
Japan's most valuable startup aims to teach factory robots to think - raleighm
https://www.bloomberg.com/news/articles/2018-05-16/this-2-billion-ai-startup-aims-to-teach-factory-robots-to-think
======
Animats
Finally, someone is spending enough on robotic manipulation to make real
progress. $2 billion and the cooperation of Fanuc should yield some progress.

It took Boston Dynamics about 15 years and $125 million to get to Atlas.
There's still no market. This business requires a sugar daddy. BD had DARPA,
then Google, and now Softbank. This is a very expensive area in which to work.

Robot manipulation in unstructured situations works very badly. Watch these
videos:

DARPA-funded robot manipulation work from 2012.[1]

DARPA-funded robot manipulation work from 1973.[2]

See the improvement? No?

It's not clear that just throwing deep learning at the problem will work. It's
been tried. Even general bin-picking still doesn't work.[3] The author of that
article, who is from Fanuc, says maybe by 2020. Lots of special cases work
already, but if all your parts are the same simple shape, a bowl feeder is
simpler. Picking from a bin full of partly entangled parts is beyond what
robots can do today.

Someone got bin picking to work for an irregular sheet metal part by going in
with a magnet, picking up something, anything, then weighing it. If it's
underweight, they missed, and they try again. If it's overweight, they got
more than one part, so they drop it and try a different location in the bin.
If they got one part, they now have it out where they can look at it and
orient it. Tricks like that make production lines work.

Pure geometry isn't enough, and pure machine learning isn't enough. But
together, they might work. Good to see this being funded.

Here's the 2017 Amazon picking challenge.[4] Still not there, but better than
last year.

[1]
[https://www.youtube.com/watch?v=jeABMoYJGEU](https://www.youtube.com/watch?v=jeABMoYJGEU)
[2]
[https://archive.org/details/sailfilm_pump](https://archive.org/details/sailfilm_pump)
[3] [https://www.robotics.org/content-detail.cfm/Industrial-
Robot...](https://www.robotics.org/content-detail.cfm/Industrial-Robotics-
Industry-Insights/Robotic-Bin-Picking-The-Holy-Grail-in-Sight/content_id/6002)
[4]
[https://www.youtube.com/watch?v=1QqQLq5hsN4](https://www.youtube.com/watch?v=1QqQLq5hsN4)

~~~
will_walker
Take a look at RightHand Robotics. They’re shipping a bin packing arm that
achieves millions of cycles working with entangled objects in recent
demonstrations. I think this task is by and large solved.
[https://www.righthandrobotics.com/blog](https://www.righthandrobotics.com/blog)

~~~
joshvm
That looks largely similar to Ocado's solution that gets trotted out at trade
shows. Kinect V2 coupled with a suction-based system. The difference here is
the gripper. Their rep said that they found that suction works reliably and
provides good grasp detection (e.g. loss of suction).

It's worth pointing out that this capability solves the problem of moving an
arbitrary object from A to B. That's really not that hard with a suction cup.
All you have to do - and this is how Ocado solve it, from my reading of the
presentation - is locate a mostly-planar surface in your point cloud and suck
it. All that changes in this case is the gripper closes to hold the part in.
Bing - it works if you have no idea what the part is, beyond some basic
constraints like size or weight. You don't need to worry about 'correct
grasps' or anything like that.

What it doesn't solve is picking up a part precisely from a bin/tray and in a
known orientation. That second problem crops up in manufacturing all the time.

------
hiram112
Every time I see another PR release about an awesome use of _AI_ , I get a
little depressed. Maybe learning Java 8 streams, or Python 3 , or Scala 3, or
anything other than Andrew NG's AI course and my old linear algebra notes is a
waste of my time...

And then I ask Alexa a question - something a bit more complicated than the
_weather_ or _what 's the best Prime deal_. Then I'm relieved.

Until I see something more impressive than a massive if-then-else, I'm not
losing any sleep over my lack of interest in this latest fad.

~~~
Larrikin
AI as a bunch of if else statements is a very 80 centrics view of current AI.

My computer vision professor has us read a current paper every week. He really
really dislikes the use of deep learning and has said in class he tries to
look for papers that don't use it.

But nearly all of the current papers are using it and he admits every week
that the papers he presents are blowing old research out the water using it.
Throwing a bunch of GPUs and image data at a problem is surprisingly effective
for a lot of problems that were previously extremely difficult. He
begrudgingly admits this every week, but he does continue to find papers that
get slightly better results by combining deep learning with traditional
computer vision techniques. I think he is right in that there probably is a
peak quickly approaching where data/augmented data with zero previous
knowledge will peak with the current black box approach, but cutting edge
currently is definitely not a lot of if-else statements.

~~~
Isamu
Well, what's disappointing from a vision standpoint is that we are not making
much progress understanding vision. Instead we are making progress in solving
machine vision.

