
YC AI - craigcannon
https://blog.ycombinator.com/yc-ai
======
jph00
If you're the kind of person that's interested in taking up this challenge,
but you currently have the coding skills without the deep learning skills, we
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(Sorry for the blatantly self-promotional post, but if you're reading this
thread you're probably exactly the kind of person we're trying to help.)

~~~
mbrookes
The course is excellent, and thank you for making it and offering it for free
- but a word of caution for those considering following it: Along the way you
will incur not-insignificant costs for Amazon EC2 GPU instances, and, even if
your instance is shut down, SSD EBS storage costs.

Edit: To be clear, I'm not suggesting it's not worth it, just highlighting
that theres's more than a time commitment to budget for.

~~~
mej10
Like how much? If you are going to get into deep learning for real seems like
it might be worth building a multi-GPU workstation?

~~~
taneq
Don't buy equipment before you have demonstrated a real need for it.

This applies across basically all of life, and it's so frustrating to see
people ignoring it, because what ends up happening is they use a string of
'gonnas' to justify buying stuff they don't need. Gonna get fit - buy $1500
worth of gym gear. Gonna learn electronics - buy oscilloscope, power supplies,
tons of components. Gonna get your motorcycle license - buy brand new bike and
stick it in the garage.

If you have a desktop computer, you're good to start. When you've done enough
that your available CPU/GPU is limiting you _on your own projects_ (not on
something you pulled off github) then you can look at upgrading.

/rant

~~~
foldr
>Gonna learn electronics - buy oscilloscope

A fairly accomplished electronic engineer told me that they'd never once
solved a problem using an oscilloscope, but that it helped to keep them
occupied while they were mulling over what might have gone wrong. (That's
presumably why the better ones have so many knobs and dials to play with, like
one of those children's toys.)

~~~
taneq
I've certainly solved problems with a storage scope before, but not for a long
time, and they were mostly software problems rather than hardware problems
(ie. using it as a poor man's logic analyzer to infer what's going on with the
code via a couple of spare IO pins). I really kinda want one though.

------
kolbe
As someone who's capable of implementing and understanding many of the most
fashionable tools in AI, I don't know what to do with the current economy. I
think there is far too much attention being paid to the pie-in-the-sky
research, and even though wealthy investors think the things that they don't
understand and I do are capable of accomplishing things that they think can be
accomplished and I don't, the problem is that they want to pay people like me
to chase their dream. And while I do love money, I also love the idea of
living a meaningful and fulfilling existence by pursing technologies that will
advance mankind.

Can other people who've actually seen real promise in their AI research chime
in and help convince me that we are actually on the precipice of something
meaningful? Not just more classification problems and leveraging the use of
more advanced hardware to do more complicated tasks.

~~~
d_burfoot
I don't think we are on the precipice of general AI, perhaps we are not even
close.

But we don't need fully general AI to have a huge transformative impact on
society and the economy. Think about the full spectrum of jobs that exist in
the modern world: doctor, teacher, construction worker, truck driver, chef,
waiter, hair dresser, and so on. How many of those jobs actually require the
full power of human intelligence? In my view, almost none. Maybe the
intelligence required is still more general than what a computer can do, but
probably a determined research effort could be enough to make up the gap for
any specific task (say, to cut someone's hair, you need to have good visual
understanding of the shape of the head, and very good scissor-manipulation
skills, and a good UI so that the customer can select a style. It hardly seems
like an insurmountable technical challenge).

~~~
smdz
> I don't think we are on the precipice of general AI, perhaps we are not even
> close.

In all probability, I want to agree with you.

However, deep learning unnerves me. Seriously, how many people who evolved the
deep-learning-trained models actually understand how those models work? But
the models produce good-to-great results.

So there could be a small chance that general AI could randomly and
spontaneously come into existence. Either we are too close to general AI or
infinitely far from it. We can't tell it because we are not sure if
intelligence is a evolved goal oriented function or an engineered substance.
Being an atheist, I believe the first part - and thats what deep-learning
based AI looks like.

~~~
zebrafish
A major difference here is that humans don't have user defined stimuli.

Human intelligence evolved because of the need to survive which evolved
because of the need for genetic replication. Our need to survive lead to a
nervous system which created the need for a central management platform (the
brain).

