
OpenAI API - gdb
https://beta.openai.com/
======
wildermuthn
In one of their examples, they note “They saw ratings hover around 60% with
their original, in-house tech — this improved by 7-8% with GPT-2 — and is now
in the 80-90% range with the API.”

Bloomberg reports the API is based on GPT-3 and “other language models”.

If that’s true, this is a big deal, and it epitomizes OpenAI’s namesake. The
largest NLP models require vast corporate resources to train, let alone put
into production. Offering the largest model ever trained (with near-Turing
results for some tasks) is a democratization of technology that would
otherwise have been restricted to well-funded organizations.

Although the devil will be in the details of pricing and performance, this is
a step worthy of respect. And it bodes well for the future.

~~~
azinman2
It's only Open™️ if I can run the API on my own machines.

~~~
madcowd
If big LM's are the future then even if you had the model you couldn't run it
on your own machines without having a DGX or two laying around.

~~~
sillysaurusx
Some of us do. And we can’t run OpenAI’s model, so it’s not open.

The essence of open source is that the resources are made available to you
(without warranty). That isn’t the case here.

------
andyljones
Concrete numbers from the various pullouts:

> They saw ratings hover around 60% with their original, in-house tech — this
> improved by 7-8% with GPT-2 — and is now in the 80-90% range with the API.

> The F1 score of its crisis classifier went up from .76 to .86, and the
> accuracy went up to 96%.

> With OpenAI, Algolia was able to answer complex natural language questions
> accurately 4x as often as it was using BERT.

I think the most informative are the first two, but the most _important_ is
the final comparison with BERT (a Google model). I am, uh, a little worried
about how fast things will progress if language models go from a fun lil
research problem to a killer app for your cloud platform. $10m per training
run isn't much in the face of a $100bn gigatech R&D budget.

~~~
grogenaut
$10m per training run gets me a lot of engineering time to build our own
version of this system and lease it to other customers. Just skip one training
run and I've got a pretty good team.

~~~
ganstyles
Putting aside the question of whether it would ever be a choice between
spending $10M on a training run and hiring a team for $10M, GPT transformers
were the end result of decades of language research and innovations. You’re
making it sound as though you can build the next iteration past GPT-3 for
$10M, which I don’t think is the case.

~~~
grogenaut
no but poach the right resource and it puts you quickly on par with the
competitors. What's that poaching cost?

------
minimaxir
Since the demos on this page use zero-shot learning and the used model has a
2020-05-03 timestamp, that implies this API is using some form of GPT-3:
[https://news.ycombinator.com/item?id=23345379](https://news.ycombinator.com/item?id=23345379)
(EDIT: the accompanying blog post confirms that:
[https://openai.com/blog/openai-api/](https://openai.com/blog/openai-api/) )

Recently, OpenAI set the GPT-3 GitHub repo to read-only:
[https://github.com/openai/gpt-3](https://github.com/openai/gpt-3)

Taken together, this seems to imply that GPT-3 was more intended for a SaaS
such as this, and it's less likely that it will be open-sourced like GPT-2
was.

~~~
wildermuthn
But since the resources required for training such a model are only available
to well-funded entities, it seems like offering the model as an API while
releasing the original source-code is the best practical method of getting the
model into the hands of people who would otherwise not have access?

~~~
minimaxir
That depends on _which_ GPT-3 model they're using, and from both the API and
the blog page, it's unclear.

Easy access to the 175B model would indeed be valuable, but it's entirely
possible they're using a smaller variant for this API.

------
zitterbewegung
Looks like OpenAI is going head to head with huggingface.

This makes a lot of sense and it seems they are telegraphing to monetize what
they have been doing. It also seems like this is why they don't release their
models in a timely manner.

~~~
minimaxir
The notable difference is that the base Huggingface library is open source, so
you could in theory build something similar or more custom to the OpenAI API
internally (which then falls into the typical cost/benefit analysis of doing
so).

~~~
zitterbewegung
Wow I actually used your code to do experiments to synthesize tweets. I didn't
realize you responded to my comment!

------
mcrider
Whoa -- Speech to bash commands? That's a pretty novel idea to me with my
limited awareness of NLP. I could see this same idea in a lot of technical
applications -- Provisioning cloud infrastructure, creating a database query..
Very cool!

~~~
jorgemf
It is not a novel idea and I don't think it is practical. If the natural
language was practical for bash we would already have already "list directory"
instead of "ls" and so on. "ls" is just 3 keystrokes while the natural
language option is 15, 5 times more.

