
Hard Tech Startups - dwaxe
https://blog.ycombinator.com/hard-tech-startups
======
rayiner
> Many hard tech founders come from academia or big company backgrounds, where
> projects can be expensive and slow. We help these founders shift into a much
> more iterative mindset so they can move faster.

I think this is key and I hope it takes off beyond YC. I used to work on a
DARPA-funded R&D project in the wireless space. DARPA's culture is really
cool: throw a bunch of money at PhD program managers, give them a ton of
directorial discretion, and let them fund "blue sky" projects they think are
really cool. But it's a very academic mindset and the mission creep is huge.
DARPA kept sending us down these "oh can we do this?" rabbit holes. At one
point our radio grew an expert system that processed XML-formatted regulatory
directives.[1] We spent huge amounts of time doing things other than solving
the core problem. A decade later consumer deployment is still a ways away. It
would be so much further along if DARPA had the focus of something like YC.

It seems like a no-brainer to those in Silicon Valley that you should find a
tractable subset of your problem and pound on it until you've figured it out.
That's not the way the big research institutions working on "hard tech"
usually operate, and it's not really how major research universities teach
people to think.

[1]
[https://en.wikipedia.org/wiki/DARPA_Agent_Markup_Language](https://en.wikipedia.org/wiki/DARPA_Agent_Markup_Language)

~~~
akiselev
What do you mean mission creep and how can you avoid it when you have "blue
sky" projects? As I understand it those types of projects, by their very
definition, are trying to do something so unprecedented that they don't have a
clear roadmap and will always go off into many tangents before circling back
to their main goal. Take the moon landing for example: early rocketry
pioneered technologies in chemistry and controlled explosives, material
science, mathematics, and computation before the first Mercury mission to say
nothing of systems engineering, a very broad field born almost entirely from
the NASA space program. DARPA is the agency that takes on projects that are
way outside of the capabilities of any other research organization in defense
and its a lot less focused on commercializing technology than the NIH or even
NASA.

The very interesting thing about DARPA is how its management is structured so
differently from every other government agency. DARPA has a $3 billion budget
with a staff of less than 300 people who are mostly project managers and
administrative staff (compare to NIH - $30 bil/20,000, NSF - $7 bil/1,700, or
NASA - $19 bil/17,000). By policy these PMs have a strict term limit of four
years and the only DARPA PM I know of that served a second term did so over
two decades after his first. These PMs have scientific advisory boards that
don't have any term limits but the mandatory turnover for management means
that they come in with clear goals and deadlines that seem to remove career
advancement out of the picture (although to be fair, most DARPA PMs are way
beyond worrying about their career prospects). No other government agency
works this way and it has paid dividends not only for our defense but for
technology and society as whole.

Unfortunately there isn't a DARPA equivalent of
[https://spinoff.nasa.org](https://spinoff.nasa.org)

~~~
rayiner
> What do you mean mission creep and how can you avoid it when you have "blue
> sky" projects?

Imagine if during the Mercury project, someone threw in: "oh, and while we've
got someone in space, we should do a spacewalk too."

~~~
akiselev
Can you give a specific example as it relates to DARPA? A space walk would
have been mission creep for the Mercury program only in the most trivial way
because the technology was already developed by that point. The problem was
the unacceptable risk and lack or reason to do any kind of spacewalk (Mercury
and the mission procedures were not even remotely designed for in-flight
repair).