People do understand the deep-learning models they create. They're based on a
user defined limit for error which is the mathematical distance between what
is and what is not.

I think that until we have an algorithm that can rewrite itself optimizing for
existence (bug-less-ness and a continuous power supply?), we won't even
scratch the surface of general AI.

------
roymurdock
> We want to level the playing field for startups to ensure that innovation
> doesn’t get locked up in large companies like Google or Facebook.

AI and ML are exciting because they promise to help us evolve systems and
machines quickly to perform more accurately.

This requires access to a constant flow of large, proprietary datasets.

Providing cheap access to datacenters and compute power is a great first step
for leveling the playing field for startups.

I'll be interested to see how YC tackles the (IMO) more important problem of
providing access to the data needed to train models.

I think IBM has taken an extremely wise first step by acquiring the data
assets of The Weather Company. This will give its Watson IoT portfolio a leg
up on other companies that need to rely on a patchwork of public and private
data sources when factoring something as integral as the weather into
algorithms and logic engines.

Perhaps YC can consider something similar, pooling investors and VCs together
to acquire/partner with providers of essential data.

~~~
jacquesm
> We want to level the playing field for startups to ensure that innovation
> doesn’t get locked up in large companies like Google or Facebook.

It's not just the data. It's also acquisition: Facebook and Google are
figuring very large in the exit path of a lot of these companies.

Which means that after one or more years the stated goal here could be nixed.
You'd almost have to close that route before this statement is meaningful.

~~~
thr0waway1239
The two companies are like two giant vacuum cleaners sucking competition out
of the technology industry.

Taken in isolation, the two trends (data acquisition and talent acquisition)
are already disturbing. Combine the two, and you have to wonder how dumb we
actually are to allow things like Facebook's acquisition of WhatsApp.

------
petra
>> RFS: Robot Factories.

From all the places where AI could help, why focus on that field, the place
where the most vulnerable employees are found, the hundreds of millions from
china, Bangladesh, etc - who have little chance of having a meaningful Social
safety net ?

>> job re-training, which will be a big part of the shift.

I don't believe that this is realistic, even in the west. Why ? because the
internet, who is obsessed about this subject, and doesn't lack imagination,
can't even supply a decent list of what jobs will the future offer that could
employ the masses who's jobs will be automated.

~~~
austenallred
While it's true that there have been, are, and will continue to be a loss of
manufacturing jobs as a result of automation, robotics, and AI, we also need
to consider the other side of the economic spectrum, and look historically to
see what has happened when these kinds of shifts come.

For example, I'm sitting next to someone who is working on robotic apple-
pickers. The amount of cost from buying apples is about 75% represented by
labor. So yes, there would be job loss, but what if apples start to cost 25%
of what they currently do? What if we extrapolate that across all fields?

What if we could do this with everything we need - food, consumer goods,
housing, etc? It's a shift as big as the industrial revolution and moving away
from an agricultural society from a consumer perspective. In short: Life would
get much better and cheaper for all of us and _fast_.

But then there's unemployment. What will the masses do? Well, what did the
masses that used to be farmers do when we moved from 50% of the United States
being farmers to the current levels of ~2%?

The answer historically has been that entirely new types of employment are
created, and the pain is remarkably short-lived considering the size of the
shift and the decrease in costs, and the Luddites look silly in retrospect.
It's usually hard to see looking forward, but somehow it's always worked out.

I'm not sure what the entire picture looks like; I do think that we will need
massive re-education as a society, and we're completely unprepared for that.
In the past we've replaced unskilled labor with new unskilled roles, and I
don't see those roles hanging around anymore. (I moved to San Francisco from a
very rural town, and I get stressed whenever I think of the economic future of
that small town. Until there's risk-free education available at will that area
is economically doomed.

But I don't think the proper response is to slow innovation because of pending
job loss. If the AI shift will be as big of a deal as the Knternet, imagine
how much better it makes the lives of everyone - is that really something we
should actively fight against? I'd argue history suggests we shouldn't.