~~~
kredd
I was imagining more of a "list of files that contain word "hello" in them at
least 5 times". Would be useful to easily write longer and pipe-chained
commands, especially for people that don't use bash-like scripting on a daily
basis.

------
typon
This is incredible. I can't tell how much this is cherry-picked examples vs.
revolutionary new tech.

~~~
spookyuser
Yeah I can't tell exactly which ones but I really feel like some of the OpenAI
demos of products could be potentially huge if fleshed out.

~~~
gdb
Sign up for the beta if you'd like to be the one to flesh them out :)!

~~~
OkGoDoIt
I definitely did immediately after seeing this. Being neither an academic nor
representing a recognizable name brand company, I don’t know if I should have
my hopes up too high for getting access soon, but I certainly hope so. I’d
love to play around with this and push its limits for some creative hackathon-
style side projects!

Just wanted to add: It’s amazing all the negativity in this discussion.
Whatever happened to the creative tech community who loves to push boundaries?
Isn’t that still part of the hacker ethos, isn’t this still hacker news? Just
because a tool has the potential to be used for bad doesn’t mean we shouldn’t
be excited to find new ways to use it for good.

------
say_it_as_it_is
OpenAI started off wide-eyed and idealistic but it made the mistake of taking
on investors for a non-profit mission. A non-profit requires sponsors, not
investors. Investors have a fiduciary responsibility to maximize profits, not
achieve social missions of open AI for all.

~~~
gdb
OpenAI LP, our "capped-profit" entity which has taken investment, has a
fiduciary duty to the OpenAI Charter: [https://openai.com/blog/openai-
lp/](https://openai.com/blog/openai-lp/)

~~~
say_it_as_it_is
Mind changed. Keep leading the way!

------
m_ke
I guess Sama plans on manufacturing growth metrics by forcing YC companies to
pretend that they're using this.

Generic machine learning APIs are a shitty business to get into unless you
plan on hiring a huge sales team and selling to dinosaurs or doing a ton of
custom consulting work, which doesn't scale the way VCs like it to. Anybody
who will have enough know how to use their API properly can jus grab an open
source model and tune it on their own data.

If they plan on commercializing things they should focus on building real
products.

~~~
antris
Not everyone wants to be an admin to their infrastructure. Real existing
services like Heroku and Squarespace exist as useful services because even
though you might know how to design and build a website from scratch,
sometimes you just need something done quickly without too much worrying about
details of the system that do not matter for your project at this point. I
really don't see how this wouldn't apply to AI projects as well.

I could make a much better site coding my own website from scratch and setting
up servers myself, but for some projects I wouldn't even think about it that
way, because using Heroku or Squarespace I can save a LOT of time and get the
results I need much quicker.

~~~
m_ke
That's true, but machine learning models are not twilio or sendgrid, you have
to tune them for your use case, monitor their performance and handle the
uncertainty of their outputs. Doing that well requires a data scientist and if
you have one they will be much more productive iterating on their own models
instead of depending on a 3rd party black box.

~~~
antris
Not a data scientist myself, but plenty of data scientists in a consultancy
company that I used to work in said that they have to implement variants of a
limited set of models over and over again, because they couldn't reuse code
and infrastructure. The project contracts demanded that all IP created by the
consultant is the property of the client. This even caused some of the data
scientists to lose motivation, because the job wasn't challenging to them
intellectually as it involved setting up the same stuff again and again. Very
rarely would their actual expertise be needed in the job.

I am not sure if this particular service solves the problem for them in any
way, but to my ear it sounds like there is a need for code and infrastructure
reuse in the data scientists domain that is ripe for innovation.

------
eggsnbacon1
OpenAI started as a non-profit, went for-profit. Still owned by the big
players.... Something isn't right.

Is OpenAI just a submarine so the tech giants can do unethical research
without taking blame??? Its textbook misdirection, nonprofit and "Open" in the
name, hero-esque mission statement. How do you make the mental leap from
"we're non-profit and we won't release things too dangerous" to "JK we're for-
profit and now that GPT is good enough to use its for sale!!". You don't. This
was the plan the whole time.

GPT and facial recognition used for shady shit? Blame OpenAI. Not the
consortium of tech giants that directly own it. It may just be a conspiracy
theory but something smells very rotten to me. Like OpenAI is a simple front
so big names can dodge culpability for their research.

~~~
swyx
wow you just made the connection for me. GPT2 was too dangerous to release,
and now GPT3 is so much better - is there no point at which things become too
dangerous anymore? what was the conclusion on that one?

