
Microsoft forms new 5,000-person AI division - cosmoharrigan
http://www.geekwire.com/2016/internal-email-microsoft-forms-new-5000-person-ai-division-top-exec-qi-lu-leaving-bike-injury/
======
dave_sullivan
To put this in perspective, 5000 people at $200k per year (which is
conservative if you include benefits, etc.) is 1 billion dollars in comp per
year.

So OpenAI is spending a billion dollars over the next several years.

Microsoft is spending a billion dollars per year.

Google, etc. do the math.

There's literally billions of dollars now being spent on moving deep learning
forward. Pretty amazing when I think back to 2011 and there were machine
learning conferences where literally no one I spoke to had heard of deep
learning.

People worrying about a second AI winter are like the people that have been
worrying about an "internet bubble" since 2004. It's fine to be worried, there
will be bubbles, but this time it's different and there are many reasons for
that. There is no "internet industry" anymore; it's become more segmented and
just plain _bigger_. Similarly, there will be no "AI industry"; it will branch
out, and there are more potential applications of "understanding data and
automating decisions" than there were in the 80s.

> something that they are branding AI - I might wait and see how much of it is
> on real AI - what ever that is.

Yeah, I wouldn't get hung up on that, they're calling it AI because that's
easier to explain to reporters than deep learning. The difference is deep
learning techniques are already being used in released products and companies
are looking to do more of that, so there is a very real definition and set of
goals associated with what these groups are doing, it's not just, "hey
everyone, let's make an ai!"

~~~
johnward
>(which is conservative if you include benefits, etc.)

I've never been able to figure out how my employer says I cost them $280 per
hour.

~~~
what_ever
$280/hour is $280 * 40 * 52 = 582400/year btw. I think your figures are off.

~~~
johnward
I need to bill out at an amount higher that that to be profitable to the
company. They don't pay me anything near that.

~~~
NikolaNovak
Depends what you do.

If you are client-facing consultant, your billable rate is paying:

\- Your salary

\- Your benefits

\- Your expenses (travel, per diem, equipment, software, anything else)

\- And then... Salary, benefits, expenses of all your NON-client-facing
teammates: Salespeople, marketing, management, client relationship,
administrative, HR, etc.

So as a consultant, you are the product, and as such have to be sold at a
price that nets enough profit to pay for rest of the organization.

Normally when they say "you cost $150/hour", what they mean is, "you, and all
the support framework behind you, needs to be billed at $150/hour to pay off".

Hope that helps. If you're in-house developer and not client-facing, it's
harder to understand and justify cost figures, but typically would be nowhere
near that rate...

------
delegate
I feel like, as a solo app developer, I'm being left out of this 'revolution'.

It seems like deep learning only makes sense if you have enough data to feed
the algorithm with. The kind of data that only big companies can produce or
harvest.

Sure you can produce some video and audio data and you can spider the web a
little bit, but that doesn't even come close to the resources that these big
corporations have and the 'depth' of learning that they can achieve.

So I'm not even trying.

Or should I ?

Is there any place for solo/indy developers in this field ?

~~~
SwellJoe
I've just started tinkering with deep learning for a solo project; I
recognized pretty quickly that there are many areas where I can't "play with
the big boys", but I also realized there's a lot of low-hanging fruit that
_is_ accessible to me exactly because the big guys are open sourcing so much.

So, I can build products that aren't big enough to interest Google, but
include a bunch of tech developed by Google (and others) and leverages their
APIs to provide a unique service that is feasible for me to build, and will be
useful to a wide variety of people. I can offer it for very little money (one
person's side project), and hopefully have some fun learning about deep
learning.

I'm so new to it that I'm not even thinking about advancing the state of the
art or doing novel work. But, in a couple of years, who knows. Just tinkering
with things in a new industry often provides pathways to cool stuff because so
many doors are opening all the time. This is like being involved in the
Internet in the early-to-mid 90s. You probably won't become the next Google,
but the odds of finding a highly profitable smaller niche seems pretty high.

Also, there's going to be a _ton_ of acquisitions in the AI/deep learning
space over the next decade. Every company that even does a little tech will
"need" an AI story to keep their investors happy. Your tiny thing could be one
of those acqui-hires, or maybe not.

Then again, if you have an interest in other stuff, and really don't feel
excited about it...probably not worth forcing yourself to get into it. Life is
short, you should do stuff that's fun, even if you have to ring the cash
register now and then.