~~~
icebraining
_Well, what did the masses that used to be farmers do when we moved from 50%
of the United States being farmers to the current levels of ~2%?_

Didn't that work in the opposite way, though? New opportunities appeared that
pulled (sometimes forced) people away from farming; it wasn't like there was a
bunch of unemployed ex-farmers who suddenly started finding new jobs.

~~~
nostrademons
Which time period in history? In the 1830s, you'd get younger sons or
daughters of a farming family who would move away to the city to earn extra
spending money for their family and find a measure of independence; oftentimes
the eldest son would inherit the farm, so there was no place there for the
other children.

In the 1930s, the farms were themselves collapsing. Mechanized agriculture
created both a huge oversupply of produce (which drove down prices) and also
ruined the ecology of the plains, which eventually led to the dust bowl.
Farmers absolutely were forced off their land: that's where we got Okies,
Hobos, the Great Migration, _Grapes of Wrath_ , and all those other
subcultures of migrant workers from.

------
gabrielgoh
I've wanted to break into robotics from machine learning for a long time, but
I haven't found a good entry point for the problem. It seems like a rather
large vertical cliff I have no way of scaling.

One of the handholds I'd need is a physics engine which which models a robotic
arm down to the finest levels of motor control and feedback. I am not a
mechanical engineer, and I do not know where to begin with a problem like
that. I don't imagine this is hard to build using existing physics engines,
but it wouldn't work out the box. It requires some deep domain knowledge of
things like friction, tensile strength, and so on. A system like this would
spur progress in robotics immensely.

~~~
ambicapter
Why do you think you need a physics engine (outside of simulation/testing)?
Don't humans get by pretty well with only an intuitive one?

~~~
gabrielgoh
it is for simulation, as you say - but this is a critical for employing
reinforcement learning. The internal (inverse) model will of course, be based
on a simplified system, like a DNN

~~~
saycheese
Maybe or maybe you could just model what the workers already do, predict what
they should do, and dynamically provide feedback, simulation, etc.

~~~
gabrielgoh
im not quite sure what you're suggesting. there needs to be a source of ground
truth to inform the robot if what is being done is right. And actually having
a physical robot arm for this would be way too slow

~~~
saycheese
Right, the ground truth is the existing human labor - and yes, run sims at
scale makes sense, but if you don't build and model using the real world
you'll rapidly get a solution that only shows the sims errors in modeling the
world. All the best robots I've seen run sims, but very narrowly and with a
well defined problem to refine via a well designed model.

Offer stands to help you, but given the deadline for the next batch is days
away, you would need to let me know as soon as possible via a comment, then
I'd contact you via email.

~~~
gabrielgoh
shoot me an email with your background etc. I'm not aiming for this batch
actively but i wouldn't mind a chat. Google my name to get my website an
email. it should be the first result

------
personjerry
How exactly does this "democratize" AI? Doesn't this only potentially prop up
another AI company with the hope that YC will be backing it (and thus profit
from its success)?

~~~
cbanek
It just seems like "democratize" is one of those new startup buzzwords. But
yes, it seems like really what they want to do is bring it to market, and by
democratize, they mean have everyone buy it.

~~~
kabes
Yep, No one was taking "disrupt" serious anymore, so they needed a new word to
strip from its meaning.

~~~
ericjang
Did you mean 'disrupt'? Hadn't heard of "disturb" before used in startup
lingo.

~~~
woah
I like it.

"How This Startup Is Disturbing The Equipment Financing Market"

"A startup is disturbing the consulting industry"

"16 Startups Poised to Disturb the Education Market"

------
itchyjunk
Slightly off topic but had 2 questions.

The last part reminded me of google training a bunch of robot arms [1].
Haven't seen much being done with it, does anyone know if anything is being
done with the data?

We don't really know how much of each resources it takes to grow something.
How much oxygen does 1 tomato plant take? I think growing in space would
require one to investigate such questions in more detail. Ever since I came
across ML and DL, I wondered if there was a way to train a deepFarmer.
Something that understands relations between minerals nutrients and the
fruiting body. Sometimes you want to grow stuff that might have less of
certain stuff but you want more off it. Eg: low calorie high volume foods. Or
you might want high protein food. If an "AI" could figure out how to maximize
vitamin C for example in tomato for a population that needs more of that vs it
learns to make the tomato more water rich for some other reason. AI is
interesting.

[1] [https://research.googleblog.com/2016/03/deep-learning-for-
ro...](https://research.googleblog.com/2016/03/deep-learning-for-robots-
learning-from.html) Edit: Forgot link

~~~
fnbr
I've spoken to a few people who are interested in applying machine learning to
hydroponic farming with the aim of creating vertical farms.