~~~
minimaxir
The blog post directly addresses this question:
[https://openai.com/blog/openai-api/](https://openai.com/blog/openai-api/)

> What specifically will OpenAI do about misuse of the API, given what you’ve
> previously said about GPT-2?

> We will terminate API access for use-cases that cause physical or mental
> harm to people, including but not limited to harassment, intentional
> deception, radicalization, astroturfing, or spam; as we gain more experience
> operating the API in practice we expect to expand and refine these
> categories.

~~~
bhl
With Amazon having a moratorium of their rekognition API, I wonder if a
Cambridge Analytica type event could happen to OpenAI where someone abuses and
escapes the terms of service.

------
gumby
I miss the opposite: the old openAI gym and other testbeds. I still don’t know
why they shut those down.

What alternatives do people like?

------
nutanc
Why are there no live examples on the page. All I see is video presentations
and some cached API response.

Is it a confidence problem? Are the OpenAI folks not confident on a single use
case? Or did I miss the live demo somewhere?

~~~
gdb
You can use the API live in multiple products, such as AI Dungeon
([https://play.aidungeon.io/](https://play.aidungeon.io/))!

~~~
nutanc
Thanks Greg. Will check it out. Would love to see AI move from the "it's fun"
zone to "make some money" zone soon though. We are all invested in the success
of AI :)

------
sytelus
Natural language search is approximately $100B business. This might be first
AI application that changes the search landscape from 1990s and finally puts
an end to the question “where is money in AI?”.

------
krallistic
I wonder if there are any legal complications in the transition from a non-
profit to a regular company (especially from a tax perspective)

------
d_burfoot
In NLP there is a very clear and powerful new paradigm: train a HUGE language
model using vast amounts of raw text. Then to solve the problem of interest,
either fine-tune the model by training on your specific dataset (usually quite
small), or 0/1-shot the learning somehow.

The crucial question is : is this paradigm viable for OTHER types of data?

My hypothesis is YES. If you train a HUGE image model using vast quantities of
raw images, you will then be able to REUSE that model to work for specific
computer vision problems, either by fine-tuning or 0/1-shotting.

I'm especially optimistic that this paradigm will work for image streams from
autonomous vehicles. Classic supervised learning has proved to be difficult if
not impossible to get to work for AV vision, so the new paradigm could be a
game-changer.

~~~
canjobear
The pretraining approach was used in vision for years before it was successful
in NLP.

~~~
julien_c
Not really on unsupervised/self-supervised data though, right?

(nor on the same scale of corpora, as far as I can tell)

------
sytse
An API that will try to answer any natural language question is a mind blowing
idea. This is a universal thinking interface more than an application
programming one.

------
dalys
I just sent in a request to join the waiting list, for the company I work at,
Kognity. The potential for this in the EdTech field is mindblowingly amazing!

There are a few good examples of educational help on the list but it's really
only scratching the surface.

I'm really excited and hope Kognity and EdTech in general can use this for
even more value-full (both for students and teachers) tasks soon.

------
owenshen24
Seems potentially more simple to get up and running then the Azure and Google
Cloud alternatives which seemed involved when I last tried them.

------
kamikazehosaki
OpenAI seems like a completely disingenuous organization. They have some of
the best talent in Machine Learning, but the leadership seems completely
clueless.

1) (on cluelessness) If Sama/GDB were as smart as they claim to be, would they
not have realized it is impossible to run a non profit research lab which is
effectively trying "to compete" with DeepMind.

2) (on disingenuity) The original openAI charter made OpenAI an organization
that was trying to save the world from nefarious actors and uses of AI. Who
were such users? To me it seemed like, entities with vastly superior compute
resources who were using the latest AI technologies for presumably profit
oriented goals. There are few organizations in the world like that, namely
FAANG, and their international counterparts. Originally OpenAI sounded
incredibly appealing to me, and a lot of us here. But if their leadership had
more forethought, they would perhaps not have made this promise. But given the
press, and the money they accrued, it has now become impossible to go back on
this charter. So the only way to get themselves out of the whole they dug into
was by making it into a for profit research lab. And by commercializing
perhaps a more superior version of the tools Microsoft, Google and the other
large AI organizations are commercializing, is OpenAI any different from them?

How do we know OpenAI will not be the bad actor that is going to abuse AI
given their self interest?

All we have is their charter to go by. But given how they are constantly "re-
inventing" their organizational structure, what grounds do we have to trust
them?

Do we perhaps need a new Open OpenAI? One that we can actually trust? One that
is actually transparent with their research process? One that actually
releases their code, and papers and has no interest in commercializing that?
Oh, that's right, we already have that -- research labs at AI focused schools
like MIT, Stanford, BAIR and CMU.

I am quite wary of this organization, and I would encourage other HN readers
to think more careful about what they are doing here.