~~~
rayiner
So our project (XG) was about developing radio networks that could
opportunistically use spectrum without _a priori_ channel allocations. That
was hard enough when you took into account challenging environments (terrain
obstacles, jammers, etc). But DARPA decided the radios also had to be able to
make decisions in conformity with regulatory policies written in this
declarative XML language. It became this huge tangential AI project:
[http://xg.csl.sri.com/technical_reports.php](http://xg.csl.sri.com/technical_reports.php).

~~~
elcritch
Honestly, sounds like the side-AI project could be the exact point of a "blue
sky" project but that open ended "maybe this won't result in a explicit result
in this decade" ain't for everyone. Neither good nor bad.

The ability to produce AI tuned opportunistic spectrum allocation could have
far reaching implications in fields outside of spectrum analysis. Many of the
biggest problems faced by modern organizations is dealing with beaurocracy
while efficiently allocation resources. Maybe this never lead to anything, but
then again who knows if this could lead to a whole future field of efficiently
scaling large organizations ... Take a look at the outputs of undirected DARPA
funding and the results still bearing fruits decades later: computer animation
by people like Ed Catmull (culminating in Pixar), Alan Key and object oriented
programming, tcp/ip, etc. The bigger question of whether this side project
could yield fruit has more to do with the type of team environment of the
project and whether the pursuit came from a genuine "I wonder if...". E.g. One
of the best predictors of the useful of such blue sky discovery is whether
there's a large element of "this seems fun/intruiging!" as appeared to the
driving motivation of Ed Catmull when he invented texture mapping.

And thanks for the links! I'm actually _very_ interested in reading these
papers. There's been a lot of intruiging work and research on type-valued
types (c.f. Iris programming language). But there's a difficulty of describing
and translating rulesets from various vague human logic into effective
computer passable rulesets.

~~~
_pmf_
> Honestly, sounds like the side-AI project could be the exact point of a
> "blue sky" project

As a separate follow up project; not as a sub-project that stalls the main
project (which is how it will be done since "What else are we going to do with
the money? Doing the boring work of ironing out the kinks in the main
project?").

------
AndrewKemendo
This is the hardest thing to explain to people about companies like ours. When
I say that machine vision systems are comparable to building hardware people
can't conceptualize that because they have never really worked with novel
CV/ML systems.

I think this post has it right too in that finding a small application of the
technology is a good approach to sustaining yourself while you get to a bigger
goal. This however adds a magnitude of complexity - which means funding
requirements aren't that much smaller. For example you have to build a product
while also building the technology - vs just building a product on exiting
technologies, which is hard enough itself. It's also a risk because if that
one product is not a winner, then it poisons the larger play - even though it
might be itself very valuable.

The challenge comes when you have to explain that, no actually this first
thing is just the POC for a larger thing we're trying to do - especially when
you are building the market for that larger thing.

I think the best path for hard tech companies is to have a lot of money from
the start. I know that sounds obvious, but I think it's true specifically for
hard tech companies.

Unfortunately that usually means you as a founder are a known entity in the
venture world. Whether that means you use your own money from a previous exit
(like Musk) or convince someone to fund a lot of it (probably because you had
a previous exit and have connections) you need a lot of capital up-front.

So if you are an unknown to the people with cash, with hard tech plans,
prepare for a tough time ahead.

~~~
snovv_crash
If you don't have to design for assembly, you aren't dealing with hardware.
The fact that software essentially has zero reproduction and distribution cost
is what makes it so much easier.

Put it this way, when you buy a car, the difficult part for the manufacturer
wasn't the customer-experienced design of the car, or even the driving
concept. The hard part is designing the assembly line, and designing the car
in such a way that 100,000 of them can be put together such that the assembly
of each individual piece takes exactly the same amount of time, otherwise
there are assembly line stalls. Then you also have to design, or at the very
minimum optimally position and program, the machinery to put the pieces
together, organise supply chains, deal with subpar contractors whose quality
changes even if they are delivering theoretically the same product, etc.

Seriously, I have done my time in the CV space, and it is a lot easier than
real world hardware, even if CV is still being explored, just because of the
distribution and replication of a finished product.

~~~
AndrewKemendo
I don't disagree that hardware itself has more dependencies. I don't think
that makes it harder or less probable of delivering though than bleeding edge
computer vision/machine learning systems.

I too have worked hardware and on those projects we could get fairly low level
line workers on assembly up to speed quickly, source our parts in a repeatable
fashion and build systems to scale without too much brain power. Not easy, but
more logistics management than creativity.

With these non-deterministic CV systems (for example point cloud generation)
the path to working is much less clear.

I'm not saying one is harder than the other, but the class of unsolved
problems in CV/ML doesn't have off the shelf solutions, so they pose different
but similarly hard problems as hardware.

~~~
snovv_crash
A lot of the CV problems are essentially 'solved', though.

Feature extraction (AKAZE, BinBoost), matching (GPU brute force hamming),
RANSAC (with PROSAC and relatives), bundle adjustment (Schur Decomposition
with LM), point clouds (SGM, PatchMatch) and mesh (Poisson, FSSR).

Each stage has tuning, and real-time requires sacrifices on the hardware we
have available, but we know with better computers we can have it. (HSA has me
drooling, hurry up with Zen, AMD!)

IMO the harder stuff is in semantic segmentation of point clouds and dynamic
scenes, but I have high hopes for the next few years.