If you could isolate the different rooms sufficiently, you could run machine
learning to optimise yield (or Vitamin C).

I have doubts as to the commercial viability of this, as farming is pretty low
margin, so the overhead requirements for the capital expenditures would
require pretty substantial gains in efficiency, which I think just don't
exist.

~~~
contingencies
I have at least one serious potential investor ready for anyone attempting
this (vertical farming automation).

Also, I am interested to cooperate on creating reliable contracted urban
demand without the need for retail packaging - [http://infinite-
food.com/](http://infinite-food.com/) \- currently relocating to Shenzhen.

If automated urban vertical farming happens it will probably happen in China
because dense/cheap/economies of scale/rising food prices/rapid
urbanization/transition toward smaller households/cultural preference for
fresh and less processed foods/less regulatory issues.

~~~
simonrobb
Why vertical farming specifically? No doubt vertical farming will form part of
the solution to feeding urban populations in the coming decades, but the area
covered by open-air "horizontal" farming is _immense_. We just can't do
construction on that scale, not to mention the incredible environmental
impacts. Growing things with LEDs seems pretty wasteful when we have a great
big star shining down on us all day. Vertical farming will bring fresh food to
high-density populations for sure, it just isn't going to change the face of
farming across the planet.

Although it's a much more difficult problem to solve being an uncontrolled
environment, my company is working on this automation but for traditional
farms ([http://touch.farm](http://touch.farm)). The first step is gathering
rich data from different crops/climates, which is why we're starting by
designing the cheapest and most usable ag sensors we can. If we can make
sensor tech accessible to a wide range of farmers, we'll gain a rich enough
dataset to start applying ML (and farmers and the environment win in the
process).

tl;dr: vertical farming is great, but what we really need is
innovation/investment in traditional farming.

~~~
contingencies
_Why vertical farming specifically?_

Ethnic Chinese investor, China focused. China has removed a lot of arable land
recently for urban development, people are urbanizing at the fastest pace in
human history, and food prices are rising quite rapidly.

Your comments are logical for the US and your project sounds interesting. From
what I understand EU agriculture is a sort of middle-ground, with smaller-
scale automation.

~~~
itchyjunk
Also depends on crop types. Makes sense to do large fields for corn, for
example. But being able to grow herbs etc locally where it's consumed, inside
cities makes way more sense. This in turn frees up resources tied to growing
and transporting such stuff to cities.

There are pros and cons to both but I think you can get richer data for
vertically initially to train systems than move on to larger scale horizontal
farms. Tough this doesn't mean there are low hanging fruits their either.

~~~
simonrobb
That's a good point - the choice of crop will have a large bearing. I don't
know if low margin crops like grains could provide an adequate ROI given
electricity costs etc, let alone the outlay required to build structures over
huge areas.

In my understanding vertical farming is usually a hydrocultural practice
(doesn't use soil). That works well for a lot of horticulture, but not so much
for broadacre crops.

------
pron
> Some think the excitement around Artificial Intelligence is overhyped. They
> might be right. But if they’re wrong, we’re on the precipice of something
> really big. We can’t afford to ignore what might be the biggest
> technological leap since the Internet.

1\. We need to work on big things whether or not they're overhyped and whether
or not we're on some precipice.

2\. Those who think what marketers call AI is overhyped (myself among them)
don't think that it isn't something really big. Even though we haven made very
little progress since the algorithms that power most modern machine learning
were invented fifty years ago, there is no doubt that machine learning has
become quite effective in practice in recent years due to advances in
hardware, and heuristics accumulated over the past decades. It is certainly
big; we just don't think it has anything to do with intelligence.

3\. Are there any machine learning experts who think we are on the precipice
of artificial intelligence? If so, do they think we can overcome our lack of
theory or do they think that a workable theory is imminent?

------
karmicthreat
I think this is one of the few RFS that I would drop everything for.

The factory environment has to be one of the most frustrating as a software
developer. So much low hanging fruit that you really have to develop too much
if you are not following the typical industrial idioms. (Throw ladder logic at
it, keep at it till it barely works, then run it till the wheels fall off.)

Even just something as simple as reporting on a 30K$ PLC driven machine is
painful. You can't buy a 10K HMI with Wonderware (a still painful piece of
software) so you just ignore it. In my particular case I developed a simple
reporting system on a RPI.

These industrial systems are usually not capable of even SQL or MQTT. You have
to strap on an extra piece of hardware and a ton more money for licensing.

Even deployment is painful. You can't just push new code because you have no
way to mock your industrial systems. Even if you could you will need to live
edit your code into the PLC or you will wipe its current state of recipes and
other user data. Because your PLC wasn't able to use standard SWE tools to get
that data. God help you if you need to roll back.

So I am applying to this. Everything is broken. Where do you even start? Fix
the platform, fix the robots, fix the job setup, fix the people.