~~~
liamzebedee
Could you provide an example of a project you'd develop? :-)

~~~
SwellJoe
I'll be posting a Show HN post in a few weeks with one of those ideas.

But, there's a bunch of ideas I've brainstormed around using things like
sentiment analysis and other kinds of very simple-to-use AI concepts for
automating tedious stuff. Things like automatically triaging support requests
based on how angry the customer sounds, or based on keywords and an analysis
of earlier requests; off-the-shelf NLP algorithms can do this today (and
Google uses it that way for their own support tools, but doesn't make it
widely available in that form, though Inbox has some of that kind of tech
working in it). All you need is training data and some familiarity with
Python.

My brainstorming exercise goes something like this: Append "with spooky
powers" to a bunch of common things until one of them seems cool and useful to
me. So, "forum notifications bot with spooky powers", "IRC bot with spooky
powers", "twitter bot with spooky powers", "customer relationship management
with spooky powers", "analytics with spooky powers", "server monitoring with
spooky powers", "log analysis with spooky powers", etc. And I try to think of
what I would use such a thing for, if it existed. Then, I sit down and see if
I can make it real. The Yahoo NSFW image detection announcement reminded me of
ideas I had and tinkered with a decade ago when I worked on a content
filtering system for schools...the difference is that now we have the
horsepower, the data sets, and the algorithms to actually make it work (but, I
haven't worked in that field in a decade and never really liked being a
purveyor of censorship tools, even if only for children, anyway).

Anyway, the possibilities are kinda huge and wide open. Many of these ideas
will fizzle out, even the ones that look promising, but as with the Internet a
lot of millionaires are going to be made by people saying, "It's like X, but
with AI." just as people used to say, "It's like X, but on the Internet."

~~~
sudoscript
That's a really neat way to brainstorm. Let me add one more thing.

The big companies have an advantage in hardware and research. But they dont
care about niche applications of their tech, because prizes worth less than
$1B don't matter at their scale. That's where I try to focus on.

The key challenge is data. Too many AI startups get stuck in the "give us your
data and we'll do some awesome stuff." That almost never works.
[This]([http://mattturck.com/2016/09/29/building-an-ai-
startup/](http://mattturck.com/2016/09/29/building-an-ai-startup/)) talk does
a really good job explaining why. The trick is figuring out how to get enough
initial data to deliver value upfront.

~~~
SwellJoe
Good slide deck, and I agree with most of it (and what I don't agree with is
probably my own ignorance of the field).

I suspect there will be very few "pure AI" startups, and a ton of regular old
tech startups that figure out how AI fits into their business faster than
their competitors or figure out how to use it for a business advantage or to
deliver a service that couldn't exist in that way before AI. With the early
"like X but on the Internet" startups, the ones that succeeded in the biggest
way (Amazon, for example) were the ones that built a _great_ X that leveraged
the internet to make it an order of magnitude better X.

So, Amazon was the best book store because they got everything right about
being a regular bookstore (good prices, good service, efficient sales channel,
solid relationships with publishers) _and_ had damned near every book and
could serve customers everywhere; a thing that is only possible on the
Internet.

So, the best "X except with AI" company will be a great X company, and then AI
will allow them to do some kind of force multiplier to push them to the top of
the heap. That means we need to look for opportunities that currently require
a lot of resources (say, people, or vehicles, or ) and can have AI added to it
to make it produce 10x value given the same inputs. Even 2x value could be a
big enough difference to beat your competitors at market, but the real out-of-
the-park success stories probably need an order-of-magnitude boost from AI,
even if it starts out slower because AI is still clumsy and most of the small
companies are starting with tiny data sets (relatively speaking).

Anyway, mostly I think it's cool to play with. I _think_ I see some ways to
provide value and make some money with it, but it'll be as much an experiment
as a business plan in the short term.

------
vessenes
A friend of mine was an early investor in DeepMind. For like a year and a
half, because that's how long it took Google to buy them out for somewhere
around $400mm.

At the time, I thought that sounded like an amazing exit (OK, it still sounds
like an amazing exit), and wasn't clear how Google could get that value out in
a reasonable timeframe.

I was so, so, wrong. The amount of value hidden and public in that acquisition
is astounding. Whoever put it together deserves a massive bonus, ideally in
Alphabet stock.

MS putting $1bn a year in on AI is a catch-up game. They may do very well at
it, but make no mistake -- we are only seeing the public side of the value
Google is generating. I don't imagine we'll ever see blogposts about how
they're tuning adwords using AI, for instance. But you can bet the same sort
of gains they are seeing with translations, audio generation, game playing
they are seeing in the ad space.