~~~
AndrewKemendo
_semantic segmentation of point clouds_

lol, hey it's hard enough to do with static images. Feature matching
pointclouds is probably turing complete :P.

That's the kind of shit we're working on though. We're trying to turn the real
world into a platform.

~~~
snovv_crash
I feel like it should be easier than images, since we have all the 3D
information. There are all of the features based on 3D structure which image
segmenters can't even begin to use.

It's one of those things that we can do efficiently, so with enough priors of
what scenes look like a sufficiently informed ML system should be able to get
decent accuracy.

------
hoodoof
"Hard tech startups

Some people think YC only funds software startups."

Kinda strange that software is not seen by YC as "hard tech".

I think there's lots of hard tech in software but the way venture
capitalists/angel investors tell it, you should only ever build software that
can be made in a weekend and then iterated upon.

The outcome of this is the X thousandth dog walking social network for uber
drivers staying at AirBNB - i.e. stuff that you can build in a weekend and
iterate on. And this is why demo days are full of such lightweight software
applications - people are actively discouraged from taking the time to build
something large scale and, well, "hard".

Sometimes it makes sense to make a big bet on building some complex software
that might take months or years to build, with lots of moving parts, but once
complete solves a big problem. That is software that is "hard tech".

~~~
striking
Edit: I'm awful at this reading thing. Please see the replies to this comment
for a correct definition of "hard tech". My original comment follows.

.

I think "hard tech" in this instance means "technology in the form of
hardware" or "technology that is physically manifest" and not "technology that
is difficult."

~~~
hoodoof
The first line of the post explicitly makes a distinction between "software"
and "hard tech".

I really challenge the accepted wisdom of "build something tiny and iterate"
as being the only way to build software.

~~~
tedmiston
Of course there are many approaches to build software [1]. I also read that
comment as more of a philosophy for _product_ development than software
development.

[1]:
[https://en.wikipedia.org/wiki/Software_development_process#A...](https://en.wikipedia.org/wiki/Software_development_process#Approaches)

------
pitchups
> Hard tech companies go through the same 3-month batch format as all of the
> startups we fund.

Is 3 months sufficient time for working on hard tech startup ideas. The
original 3 month batch format was designed for software & web startups - YC's
initial focus. It seems to me that the cycle time for iterating and testing
different approaches to solving problems in hard tech would be much longer -
hence require more time?

~~~
toomanybeersies
My personal opinion (not that I have any commercial experience with hardware
development) is that it's not.

It can take up to a month to receive a specific part for a prototype, and
prototyping takes a lot more time in real space than in software.

I can change a class or a module in some code and 15 seconds later have the
new version running. Changing a single part in a hardware system could take a
day of work, changing both the software drivers and the actual physical
hardware.

You can't just NPM install a new part and see if it works, you have to
actually order it and wait for it to arrive in the mail.

~~~
Balgair
The ONLY way I can see this working is if your parts can ALL be 3-D printed in
their entirety or milled in under an hour. That then relies on a very very
good printer set-up, likely one that you own and have used for at least a year
(temp/humidity issues). You can do some electronics and PCB design with a mill
and a copper plated proto-board (mill away copper plate and you can make crude
PCB 'wires'), but you still need a fully functioning and stocked components
chest or you have to wait a week for Digikey. If the zeitgeist is going
towards IoT stuff, and I think it is, then you must wait for electronics parts
to link the 3-D printed gizmo to the hackers waiting to make it a spam bot. 3
months is unlikely to be enough time to really get anything working without a
well stocked lab.