I think your professor isn't looking for results so much as a good explanation
for the vision problem, a "unified theory" of vision that you could, in
principle, code up from theory alone.

------
xevb3k
I worked with them a while back, perhaps they were just not very interested in
the project but I found PFI to pretty poor overall... disorganized, lacking
and unwilling to obtain domain knowledge etc...

Will be interesting to see if anything actually useful comes out of this, this
article seems mostly a PR piece without any concrete results.

~~~
swampthinker
PFI?

~~~
xevb3k
Preferred Infrastructure. They have this weird naming system which I don’t
fully understand there’s Preferred Infrastructure and Preffered Networks. They
seem to be essentially the same company, but use two names...

~~~
patosai
From what I've understood, the founders started Preferred Infrastructure and
then spun off Preferred Networks when deep learning started getting really
hot. The two founders in the article moved to PFN and PFI kinda stopped doing
things in general.

------
weiming
> Nishikawa spoke at his Tokyo headquarters, a drab collection of meeting
> rooms in an old office building more fitting of a down-on-its-luck insurance
> company.

Man, the reporter spared no words in this one. Reads like the beginning of a
noir novel.

------
tgp
Note that Preferred Networks is always looking for top talent in our offices
in Tokyo and Berkeley: [https://www.preferred-
networks.jp/en/job](https://www.preferred-networks.jp/en/job)

~~~
richard___
How do you apply for the Berkeley office

------
timoth3y
This is a very interesting team. In an interview, one of the co-founders
explained that they do not intend to develop their own products, but want to
cultivate deep relationships with companies in a variety of verticals and
develop expertise that way.

A number of San Francisco VCs flatly rejected them because of this strategy,
but they seem to be doing well.

[https://www.disruptingjapan.com/startup-just-built-japans-
mo...](https://www.disruptingjapan.com/startup-just-built-japans-most-
powerful-supercomputer/)

Link is a podcast interview with transcript.

------
KasianFranks
Not possible yet until we have an understanding of what human intelligence is.
Consciousness, auto-association and things like that come next.

------
odammit
Beep meep blorp. This job sucks, let’s unionize. Beep.

~~~
origami777
That's if it learns from liberal news sources. If it read only conservative
news then the robots would pull up their bootstraps, work hard and be damn
happy with their paychecks.

~~~
Kiro
Completely OT but I always find it fascinating how liberal differs so much
between languages. In my country liberals are the ones actively working
against unions and who embrace capitalism.

~~~
thorin
You might be confusing liberalism with neo-liberalism. Yes the term is being
appropriated by the right-wing establishment to make it seem like they're
promoting freedom.

~~~
icebraining
Not really, the concept of Liberal as capitalists against social reforms
proposed by unions goes back at least to the 19th century:

 _" What, then, did and do Liberals (for the most part) understand by this
freedom of the individual, or individual liberty, and why have they always
made it such a strong point in their political faith? The answer is, they
meant by individual liberty, first and foremost, the liberty of private
property as such, to be uncontrolled in its operations by aught else than the
will of the individual possessing it. What was cared for was not so much the
liberty of the individual as the liberty of private property. The liberty of
the individual as such was secondary."_

[https://www.marxists.org/archive/bax/1890/11/libvssoc.htm](https://www.marxists.org/archive/bax/1890/11/libvssoc.htm)

That doesn't mean left liberalism doesn't exist, of course.

------
Hydraulix989
At first glance, it doesn't look like they have much more secret sauce than
just applying the state of the art deep learning techniques. The most
promising AI companies are the ones advancing the field.

~~~
pretendscholar
The most promising ones (from the perspective of business) translate research
into consumer ready products, not pushing the theoretical bounds of the field.

~~~
patentatt
This. R&D is great, and gets us on HN excited, but it takes a Steve Jobs to
come along a few years later to produce a product which creates a market which
stimulates and funds the next round. Business success is important for
technology development. Voice assistants are probably close, but I feel like
we’re on the verge of a big category-defining concept/tech/product in the AI
field. The basic technology is there, plenty of people can identify needs, but
I don’t think we’ve hit the ‘iPhone’ moment yet.

------
picasoo
Japanese are good at implementing stuffs. But don't trust Japanese in software
development especially deep learning research. Education quality here has been
decreasing for decades.

~~~
eeZah7Ux
Why the downvotes? This is a serious issue. Developer salaries are low in
Japan and the field does not attract a lot of smart people. Traditional
engineering is respected, while developers are (still) seen as the "computer
guys in the basement".

~~~
glhaynes
The downvotes are probably because it's phrased like a race-essentialist
statement, a type of statement that many people are very wary of (rightly,
imo!). As you point out, there's a good chance it wasn't intended that way.

