
Andrew Ng launches $175M AI fund - dsaw
https://techcrunch.com/2018/01/30/andrew-ng-officially-launches-his-175m-ai-fund/
======
urlwolf
Andrew Ng's VC fund will use their own teams instead of listening to pitches.
What can we read from this? (1) the market is saturated with 'wannabe
startups' that talk about ML but don't have a clue (2) VCs get many of these
pitches 'X but with AI' with noone knowing ML in the team.

Andrew has the reputation to do this and not be hated. But you know who did
exactly this? Rocket internet, the clone-war masters.

------
nora4
"In his view, AI businesses are also different from regular startups because
you generally get a closed feedback loop that allows you to quickly see what
works (and what doesn’t)."

What is he talking about here? First of all, this is just the basic lean
startup methodology. Any startup (especially consumer ones) try to do that,
i.e. A/B testing new features. Second, he may be referring to the case that
once you have a big comprehensive dataset already gathered, then you can just
iterate improving the model.

My (cynical) answer: good luck with that. The real issue with AI especially in
mission-critical situations is data in edge cases. Even if you can improve on
your train/test data, that barely translates to customer satisfaction unless
the edge cases are treated well. And edge cases will be revealed very slowly
by encountering data in the field. Just ask anybody working on voice-assistant
agents (Alexa, Siri, Google one) or self-driving. It's not a fast loop by any
means.

Of course, Ng probably knows all this which makes me feel even more bothered.

~~~
otoburb
>> _Of course, Ng probably knows all this which makes me feel even more
bothered._

Ng's implied claim is that he has a head start on how to tackle the edge
cases, along with other hard problems encountered in the field, based on his
experience at Baidu. This is what got him the "easy" capital raise. If he
really has an edge (no pun intended), then it makes sense for him to apply it
while it's still relevant.

~~~
nora4
Maybe. Part of me thinks it's somewhat of a small money grab. (hope it's not.)

What I will bet money on though is that no _massive success_ will come out of
this. The key to AI is data & hardware (and not algorithm or methodology --
where everyone is essentially doing the same) and that's the domain of already
giant tech companies. There can be a lot of good use cases in teaching far-off
industries on how to use AI (manufacturing, etc.) but that's essentially a
consulting business which will have a limited window. So lots of little
successes is completely achievable; massive successes I hardly doubt.

------
oneiric
[https://www.aifund.ai/](https://www.aifund.ai/)

~~~
tylerruby
Thanks for this

------
thisisit
I am surprised it took so long for this to happen. Ideally speaking you would
want the famous ML guy to help you in vetting any startup claiming to solve
the problem using AI/ML.

------
strin
“One of my philosophies of building companies is the importance of velocity,”

True. And the key to keep (increasing) velocity is momentum. I believe the
fundamentals to that is _infrastructure_. Once you get to the "flywheel stage"
of an AI company
([http://nicodjimenez.github.io/2018/01/25/stages.html](http://nicodjimenez.github.io/2018/01/25/stages.html)),
experimentation becomes so easy that new models can be rolled out nightly.

~~~
ogdoad
Actually the key to keep increasing velocity is maintaining a positive dv/dt,
that is to say, acceleration. Momentum is more of a tendency to refuse to
leave a state (think of `inertia-in-motion`), rather than actively seek it.

If that makes any sense at all, that is.

------
matte_black
I remember when he was just a guy teaching me machine learning.

~~~
jtmcmc
yeah but before that he was a super fucking famous ML researcher.

~~~
matte_black
“Our next guest needs no introduction...”

------
mark_l_watson
Now I now why Andrew is two months late delivering the final 5th class for his
deep learning Coursera specialization. He has been busy!

This is really a different kind of venture, and it will be interesting in a
few years to see how they do.

~~~
yeukhon
Final as in this will be the last time Ng will teach the course?

~~~
andyjohnson0
> Final as in this will be the last time Ng will teach the course?

Courses on Coursera aren't really taught that way. The course instructor(s)
prepare the course materials (videos, presentations, quizzes, assignments,
etc.) once only. Courses start on a regular schedule and the platform, rather
than the instructors, takes you through the material in sequence. There are
forums with moderators for peer-support, but you don't typically interact with
the instructors as they're not really there.

I assume the OP is referring to Ng building the fifth of the five courses that
comprise the specialisation.

~~~
yeukhon
I see, although I have seen some refresh contents in other courses on
Coursera. Good to know he has a series of courses.

------
solipsism
Sounds incredibly similar to Phil Libin's project: [https://all-
turtles.com](https://all-turtles.com).

Phil Libin is the ex-CEO of Evernote.

Maybe there's room for multiple players in this space, but I imagine the name
recognition and bona fides of Andrew Ng is going to suck the air out of All
Turtles.

~~~
shafyy
I have a feeling that Andrew's fund is much more focused on cutting-edge AI
than Phil's. If you take a look at Phil's portfolio, you see can see that the
companies are probably using some form of AI but that's not the core of them.
Also, in my personal experience with talking to Phil, it seems that for him
the "practical AI" part is more important than what kind of tech is used. So,
maybe a more consumer-focused perspective (which I like).

I can imagine that Andrew focuses more on companies that have or have the
potential to have significant AI themselves. I doubt that Andrew would
consider a bot that uses the Google Vision API and Dialogflow an "AI" company.
If that makes sense.