~~~
jomamaxx
" and wasn't clear how Google could get that value out in a reasonable
timeframe."

Tell us, how the valuation can be justified in terms of dollars.

Which 'AI' products are useful in the portfolio today, that makes products
useful to you and I, that are derived from DeepMind?

The fact is - 'AI' is really short-hand for Multi-layer Neural nets - and they
are applying those things in some very specific areas such as voice
recognition and image recognition.

I think there will be many more places where we can do this - but I think it's
going to be a very long time before we get to 'true AI'.

~~~
AJ007
[https://deepmind.com/blog/deepmind-ai-reduces-google-data-
ce...](https://deepmind.com/blog/deepmind-ai-reduces-google-data-centre-
cooling-bill-40/)

~~~
jomamaxx
Admittedly, that's pretty 'cool' (pun intended) but not $400M kill. I think we
still have a long way to go to see AI reap direct rewards for consumers.
Payoffs have been minimal/incremental for now.

~~~
jsmthrowaway
Do you have any idea how much it costs to cool a datacenter?

~~~
jomamaxx
Not $400 Million dollars.

------
kens
Reading this carefully, the 5000-person group is "AI and Research" not just
AI. (5000 people would be a lot to have working on AI.) This group includes
Bing, Cortana and the current research group, so there are a lot of people not
working directly on AI. That said, it is a significant change in focus, making
AI a priority.

~~~
danielcampos93
Correct. The team still includes everyone who works on Bing and essentially
the Non Office part of what Qi used to run. Its less 5000 person AI Group as
5000 people running various businesses whose collective mantra is now AI.

------
beau26
We seem to be at an inflection point with AI -- companies across the board are
investing billions of dollars into AI R&D and I expect that we'll start to see
some really amazing products and services coming out of this in the coming
decades.

~~~
phreeza
It's either that, or a great disillusionment in ~5 years when the investments
don't pan out, followed by the next AI winter.

~~~
a-priori
This is a real concern. But as I see it, the difference is that the last time
around, everyone was sold on the potential applications -- which turned out to
be way harder than anyone realized.

This time around, the technology is seeing real applications today, so the
valuations are more grounded in reality. So while people are definitely
investing based on the future potential, the worst case scenario -- that we're
going to hit a wall next week where no further progress can be made in machine
learning research -- wouldn't be as devastating as the last AI winter.

At this point there's a lot of work to do, and money to be made, applying the
current state of the art even if no further progress can be made.

------
pesenti
I know IBM and Watson often get a bad rap here. But IBM made the same exact
move almost 3 years ago with the creation of the Watson unit. There is way too
much PR around Watson, but IBM should be credited for having called the
current round of AI investments way before anybody else.

Disclosure: I was part of the initial IBM Watson team, left recently.

------
coldcode
I wonder if they are successful, the next new AI division will have 0 people.

~~~
js8
Same if they are not successful!

~~~
willis77
Let's call the whole thing off

------
safdeep
I love the fact that it took Ballmer to leave for them to really get serious
about cutting-edge tech again. Bill Gates are probably wishing he never met
Ballmer at Harvard.

~~~
nostrademons
Two sides to this comment:

1) It took Ballmer to leave for them to really get serious about innovating
again.

2) ...because under Ballmer, they were able to make billions of dollars
_without_ innovating.

Bill Gates is probably pretty happy about #2 even if he's not thrilled about
#1.