~~~
aryamaan
What?

~~~
karmicthreat
Exactly. These systems are pretty foreign to most people. It has completely
different vernacular, idioms and tradition.

It is very different than say backend development.

------
lowglow
I asked this last time but got no response.

1\. Is there a firewall between the information companies applying give you
and the rest of the OpenAI effort?

2\. What's to prevent a partner from seeing a good thing and passing the info
along to a potential competitor already funded inside the program?

Overall it seems that this may be used to give OpenAI a strategic competitive
advantage by using ingress application data for market
analysis/research/positioning/signaling/etc.

------
jbarham
I really hope the bit about "free machine-powered psychologists" is satire,
but given YC's unironic techno utopianism fear that it is not.

Reading "Computer Power and Human Reason" by Joseph Weizenbaum (published over
40 years ago!) should remind people that attempting to build a "machine-
powered psychologist", even if it's something that can be done, is not
something that should be done.

~~~
jacquesm
Even if you say it isn't people will still interpret it as they wish:

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

Was against the creators insistence taken as the real deal.

------
emcq
Perhaps due to the article starting with discussing how AI might be overhyped,
but I'm very much not blown away by this post.

Reinforcement learning for self improving robots is one of their called out
areas? I've never found companies focused on tech or research problems first
to be all that successful. In terms of a research projects it's not very
interesting or socially beneficial compared to self driving cars or robotics
applications in medicine.

It all leaves me wondering what YC's strategy is here. Maybe it's easier to
establish a fund in AI, get smart people to apply, or that their expected
future returns are higher?

------
urs2102
This seems neat.

Are there any other future verticals which you would consider domain specific
perks for?

Also, what exactly constitutes an AI startup? If you utilize a ML library to
handle a small feature of your product, are you an AI startup?

------
makmanalp
> Some think the excitement around Artificial Intelligence is overhyped. They
> might be right. But if they’re wrong, we’re on the precipice of something
> really big.

I mean, even if it is overhyped, I think there's a lot to be excited about.
Weak AI is still an amazing breakthrough for automation. The trick is to not
try to do too much at a time. We do ourselves a disservice by not considering
how amazingly efficient humans _augmented by ML_ can be. The research for AI
doing everything just isn't there yet, and that's OK.

------
throwawaysbdi
Ahhh this is the moment I've been waiting for. Hype has officially hit
stratospheric proportions.

Time to add the words "deep" or "learn" to your startup name and reap in the
dough!

~~~
nojvek
It's only hype if it doesn't work. Beating humans at games which were
previously thought only humans could play.

Speech recognition, image recognition, translation have all made leaps in last
5 years.

Sure it's silicon Valley and a lot of companies will scam themselves in but I
absolutely believe there will be another Google coming out soon or has already
been born who will capitalize on AI.

~~~
omarchowdhury
Another Google as in a startup specifically using AI to improve search?

