought of it — but it just didn’t work out that way.

------
DrNuke
It is pretty cynical and hindsight is always 20/20, but... is self-driving
automotive just trains and metros? There is a fundamental business case flaw
in these startups, because regulators worldwide will never approve them go
together with human traffic, which is messy, chaotic, smart in its own sense
at local level (you need to know the uses of local people, not the general
rules... eg. driving a car in Naples is very different from driving a car in
Milan). Only dedicated lanes or tunnels then, trains!

------
m0zg
I wonder what Elon is going to do when _his_ "full self driving" fails to
materialize. Which it will. Not only you can't do this with just cameras and
radar, I doubt you can do it _period_ without modifying the roads specifically
for such cars, and segregating them from human drivers. And even then it will
be difficult psychologically and legally to convince the public that this is
"better" than a (possibly inebriated) human, for reasons that have been
discussed to death already.

~~~
aphextron
>Not only you can't do this with just cameras and radar

Humans do it really well with just two cameras. It's not a hardware problem;
it is entirely software. Whether self driving is possible or not with current
AI techniques is debatable, but we're not waiting on any advances in hardware
to do it.

~~~
qchris
> Humans do it really well with just two cameras.

If you don't mind, I think I'm going to steal that quote. It makes a really
good point very succinctly.

~~~
MegaButts
It's true, but it ignores the fact that human eyes have orders of magnitude
more dynamic range than even _very_ expensive specialized cameras, and it
obviously ignores the fact that we haven't invented general AI yet.

It's a pithy response that undermines the challenge of a problem nobody has
been able to solve even with years of effort and billions of dollars.

~~~
aphextron
>It's true, but it ignores the fact that human eyes have orders of magnitude
more dynamic range than even very expensive specialized cameras, and it
obviously ignores the fact that we haven't invented general AI yet.

That level of resolution doesn't matter at all for driving. People can drive
just as well through a video feed, like Starsky was doing. Yes general AI does
not exist yet, but my point is simply that the parent made a comment about the
need for hardware which is simply not true.

~~~
MegaButts
> That level of resolution doesn't matter at all for driving. People can drive
> just as well through a video feed, like Starsky was doing.

I can tell you from experience this is false. It usually works, but when it
doesn't you're fucked. People wildly underestimate, by orders of magnitude,
how many and how complicated the edge-cases are for self-driving.

------
punnerud
Why does every self-driving car company focus on driving like we do today?
Seems more viable to make a system where the trucks dock at speed on the
highway. This is where the power of AI come in to play by coordinating the two
trucks next to each other, switching load and continue driving without ever
have to stop. The end goal would be to also move people, but we have to start
with something safer that makes economical sense.

------
petermcneeley
All this L1/L2/L3 when most of the public failures in AV are at the level of
vision and interpretation of the world.

~~~
krisoft
So? That graph is about the capability of the system and how it improves with
effort. This has nothing to do with which part of the system fails the most.
Where do you see the contradiction?

~~~
karlding
The choice of naming here is somewhat unfortunate, and probably contributes to
some confusion.

Level 0-5 is terminology used by SAE to describe the range of fully manual
(Level 0) to fully autonomous (Level 5). One would expect that in an article
about Autonomous Vehicles, L{0,1,2,3,4,5} would describe the level of autonomy
that the vehicle provides, but the article instead uses these to describe
arbitrary thresholds of a graph demonstrating the capability of an AI.

~~~
stefan8r
Fair point. I'm shitty at drawing mathematical graphs.

I'll update at some point with different notation.

~~~
ngcc_hk
I think it makes my day as it is a rare but simple insight into the s curve
and the peak line. It will be a useful mental tool for life.

Not sure why l meant anything in some other model would affect its reading.
Good to me.

------
ackbar03
Not sure about him blaming the "professorly pace" of research though. That's
the rate good research is done at. If you were expecting anything faster than
you don't really understand what it was going to take in the first place

------
mleonhard
Stefan & team: I'm sorry your company failed. I hope you can and will take
time now to rest and recover.

Things that help recovery from burnout: long walks, therapy, exercise, sleep,
meditation, and spending time with people you love.

------
Quarrelsome
If we'd sold AV as "grandma driving" instead of "autopilot" do you think we
could have avoided some of this mess?

The public are only ever going to accept perfection which prevents us from
getting our hoverboards here.

------
mrfusion
Welcome to the trough of disillusionment. (sp)

I think the plateau of productivity will be really awesome computerized
copilots and safety assists/warnings. The human computer driving team could Be
quite a combo of designed right.

~~~
stefan8r
The problem is that most of those businesses don't make sense with the current
cost of talent. The L2 systems OEMs are rolling out are primarily made by
engineers in low-cost areas at $60-90k/yr, not $130-250k/yr in SV.