------
emcq
It always puzzled me why Microsoft laid off their ML heavy research group in
mountain view, and continues to puzzle me after news like this!

~~~
enigmo
a bunch of them now work at Google on the Brain/Tensorflow team. definitely
was an odd move.

~~~
abz10
This was Satya sending the strong message that no-one is untouchable and
everyone must get inline or they will be next. It's actually a common strategy
that requires the victims to be their best people. Obviously you can't to this
too many times. Politics as usual.

~~~
shostack
Can you elaborate on how that works? If the victims are their best people who
are doing solid, profitable work, laying them off seems like it would create a
state of uncertainty which, in this climate, might just cause people to jump
ship because competitive jobs are just around the corner.

Or was there some issue with the group where they had to sacrifice the good
with the bad due to lack of overall profitability?

~~~
abz10
It's about internal power, even at the expense of the companies wellbeing.
These layoffs were in the context of a larger set of layoffs that Satya
undertook as his first big move at MS. Satya was getting across the board
pushback from lots of different warring orgs at MS. He even had to bring the
Big G out of retirement to help him out. So by taking out the top dogs he
becomes the top dog. I don't even blame Satya for doing it - it's human nature
that required it. If he didn't do it he would have eventually been pushed out
of MS for not getting anything done. It's why drug cartels are so violent,
it's why our election choices are Clinton and Trump. At least he's less evil
than Sinofsky and Ballmer who were both cartoonishly horrible.

Good people have been leaving MS for a very long time. But big company
corporate politics are really toxic in the US. MS is actually one of the
better ones. Intel, Amazon, Netflix are much worse. Facebook and Google are on
the decline. Yahoo.... yeah

As for this AI thing, my bet is that it is mostly fluff. Most people will
ignore it until the next re-org comes along. There was a similar thing with
Big Data at MSR a number of years ago and look what happened there.

------
graycat
So, Microsoft is going to put 5000 people on applications of artificial
intelligence (AI). Likely they will also include machine learning (ML).

IMHO, there is some value there.

But, IMHO they would be better off just drawing all they can, including AI/ML
but much more from the QA section of research libraries. There they will find
oceans of material, where in comparison AI/ML look like farm ponds, in pure
and applied math as math but also operations research, statistics,
optimization, control theory, applied probability, stochastic processes,
mathematical finance, mathematical parts of high end electronic engineering,
signal processing, experimental design, quantitative methods in business, and
much more.

------
thr0waway1239
Despite the general positive spin around it ("we did it as a learning
project"), most people would agree that Tay was both a technical and a PR
failure.

But the pattern does repeat: Microsoft releases an AI which fails. Tesla's
autopilot cannot "see" white object on white background. Apparently, Google
also had a crash which is recently being claimed as human error. My guess is
that this list is not going to stop here.

Suppose I ask you to build me a teleporting machine. You try, and like the
movie Spaceballs, my torso and up comes out aligned wrong. This is now
declared part of the iterative learning process, except that the cost borne by
the corporations for the failure is quite minuscule compared to the cost borne
by the affected party (risk asymmetry).

So while people talk about the huge advancements in AI, shouldn't we be quite
skeptical especially at this point? Since none of us have seen the alternate
parallel universes, and considering

a) the resources being thrown at the problem

b) the risk asymmetry involved

c) the privacy intrusion involved in the data collection (you knew I would
bring it up, didn't you?) and not to mention

d) the inability of anyone to demand any kind of transparency from these AI
pioneers

I can as well ask, are we as a society paying too high a cost for this
progress? Could we really not do any better than this?

~~~
danielsada
Certainly interesting ideas, but we only need an AI that is better than the
current paradigm. If Teslas doesn't detect a white object, it is not as heavy
as a human sleeping in the wheel. So if Tesla's kill 30k people a year, but
humans die in the wheel at 120k people a year, an improvement would be nice,
as it avoids 90k deaths a year. So if we are already using teleporting
machines (and we accept the tradeoffs of using it, like cars) and 1 in a
million fails, if AI makes a failure in 1 in 10 million, clearly we should use
that technology right?

So as Elon musk said recently: "Whatever this thing is you are trying to
create.. What would be the utility delta compared to the current state of the
art times how many people it would affect?"

The wonderful thing about this AI algorithms is that we can rate them on their
efficacy, they might be a black box, but the input and output are always
known. If we see that google crashes 10x more cars, we wouldn't use their AI.