PS: I do think that the latter should be considered an AI company. Just like a
company using AWS to host is called web company. In fact, probably a lot of
companies will be using some sort of AI api pretty soon.

------
Laurentvw
Sounds interesting! Does anyone have examples of AI startups that solve real
world problems? Just trying to get a picture of what companies would fit their
fund.

~~~
agibsonccc
We're "horizontal".

We would not fit his definition of a vertical specific startup. (We have also
been around a while though) The bulk of what we do is time series.

Applications we do for real paying customers include:

Detecting theft of power on the raw grid

Online payments fraud

Detecting people stealing from the telco network

Detecting faults in assembly line machines

Detecting computers about to fail

Detecting root cause of dropped calls

Kind of researchy, but we've also done robotics with RL to teach a robot to
learn an obstacle course.

~~~
Nasho
Tell me more, who is 'we' ?

~~~
nora4
Just look at his profile (a click away). He is the founder of Skymind.

------
ccozan
As other fellow commenters remarked, and as an AI enthusiast/researcher
myself, I fail to see AI as a business. What I would like is a fund, or
similar that is funding research, because fundamentally we need so much
research in this area.

AI as we have it now is just a bunch of ML algos and *NNs that perform well in
different niches and, well, after all cat pictures were categorized, what to
do next?

So, in case Andrew is reading this post, I would like to have a chat with him
about my research ideas and if they could be funded. Because if this happens,
many more would follow and then we can see a real progres towards real/hard
AI.

~~~
CabSauce
There are tons and tons of meaningful uses for the current state of ML. Just
about every industry is full of opportunities to apply the most basic
algorithms and drive tremendous value. It goes without saying that research is
still valuable, but what I haven't seen yet is large, widespread use of
applied ML.

~~~
ccozan
Of course ML has his uses, even now I am doing fully industrial ML. But, in
the end, is just an algorithm/NN that does what your suppose to programm it.
And is a heck of manual work involved.

AI is on a different scale andmay have less to do with the actual
implementations.

------
danjoc
The amount of money in this field puzzles me. The difference between relative
novice and competition winner on kaggle.com is often in the single digit
percentages or less. When 26 year old George Hotz can build his own self
driving car in his garage, it seems like a very narrow moat.

~~~
otoburb
You make it sound like George Hotz is any run-of-the-mill 26 year old, except
he's anything but[1].

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

~~~
danjoc
But the point is, for $3M I can fund George Hotz and have an entry in the self
driving car arena. For nothing, I can go grab open source code and be a small
percentage away from the absolute state of the art.

How do companies justify such a tiny edge as being worth so much? I wish
Andrew Ng the best. I do. He's a class act. I enjoyed his course years ago,
but came away a little disappointed. At the end, I realized there's no
intelligence in the algorithms. It's all just applied statistics and a lot of
sweat preparing training data.

Maybe I should just shut up and vie for some of the easy money sloshing
around. I think I would just feel weird asking for a ton of cash when the end
product is just a bit of recursive math.

------
beambot
He announced that he was raising the fund 5 months ago [1]... surprised it
took so long, honestly.

[1]
[https://news.ycombinator.com/item?id=15028322](https://news.ycombinator.com/item?id=15028322)

~~~
hkmurakami
Iirc Saastr wrote that raising money from LPs takes months, if not a couple of
years.

------
xvilka
I hope this fund wont be limited by only ML, but also will work on formal
logic approaches.

~~~
gota
I don't think anything other than ML will be funded like that for a while.

We are on the very top of that hype curve, a few of years from now we'll
forget how absolutely stupefied we were when ML gave us models that "can X
better than humans" and the enthusiasm will give way to a feeling of "I
overpaid for this". It happened before with databases way back when, then with
specialist systems, then ...

The only difference is now the layperson hears about it with an astounding
frequency. I don't know, maybe that will make things different but I can't see
it having any other effect than making that 'disappointment crash' harder

------
CodeCube
I wonder if anyone who has received an
[https://aigrant.org](https://aigrant.org) will make their way over to aifund

------
bitL
How to apply to become a company supported by his fund?

~~~
camone
There's a contact link at the very end of their webpage:
[https://www.aifund.ai/](https://www.aifund.ai/)

------
ejanus
This guy has enormous energy . How can I copy him (1%)?

~~~
tylerruby
Red Bull

------
debt
I really think to achieve actual AI we need a new material other than silicon
but idk

~~~
nora4
Like H2O and carbon and stuff?

~~~
quickthrower2
No that would not give you the A, or the I from my experience.

------
make3
Andrew Ng for President!

------
KaoruAoiShiho
Did he just cop baidu's business model lmao.

------
igravious
I'm starting to notice that this AI malarkey is becoming a bit of a thing. Do
people recommend I take a course in it?

~~~
hobls
I'm really enjoying his ML class on Coursera. Considering taking the deep
learning series next. (And I work more than full time at a tech giant. It's
working into my schedule okay so far.)

~~~
igravious
I'm at the end of a PhD. Once I've this baby wrapped up I'm jumping on that
course quicker than you can say "rise of the robots". I've heard only good
things about it :)

~~~
mamon
What is the domain of your PhD? If it's computer science or mathematics then
you might find that ML class on Coursera too easy, way below your level of
competence.

~~~
igravious
Philosophy / Humanities Computing