------
ryanx435
_Very often, the first thing we do is help hard tech founders find a small
project within their larger idea that fits the model of quick iteration and
requires a relatively small amount of capital._

 _Tesla is my favorite example of how powerful this small project + long-term
planning mentality can be. Their vision has always been to bring an affordable
electric car to the masses, but they first built the Roadster—the opposite of
a mass market car—to generate revenue to get to the Model S._

so designing and building a top of the line sports car is a small project?
what?

~~~
dasmoth
It's a lot smaller than Tesla's subsequent projects.

Remember, also, that the roadster was based substantially on the Lotus Elise,
and Lotus built the bulk of the vehicle. Look at us as a drivetrain project
rather than a car project and it looks at least a bit more manageable (which
isn't, by any means, to say trivial).

~~~
FullyFunctional
I agree with your point, but just for the record:

The Lotus Elise + minor delta was the original thinking, but Tesla/Elon has
repeatedly pointed out that it was a mistake; the Elise frame was dramatically
reworked to the point where it would have been better to have started from
scratch.

------
roymurdock
Now is probably the best time to get into "hard tech" \- aka industrial
automation, automotive, aerospace & defense, energy & utilities, etc.

Look to GE for a prime example - a $250B manufacturing and processing behemoth
rebranding itself as an agile tech startup with GE Digital and Predix rolling
out across many of its factories. Its 2015 10k was titled "Digital Industrial"
and really describes the company's new focus on "hard tech":

 _We are just beginning our transformation as the Digital Industrial Company.
The Internet has had a massive impact on consumer productivity and commerce.
Its impact on industrial markets is just now being realized. By 2020, 10,000
gas turbines, 68,000 jet engines, more than 100 million lightbulbs and 152
million cars will be connected to the Internet.

At GE, we have decided to generate and model this data ourselves—both inside
the Company and with our customers. This is what we mean by becoming a Digital
Industrial. Our Digital Industrial capabilities will expand our growth rate,
improve our margins and bring us closer to our customers. There was a time
when every sale had a clear endpoint, followed only by routine service and
maintenance. Now, sensors on our products send constant streams of data,
analyzed and translated into upgrades that drive productivity in industries
where even the smallest incremental efficiency can mean very large gains.
Capturing it will be a mission in every one of our businesses. Our aspiration
is to offer with every GE product a pathway to greater productivity through
sensors, software and big-data analytics.

Why GE? I assure you we didn’t wake up one morning with “software envy.” We
have been investing in software and accumulating data for decades. Competing
will not require big acquisitions. Rather, the technology required to compete
is in our sweet spot. So, why not us?_

Similar story if you look outside of the traditional IT market and across the
embedded market. Software is being layered on top of "hard tech" to collect
data and provide value in a ton of markets that you won't see covered in Tech
Crunch. Or maybe you will, given that YC is now pushing for founders with
knowledge of these grittier industries.

~~~
mountaineer22
What is "consumer productivity"?

~~~
ScottBurson
Obviously, it's our ability to consume more rapidly! You know, one-click
ordering :-)

------
AceJohnny2
_> [Tesla] first built the Roadster—the opposite of a mass market car—to
generate revenue to get to the Model S. The Model S then generated the revenue
to start the Model 3._

Except the Roadster didn't generate enough revenue, Tesla was on the verge of
bankruptcy, and Elon Musk swooped in to save the day (and have himself
labelled a co-founder as part of the deal).

The Model X was supposed to be a quick reskin of the Model S chassis as an SUV
to provide a stopgap model while the Model 3 was developed, but that turned
out to be more complicated than expected and Musk's demands for those striking
but complicated gull-wing doors caused development and production problems
that delayed it for years.

I'm readying the popcorn for the delays and production issues of the Model 3.

------
zwieback
Interesting post, could be interpreted multiple ways:

\- growth in pure/easy SW projects is stalling, need to find new areas

\- trying to get away from the "bro" prejudice against SW startups

\- YC has found a good way to bring rapid, iterative development techniques to
hard/HW projects