~~~
thr0waway1239
> only need an AI that is better than the current paradigm

This is fundamentally what is being debated here. While the current paradigm
can seem fairly poor, let us consider a few things which are true for the
human driver.

1\. He/she puts himself ALSO at risk, as opposed to the self driving system
(remember it is theoretically possible for the self-driving car to not have
any occupants at all. It is potentially only a matter of time before it
happily wades through stand-still traffic to go and buy grocery for you).

2\. He/she is not, in the process of being/becoming a good driver, also taking
away personal freedoms of other people - which is effectively what is
happening when the megacorps collect any and every piece of data they
encounter. In a recent article in the Economist, we hear about a system which
augments the autonomous cars by mapping roads in extremely high resolution.
[1] Remembering all the work Google does to occlude sensitive information from
its maps, imagine how much more effort has to go into this system to have it
occlude personal details completely. Now imagine this data (which is currently
being collected by a third-party company) landing in the hands of
Google/Tesla/Uber etc. who are going to combine it with other human oriented
information (e.g. Bob always leaves his office at 5.00PM, and always swerves
sharply to avoid the pothole at so and so corner street, let us add that info
to our system and improve it).

3\. If you think the above scenario is ridiculous, then the next thing you
would probably ask for is accountability. In other words, at some point, you
are going to ask these companies to open up their data collection processes
and algorithms to the world. This is exactly what would happen if the entire
thing were a completely OSS-based process. There isn't an equivalent problem
for the human driver, because you have sufficient faith in a human's need for
self-preservation that you will not demand a real-time thought reading machine
which will warn oncoming traffic if the human driver is having an onset of
road rage.

> So as Elon musk said recently: "Whatever this thing is you are trying to
> create.. What would be the utility delta compared to the current state of
> the art times how many people it would affect?"

This is also being debated. There are such things as side effects, and some of
them are invisible. The current state of the art (i.e. the inefficiency, or
rather the inadequacy, of humans to perform these tasks) does not, as a side
effect, also rob society of its peace of mind. Imagine if, for every piece of
information which is collected, you also had a tiny pebble placed somewhere in
your neighborhood. Soon, by the time these systems have reached the utility
delta that you are happy with, we might have a mountain the size of Everest.
Will we? I don't really know. Because it is invisible. Some people would still
be OK with it. But most people, hopefully, would want to see the size of the
hill. Is it a molehill or is it really a mountain? The lack of accountability
surrounding these questions is actually quite shocking to me. [2]

[1] [http://www.economist.com/news/science-and-
technology/2169692...](http://www.economist.com/news/science-and-
technology/21696925-building-highly-detailed-maps-robotic-vehicles-autonomous-
cars-reality)

[2] Not to mention the _other_ cascading side effects of the data collection
process itself, such as your personal data, which you don't even know how it
was collected, being collated to be made sense of and sold to the highest
bidder

------
modeless
I am intrigued by the mention of "Monthly Q&A" at the end of the email. Is
this Satya Nadella's version of Google's TGIF meetings? If so I heartily
approve.

I left Microsoft for Google in 2010 and TGIF Q&A was one of the things I
appreciated the most about Google culture (despite the occasional screwball
live question). I think any company could benefit from a similar tradition.

~~~
danielcampos93
Yeah. They host a Q&A session every month and most leader down the totem pole
do the same(Scott Guthrie hosts fireside chats)

------
Dowwie
Which office location(s) are planned for this?

~~~
danielcampos93
mostly Seattle region. Since half of the division will be made up of Bing
folks and there is a bunch of empty office space in Bellevue I would assume
most would be clustered in the Bellevue office(as opposed to the regular
Redmond Campus)

------
hindsightbias
It's funny, the internet isn't old enough to find links to the CYC project in
Austin that blew through hundreds of millions of DoD money in the 80's and
early 90's.