Is Google really going to miss improving search with AI with all their
billions and brains?

~~~
throwaway729
Parent probably meant another company that goes from $0 to megacorp before
your newborn child graduates college. Not a search company.

------
johnrob
At some point, making food/housing/healthcare cheaper seems like a more
achievable goal than finding work for people (who are in theory competing with
AI).

------
patkai
I'm not surprised that the general public is worried about AI but I would
expect many others to worry about data. Exaggerating a bit: mathematics and AI
skills is something any talented person can get individually, but gathering
useful personal data on a large scale requires a huge infrastructure. So if we
want to "democratize" then I'm wondering why not democratize access to data.

------
EGreg
_" We think the increased efficiency from AI will net out positive for the
world, but we’re mindful of fears of job loss. As such we’re also looking to
fund companies focused on job re-training, which will be a big part of the
shift."_

I find a lot of wishful thinking, denial and cognitive dissonance in this
sentiment, which is found everywhere.

"Computers will eliminate these jobs, but humans will always have more to do."

Um...

If computers can learn at an accelerated pace, what makes you think that by
the time you learn that next thing, it won't already be eliminated (or shortly
afterwards) by a fleet of computers that use global knowledge? Do you really
think that Uber driver - turned - newbie architect is going to be in demand vs
the existing architects with their new AI helpers?

It's not black and white, but the AVERAGE demand for human labor is going
down, not because EVERY human job will be eliminated but because automation
allows LESS people to do the job.

So wages drop. On average.

The only real solutions are either unconditional basic income, or single payer
free healthcare / food / recreation.

------
mackan_swe
My goal is also to democratize AI, in particular AI research. I believe that
every developer should have at their disposal the same kind of tooling and,
even more important, the same ability to intersect their data with the world's
data. Engineers at Facebook, Google, Microsoft and so on can test their models
or even enrich them by using the Facebook, Google or Bing dataset. Independent
entrepreneurs cannot do the same thing with the same ease. If we want to reach
general AI any time soon, indie entrepreneurs must be let in to play.

My strategy is to build a service, free for non-profits to use, that would
solve the problem of "if I only had the same data Google engineers had, this
product would be perfect". Here is how it would work.

1\. Go to my webpage and register a site you want me to index for you. The
site URL you enter may already have been registered by another user, but to be
sure the data is in my index, register it again. I will now continue to index
this site every 24 hours for as long as I live. You need higher frequency
indexing? Sure, no problem. You will owe me for the additional cost.

2\. Download a client of choice from the website, we have them in c#, java,
python, R ect. The client will let you query your own private data as well as
the data in the cloud (the data I'm now generating and refreshing every 24
hours). The query language will also let you join or intersect between the two
datasets. In fact, due to the nature of RPC you can use your local data and
all of the data I'm generating and refreshing, as if it was your data.

3\. In the end, I will be indexing such a large part of the internet that
there will not be much use for Google anymore, or ads. That's the vision.

I'm not American and can't see how I'm a good fit for the YC program this
summer. However I will be needing funds for cloud machines pretty soon and so
far I've found noone at OpenAI to contact. Is there anyone from OpenAI reading
this? This should be right up your alley. Care to speak?