Hopefully the third one but probably a combination of all of the above.

~~~
codingdave
Maybe I'm just cynical, but my interpretation was more of "YC's over-arching
strategy is to benevolently get a small piece of EVERYTHING, so we'd better
convince new markets to come work with us."

------
neltnerb
I am somewhat curious whether Y Combinator is considering partnering with
Cyclotron Road up at LBL. It seems to be focused on the same type of
companies, hard science, but with an excellent model for supporting this kind
of work.

As a scientist who founded a hard science startup (and now work for another),
I feel like the hands down biggest barrier is lack of access to free/low-cost
space to work. These projects aren't the kind of thing you can do out of a
coffee shop, it's just too dangerous. Plus it requires expensive capital
outlay to do the initial work, even if you only need the equipment for one or
two tests.

The fact that they partner with a national lab to provide those testing
resources saves so much time and energy that's better spent on finding product
fit than fundraising enough to get to the point where you can even find out
how well your technology can perform.

I'd strongly suggest at least reaching out to them to see if they can help
advise, they've had amazing results so far.

------
paulcole
> YC’s largest exit to date is a self-driving car company

Isn't that just because several highly valued software startups haven't exited
yet? Judging by this list:

[https://www.cbinsights.com/blog/y-combinator-startup-
valuati...](https://www.cbinsights.com/blog/y-combinator-startup-valuation/)

~~~
tedmiston
Of course. I never saw the exact Cruise acquisition price, just "north of $1
billion", and you can see 6–7 on that list worth about a billion or more.

In fact, in her _How to Build the Future_ talk [1], Jessica Livingston said
that most unicorns have come out of YC.

[1]:
[https://www.ycombinator.com/future/jessica/](https://www.ycombinator.com/future/jessica/)

------
DrNuke
My two cents here from the industry I am in. Thesis: I can't see any nuclear
reactor at the paper stage in 2016 beating the small modular reactors from
westinghouse (III gen integral pwr) or ge-hitachi (IV gen PRISM sfr) to the
2030 race for the next coming innovative fleets in the Western World.
Corollary: Elsewhere, China and Russia will probably risk more and do better
at raising the bar of progress. Action: What can be done at YC level then
imho? There may be a niche in standardising the design of the most critical
components using data science methods, think of an Ikea for the nuclear
island. Hard tech, reduced to the simplest problem with a customer, may be the
for nuclear sector some critical process (a new material?) or some critical
component (a one-fits-all vessel?), both economically affordable at the lab
level and at the computer-powered engineering design.

~~~
acidburnNSA
It can take decades in-reactor to accumulate the irradiation dose needed to
prove out really advanced fuels and materials. We really need an international
nuclear innovation center complete with a flexible test reactor (high flux,
fast spectrum, multiple independent coolant loops), legit post-irradiation
examination facilities, core mockup facilities for mechanical design, flow
loops for thermal/hydraulics, etc. This is extremely expensive to build and
maintain, so a business model that can make money along the way (medical
isotope production, Pu238 for space travel, easy access to many customers,
etc.) is needed, though multi-mission stuff can add lots of institutional
complexity. The national labs are supposed to play this role, and are doing so
to a degree, but the current lack of facilities really saddens my advanced
nuclear design soul.

Russia has operating sodium-cooled reactors (BOR-60, BN-350, BN-600) and low-
power critical facilities (BFS-1&2). Using those, they can develop and test
new nuclear structural materials and fuels that push the envelope. And
shipping materials to Russia for testing and bringing it back for
investigation is ridiculously hard. Politically streamlining collaboration is
essential for nuclear progress.

The US shut down its best test reactors (FFTF near Handford, WA and EBR-2 in
Idaho) in the 90s so it's pretty challenging to iterate. At least we're trying
to turn TREAT back on now.

So what can a nuclear startup do? Sam is right. You have to focus on small
things and bootstrap yourself up. I was an advisor to Nuclear Innovation
Bootcamp a few months ago and the team wanted to build a new giant reactor in
Diablo Canyon's containment for hydrogen production. Big picture stuff. I
encouraged them to focus on something more specific, like technology for
coupling the nuclear island to an industrial unit (hydrogen, desal, ...
anything) while being able to smoothly alternate power between it and the
turbine (for load following on the grid). It's a lot less glorious to work on
something like that, but that's the only way to get started in this field
unless you're sitting at the non-existent international nuclear tech center,
or on $1B of very patient seed money.

~~~
DrNuke
Hello, great post, thanks! About the material: it may be an incremental steel
alloy, for which data science methods can help a lot: for the learning part,
feed the results (the plots with dpa irradiation vs damage in terms of
displacement, swelling, bubbles o whatever relevant) from the 2000-2016 papers
from Western and Chinese universities aiming at the same target; for
prediction, let deep neural networks or extreme gradient boosting cluster or
classify or rank the nearest alloy that solves your most urgent technological
readiness problem. This would help speed the process imho.