What's old is new.

~~~
Animats
Cyc and Lenat are still around.[1] Here's Lenat at SXSW 2016.[2]

[1] [http://www.businessinsider.com/cycorp-
ai-2014-7](http://www.businessinsider.com/cycorp-ai-2014-7) [2]
[https://vimeo.com/158956032](https://vimeo.com/158956032)

------
sam36
What is the current fascination with AI? It seems to be talked about
everywhere right now. Yet "AI" in a core sense has been around since the
70's...

~~~
mkehrt
In the past few years, both the hardware caught up to and new practical
techniques have been developed for multilevel neural nets (deep learning). It
turns out that these are very effective at many problems that were not as
amenable to earlier techniques. The theory of neural nets has been around a
long time, but there has been a recent increase in the practical applicability
of them.

------
visarga
With a billion I could get a cloud of 10,000 servers with 16 GPU cards... mmm,
lots of GPUs...

Or 5000 employees and 5000 servers each with 8 GPUs.

~~~
ww520
$100K for one server? Those are darn good servers.

~~~
jsmthrowaway
In this case, it's the GPUs. High six figure servers aren't unheard of in the
commodity world (even before you start talking about bigger iron).

Oh yeah, and one word: Fusion-IO.

------
randartie
How can they possibly staff a 5000 person ai division. Sounds to me like only
a small-ish subset will be talented ai researchers.

~~~
fma
You're probably right. There's always overhead to a project. Testers,
Analysts, Managers, Dev Ops...

------
amirathi
How do you really start a 5000 person division at once and expect to succeed?

I assume AI development is a niche field. And you would want smaller dedicated
teams of brilliant researchers and practitioners focusing on a single problem.

I can't imagine the overhead in maintaining and operating such a large
division. I hope they know what they are doing.

------
pazimzadeh
Something something mythical man month?

~~~
jomamaxx
Exactly.

The bulk of 'practical AI' don't come from massive products, like 'Office' \-
but from very specific neural algorithms, applied to very specific things -
done by a few people.

That said - this kind of research may benefit from a lot of concurrent
research.

Also - there are a couple of strategic issues:

1) Prestige - it's important to be recognized as 'a leader' to maintain brand
cachet among tech talent

2) Talent Hoarding - Google, FB and MS are each big enough to tilt the
landscape in any specific field. It's actually economically viable for them to
pay the best talent to sit in a lab and fiddle, even while accomplishing
little, over letting the talent go to competitors.

------
jacquesm
5000 more people working hard to make themselves obsolete. I wonder how long
it will take those working on AI to figure out that they're doing to
themselves and the rest of the IT industry what the IT industry has already
done to many others. If and when they succeed we'll finally know the true
meaning of the term disruption.

~~~
icebraining
Why do you assume they don't know what they're doing? I'd be happy to get a
nice salary to work on making myself obsolete.

------
j2kun
Let's hope they don't fire them all like they fired their research staff at
MRSV

------
desireco42
Look and then in few years they will have to fire those people.

------
macawfish
Get ready for patent disputes.

------
andrewfromx
there's a really funny paper clip from office 95 joke here somewhere.

------
pjc50
Prepare for Clippy 2.0!

(Joke; Microsoft Research are actually highly respected, it's just that like
Xerox they have some trouble turning it into products)

~~~
DanBC
[http://robotzeitgeist.com/tag/bayesian-inference-
engine](http://robotzeitgeist.com/tag/bayesian-inference-engine)

Clippy is an interesting case because they had a good product and then they
downgraded it for reasons.

It's kind of frustrating that they could have introduced something brilliant
but chose not to.

~~~
douche
The Clippy for Resharper[1] extension is my second favorite joke extension
after the Visual Studio Achievements[2] extension.

[1] [https://blog.jetbrains.com/dotnet/2014/04/01/clippy-for-
resh...](https://blog.jetbrains.com/dotnet/2014/04/01/clippy-for-resharper/)

[2]
[https://blogs.msdn.microsoft.com/zainnab/2012/02/28/visual-s...](https://blogs.msdn.microsoft.com/zainnab/2012/02/28/visual-
studio-achievements/)

------
snippet22
Maybe it'll make windows better.