~~~
zodiac
I have a question about your site - "Google engineers" have a lot more data
than just "Google's index of the web", they have street view data, data from
people doing captchas (including the new street sign ones), click data for how
people use their products (gmail, maps), maybe android autocorrect data,
speech recognition etc - how would you provide access to those?

~~~
mackan_swe
I wouldn't provide access to most of those data because I don't have the means
to and I wouldn't want to either. My businss strategy is to build "strong NLP"
without having to treat users as bags-of-valuable-data that I can sniff. But
to integrate with a open map service would absolutely fall within the scope of
my offering.

The research we would do in my team would be cutting-edge. But we would never
even attempt to achieve what Google is achieving when they sniff their Android
users. Why would we be cutting-edge? I don't know, but that would be our aim.
Here's an example of what we would be doing in the NLP domain:

"Give me the latest sales numbers."

parse:

Give=exec latest=DateTime.Now-x sales=sp_daily_sales

exec:

exec sp_daily_sales '2017-03-23'

------
partycoder
If you find it hard to sell AI based solutions, just call it automation rather
than AI. It is a term that people react to differently.

It's like the term "technology". Spoons, chairs, bricks are technology. The
modern usage of the word technology is what people used to call "high
technology".

------
aabajian
I'm interested in this per my earlier discussion on machine learning in
radiology (see:
[https://news.ycombinator.com/item?id=13571847](https://news.ycombinator.com/item?id=13571847)).
It's disappointing that you have to be in the Bay Area to participate. I'm
just starting residency and don't have the time to drop everything and enroll
in an incubator. I think I'm one of the few people with a master's degree in
computer science and (soon) to have a medical degree. I can handle the
technical and medical sides of a radiology informatics / machine learning
business, but I'd need someone to manage the business, marketing and sales
sides.

------
Entangled
> If the experiment works out, we’ll expand what we offer to include things
> like access to proprietary datasets and computing infrastructure.

Datasets, that's the most important point in Machine Learning and exactly what
Google has been collecting for the past decades.

I wanted to start a project about dermatological images but how would I get
that information? Then decided to start an agricultural project but then
again, how to get a million images to identify a thousand species? Birds?
Legal documents? Human faces? Fashion? Speech? Translation? Everything needs a
huge collection of datasets.

The tools are there, that's the easiest part.

------
amelius
Perhaps it's an idea for YC to start a "job agency for AIs".

On the "demand" side, client-companies can offer problems to be solved by AI.

On the "offer" side, startups can provide algorithms solving specific
problems.

YC can be a mediator, running the algorithms, and keeping the data of client-
companies safe from anybody else (including the AI startups).

Here's an example of such an agency:
[http://www.aigency.co/about/](http://www.aigency.co/about/)

------
legel
The post is clear that A.I. startups in this vertical will be given special
resources, but not clear if there will be more startups selected specificially
for this?

------
eddd
I see ML and AI raising on the market quite fast. How does this work? How many
ML engineers are out there? If, broadly speaking, we have shortage of software
engineers, what is the demand for ML engineers? It is not something you learn
overnight as a dev or mathematician, so where are there coming from?

~~~
bra-ket
coursera

------
elmar
So how to correctly "mention this post in your application." just insert the
URL ? "[https://blog.ycombinator.com/yc-ai/"](https://blog.ycombinator.com/yc-
ai/")

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samirparikh
Seeing as how sam altman has invested in an AI startup (vicarious.com), which
is pursuing robotics applications, why would he/YC want to fund competitors
for RFS ?

~~~
skynode
Democratize all the things.

Democracy is dead. Long live AI Democracy.

------
deepnotderp
Would YC be interested in funding a deep learning chip startup?

------
malux85
Is YC still interested in Solo Founders?

------
tylermenezes
I'm excited to see what new ways companies will find to call a bunch of if-
statements "AI".

~~~
stagbeetle
Curious, what would qualify as AI under your definitions?

~~~
tylermenezes
The joke I was trying to make is that a lot of startups are doing the same
things as always but calling it "AI." A chatbot using NLP technology from the
early 2000s is suddenly "AI."

There are plenty of actually innovative products in the AI space.

~~~
stagbeetle
Curious again, what are the innovative products in AI right now?

~~~
tylermenezes
Major verticals that come to mind in terms of progress are healthcare imaging
and research and self-driving cars.

------
itcrowd
At Risk of being downvoted to oblivion and out of a very well-meant interest:
what if you'd replace AI with Chinese traditional​ medicine in the post above?
Why would AI be more viable than that?

(Note: I am very skeptical towards CTM and quackery. But also towards AI and
ML in general. Any pointers would be great. Why is this the new industry to
look out for, for example?)

~~~
antons_ghost
Also at risk of being downvoted:

If I had general_ai.exe or worlds_best_nlp.py, what should I do with it? It
isn't even clear to me how they would be useful.

~~~
tommynicholas
Why do you expect people will be trying to build a general_ai.exe? Vertical
applications of machine learning and light-AI are what most private comapnies
that are getting traction are doing today, while big-cos and universities (and
things like OpenAI!) are funding the research that could lead to more
generalizable AI.

~~~
antons_ghost
People certainly talk about general_ai.exe.

Often I imagine I had a technology such as general artificial intelligence or
world-class NLP. Perhaps I lack imagination, but I have not yet thought of an
exciting application. These are tools, much like Perl scripts, and it is not
clear to me which will displace more jobs during my life.

~~~
tommynicholas
Not serious people in any near-term way. Even bullish AI folks think general
AI is MINIMUM of 10, more likely 50-100 years away.