------
memossy
Out of curiosity do the "hard software" startups at YC (a startup is whether
there is doubt that the software can be built at all) share more
DNA/commonalities with the "hard tech" startups or their fellow software
startups?

------
lifeisstillgood
VC is apparently awash in capital (11 Trillion USD in bonds now trading at
negative interest rates quotes Andreessen)

The Internet was born out of probably the worlds most successful long term
focused VC - DARPA

now I can't tell if this is the VC community going back to a long term model
and invest for decades before expecting a return. 11 trillion would do a lot
of good invested for ten years in the globes best and brightest

If we don't know if the tech will work at all (fusion etc) then YC is
effectively funding academic research. Which is fine, but I assume the right
way to build a business may not be the right way to choose the next research
project. Gittens index notwithstanding

Are these businesses measured in some way differently to the next Uber?
Different P&L expectations, different pool of funds? If not then ... ?

------
ftrflyr
My first company Light Up Africa Inc., a hard tech startup, was a part of the
Impact Engine in Chicago. We did not have access to 3D printing, hardware
facilities, and labs to help us prototype and iterate effectively. And that is
just step 1. We then had to manufacture in parallel while continuing to
research.

Also, I can attest that is extremely difficult to build a startup with a heavy
research focus. However, from the brief write-up presented, I don't see how YC
is in the position to help build and scale hard tech startups at scale -
especially those with a tremendous need for capital invest to further research
and manufacture.

------
jonbaer
I find this to be a unique 'hard tech' example ...
[https://www.technologyreview.com/s/422511/the-fantastical-
pr...](https://www.technologyreview.com/s/422511/the-fantastical-promise-of-
reversible-computing/)
[https://en.wikipedia.org/wiki/Reversible_computing](https://en.wikipedia.org/wiki/Reversible_computing)

------
imaginenore
As much as I like YC and this particular board, their standard deal is $120K
for 7% of the company. That amount of money is so ridiculously low for almost
any serious hardware project.

Just consider what $120K buys you. Barely one mid-level engineer for a year
(don't forget the taxes, social security). In that year you would have to
create and mass-produce and sell the product, just to keep paying the salary.

I'm surprised YC doesn't offer something like $500K for 50% of the company.

~~~
tlb
The typical trajectory is to take YC's $120k for 7%, gather some evidence that
the idea will work, then raise $1-2M for 15%, then get it really working at
small scale, then raise $10-20M for 25%, then scale up. The farther along you
are, the more money you can raise for a given amount of equity, so it makes
sense to raise money in stages.

~~~
rebillionizer
Why would this be a better path than using SBIR/STTR funding and the
associated ecosystem for proof of concept? Unlike YC it is non-dilutive.

It's something I've long wondered but it's never been answered to my
satisfaction.

~~~
themikemachine
SBIR/STTR funding is non-dilutive but it is far from free. To apply, you: (1)
Spend 1+ month on writing the grant, doing all the paperwork, getting letters
of support, etc. (2) Wait up to a year to see if you got the money. The hit
rate is often 15% (on average you need to apply 6 times to get 1). (3) Get
~$150K if you're lucky for phase 1, and this money is only for research. You
cannot use it on lawyers or keep it in a bank. You also have to spend the
money in 8 months. And write a report on your progress. (4) Then apply for
Phase II, which can be up to $1M. Even if everything goes right, it will take
at the least 2 years since you start applying to get a phase II application.

It's great money if you have all the time in the world and really like writing
grants. Or if you have no other choice. But you will pay for it with your
time. Also, you will be at a huge disadvantage unless you have a PhD and
university contacts. Writing successful grants is a difficult skill that takes
a lot of practice, and you will be competing with people that ONLY write
grants.

------
Animats
By "hard tech", YC apparently means "has technical risk", as opposed to a
marketing-based business.

There was a time, pre-2000, when VCs did almost entirely "hard tech" startups.
VCs were more profitable then. But the weakening of patents by the anti-patent
lobby has made this infeasible as a business strategy. You have to buy market
share now before someone steals your technology.