Realistically, most of the AV talent will go to industries that can afford
them. Salary isn't super elastic.

~~~
mrfusion
The engineers in the low cost of living areas do the real work. We don’t need
rockstars.

------
machinelearning
For any engineers reading this who want to solve the computer vision/machine
learning problems explained in the blog post - reach out at
info@nuronlabs.com.

------
anandkulkarni
Thanks for sharing, Stefan. Lots to be proud of in what Starsky achieved, and
factors outside your control at work at the end.

Excited to see what you do next.

------
malandrew
> In 2019, our truck became the first fully-unmanned truck to drive on a live
> highway.

Uber drove an autonomous truck on a live highway to deliver beer for Anheuser-
Busch back in October 2016

[https://fortune.com/2016/10/25/uber-anheuser-busch-first-
aut...](https://fortune.com/2016/10/25/uber-anheuser-busch-first-autonomous-
truck-beer-delivery/)

~~~
stefan8r
There was a person in the vehicle. Amusingly - many VCs who "should know
better" fell for the same error. I'd regularly get in arguments with investors
about whether others had done unmanned or not.

~~~
malandrew
In the sleeper cabin monitoring the vehicle. The main cabin was unoccupied and
there wasn't a single intervention for the entire trip. I knew people involved
with that trip at the time.

~~~
stefan8r
The difference between "in the sleeper cab" and "outside the truck" are huge.
We first started doing in the sleeper cab in Jul'17, took us 2 years of
dedication to get confidence to remove from vehicle.

To take the person out of the vehicle, the system itself needs to be able to
self-monitor and pull itself over if it stops working. That's the big lift.

~~~
malandrew
That's it. The team at Uber did that like a year or so later but with no
public fanfare because it wasn't considered noteworthy. That still puts it at
~2 years prior to this accomplishment.

------
Havoc
This to me very much assumes no leap forward. See the start of deep learning -
sudden rapid progress. I don’t see why there can’t be another jump like that.
Much like the chip manufacturers mentioned in the post.

No idea what that advance may be but it’s out there I think

~~~
larrydag
Perhaps there is no leap forward in long haul trucking. Yet there are many
supervised machine learning products in the market and doing well (Tesla
autopilot, iRobot vacuums, etc). I bet the founder can find a niche that could
be marketable and can be mass produced or scaled.

------
johntiger1
Just this hiring season, I still saw positions open...and now this

------
blackrock
Maybe it’s time they got bought out by a larger company, and go dark. Continue
their research in private, until they build the perfect robot.

------
keenmaster
Sad news. Apart from improving upon ML, can more sensors and physical modeling
get us past the AV plateau?

An example of an additional sensor would be an infared camera. I don't know
how well infared cameras work during the day or when they are occluded, but
they seem like they can provide an additional datapoint to classify an object
as "person" for example. That way, it doesn't matter if they're wearing a
paper bag Halloween costume, the car still knows what's underneath.

Physical modeling seems like it would help with prediction. If a deer is idle
on the side of road ahead, a car with a physical "deer" model would account
for the probability that the deer will suddenly dart across the road and the
speed at which it can possibly do so. It will slow down and watch for certain
behaviors, such as the deer standing up from a prone position, and modify its
probabilities accordingly. That is, after all, what we humans do. The ML
wouldn't need to perfectly model all animals. Some animals would be put into a
"mammal" class or more vague "animal" class, paying special attention to size
and stature.

Additionally, depending on how long it might take to develop truly autonomous
self-driving cars, we might want to develop self-driving car friendly
infrastructure. I'm talking about AV-only lanes with safeguards in place to
minimize variability, vehicle-to-vehicle communication, infrastructure-to-
vehicle communication, and better than average maintenance. It seems like it
might be worth it, given the gains to be had.

Here's an underappreciated angle to the AV-friendly infrastructure: it's a
hedge against incorrect predictions. What if truly autonomous vehicles are
actually 15 years away? In that case, if an "AV heaven" is developed in a
corridor somewhere in Los Angeles 5 years from now, that'll be the only place
where the AV dream is realized for the ensuing 10 years. The profit from "AV
heaven" can be reinvested into AV development. It can also be used to expand
into other areas. Moreover, AV heaven might galvanize the government, public,
academia, and investors to eliminate any bottlenecks in AV development.
There's no immutable stone tablet, only viewable by God, that says "AV
development must take X years." We can modify the timeline to some extent.
Lastly, AV heaven would allow us to observe the true value of self driving
cars. What if they're better than we ever imagined? What if they radically
change human behavior? What if they increase development in surrounding areas
by a lot? What if they change the nature of work and where people live by more
than we even expected? What if self-driving trucks + last mile bot delivery
radically push down prices on everything and enable previously impractical
business models or behavior? We actually know many of the changes that AVs
will bring, but, critically, we don't know the magnitude of those changes.

------
smabie
I'm not sure it's intellectually honest to put all the blame on stupid
investors, as a founder it's your job to deliver what the market and the
investors want, or convince them otherwise. And if in fact investors and the
market is just stupid, that's actually a great sign: you were just early and
have a shot at doing it again in the future.