~~~
foobarqux
Why are patents weak now? Why were they strong before?

~~~
Animats
America Invents Act, easy and repeatable post-grant challenges, no more
injunctions, very limited punitive damages. Worst case for a patent infringer
is having to buy a license.

------
rokhayakebe
I prefer Hard Business to Hard Tech. Some businesses may be easy on the tech
side, but very hard on the customer acquisition side because they require a
complete change in the way people think and/or behave.

In that light these businesses were easy tech but hard Businesses that ended
up being worth a lot: Ebay, Amazon, Uber, AirBNB, Dropbox, and more.

EDIT

10 of the top 15 Unicorns

Uber - Not Hard Tech

 _Xiaomi - Kind Of Hard Tech_

Didi - Not Hard Tech

AirBNB - Not Hard Tech

Palantir - Hard Tech

Snapchat - Not Hard Tech

Wework - Not Hard Tech

FlipKart - Not Hard Tech

 _SpaceX - Hard Tech_

Pinterest - Not Hard Tech

Dropbox - Not Hard Tech

~~~
throwaway729
Uber's core business isn't hard tech, but they're investing mountains of money
in hard tech.

~~~
tlb
Or to say it another way, providing v1 of the service wasn't hard tech, just a
mobile app with routing and payments. Scaling up and driving the cost down is.

This is a great way to build a company, because you have real data about which
scaling problems are actually important, and a real operation to incrementally
test solutions in.

~~~
throwaway729
Actually I was thinking self driving. But that too.

------
asimuvPR
Say I have a technology that's related to autonomous vehicles. It requires
hardware and software. How would joining YC increase the odds of the
technology being adopted by auto manufacturers? Its not a consumer product and
its a technology that aides and improves autonomous operation but does not
actually drive the car. It would be nice to hear from anyone from YC or with
experience.

~~~
jayjay71
The mentors provide excellent feedback on what you should focus on at any
given time, and are great at troubleshooting problems. In addition to that,
they have a great network (the YC alumni which includes some self-driving car
companies as well as investors) who may be able to connect you directly to the
companies you want to work with.

One of the hardest things for people that have never started a company before
is to understand just how hard it will be. Having people on your side can make
all the difference, if only to improve morale and help you maintain you
sanity.

~~~
asimuvPR
Thank you for the reply. Is there something in YC that is not for pure
startups? Something to support R&D with a commercial goal but that do mor
necessarily follow the common business path.

~~~
jayjay71
I think YC's criterion for getting admitted into the core program is still
fitting - do they believe it can become a (ten) billion dollar company? They
recently created the Fellowship program to fund more companies at an earlier
stage but I don't know too much about that.

It's hard to give you more feedback without knowing more. If you don't want to
focus on growth and realistically take VC money, YC might not be for you
(these are generalizations, I'd argue Wufoo was a YC success story and they
barely took any money at all).

~~~
asimuvPR
This is great feedback. I will make sure to contact YC and simply ask them.
I'm not really interested in VC but the network seems very valuable.

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x0x0
Hmm. I'm only half serious, but if anyone wants to compete with mylan/epi-pen
ping me.

They've taken the price from $100 to $500+ over the course of a decade.
There's got to be a way to (1) make epi-pens for $25-$50 (which mylan does),
(2) sell them for $50-$100, (3) get stupid rich (4m sold per year in the us
alone), and (4) do good for the world as well.

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poppingtonic
I watched Chad Rigetti's talk
([https://www.youtube.com/watch?v=GzMvG8UO6Eg](https://www.youtube.com/watch?v=GzMvG8UO6Eg))
this morning, which was really exciting.

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dammitcoetzee
Alright. I'll apply. I'm barely through the business model stage, but I'll do
it. I'll lose some sleep, but if YC is serious about hardware then ok.

~~~
jayjay71
If you're starting a company, be prepared to lose a lot of sleep moving
forward :]

Shoot me an email [redacted] and I'll help you with your application if you
want.

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mannanj
Cool!

------
CalChris
"We look for brains, motivation, and a sense of design. Experience is helpful
but not critical.

Your idea is important too, but mainly as evidence that you can have good
ideas. Most successful startups change their idea substantially."

Could you possibly be more la dee dah?