~~~
chillee
Why is it "impossible"? Academic labs are non-profit, and they are also
effectively trying "to compete" with DeepMind.

~~~
dna_polymerase
Have a look at this discussion and the article from earlier today [0]. Of
course, a singular lab could compete with something DeepMind does, but not
without massive amounts of money in their pockets. The state of the art has
become pretty expensive, really fast.

[0]:
[https://news.ycombinator.com/item?id=23486163](https://news.ycombinator.com/item?id=23486163)

~~~
Yajirobe
State of the art can be (and usually is) born in academic labs.

~~~
markchen90
I don't think this is true. The ResNet was born at Microsoft, DQN was born at
Deepmind, the Transformer was born at Google, and GPT2 was born at OpenAI.

I'm obviously biased since I work at an industry AI lab, but we both have
important roles to play.

~~~
stonogo
ResNet lead authors were from UC San Diego and the Transformer was a
collaboration with U Toronto. There absolutely is innovation coming from
industrial labs, but industrial ties to academia run deep -- especially at
Stanford-born Google and affiliated organizations.

------
LockAndLol
It'd be great if OpenAI also introduced CAPTCHA. I'd be much more willing and
understanding to resolve those than anything Google makes.

------
agakshat
It’s been a long time coming, but I am curious to see how OpenAI’s research
output is directed and impacted by market forces.

------
nick_araph
It seems like a step towards OpenAI becoming something like a utility provider
for AI capabilities

------
lerax
Natural Language Shell seems fun

------
alphagrep12345
Interesting to see this. Is this similar to Google and Azure's ML apis?

------
mcemilg
From AGI to money machine...

------
zmitri
What happened to working on AI for the good of humanity, including AGI, and
making sure it didn’t fall into the hands of bad actors? Wasn’t that the
original aspiration? Now this reads like next generation Intercom/Olark tools.

------
danielscrubs
It seems it has translation. How does it compare to Google Translate?

------
dmvaldman
AGI in text is < 3yrs away.

~~~
Barrin92
there's zero understanding in any of this. This is still just superficial text
parsing essentially. Show me progress on Winograd schema and I'd be impressed.
It hasn't got anything to do with AGI, this is application of ML to very
traditional NLP problems.

~~~
dmvaldman
i think you are assuming that what is happening under the hood is that a
human-inputted sentence is being parsed into a grammar. it is not.

~~~
Barrin92
I know that it isn't. That's part of the problem. There is no attempt to
generate some sort of structure that can be interpreted semantically and
reasoned about by the model. The model just operates on the input
superficially and statistically. That's why there has been virtually no
progress on trivial tasks such as answering:

 _" I took the water bottle out of the backpack so that it would be
[lighter/handy]"_

What is lighter and what is handy? No amount of stochastic language
manipulation gets you the answer, you need to understand some rudimentary
physics to answer the question, and as a precondition, you need a grammar or
ontology.

~~~
FeepingCreature
Have you tried feeding this to GPT and seeing if it continues it in a way that
reveals understanding?

It sounds like you're saying "It doesn't work because it can't work", but you
haven't actually shown that it doesn't work.

~~~
Barrin92
yes, I have. You can paste these into the website of the Allen Institute for
AI, yourself here. ([https://demo.allennlp.org/reading-
comprehension/MjE1MzE1Mg==](https://demo.allennlp.org/reading-
comprehension/MjE1MzE1Mg==))

In the example above it guesses wrongly, but again this is not surprising
because it can't possibly get the right answer (other than by chance). The
solution here cannot be found by correlating syntax, you can only answer the
question if you understand the meaning of the sentence. That's what these
schemas are constructed for.

~~~
FeepingCreature
The problem for me was how to formulate the sentence in a way so that the
natural next word would reveal the thing the network had modelled.

edit: Retracted a test where it seemed to know which to select, because
further tries revealed it was random.

edit: I did some more tries, and it does seem to be somewhat random, but the
way it continues the sentence does seem to indicate that it has some form of
operational model. It's just hard to prompt it in a way that it is "forced" to
reveal which of the two it's talking about. Also, it seems to me its coherence
range is too short in GPT-2. I would love to try this with GPT-3.

------
ericlewis
Exciting!

------
historyremade
"Powered by Azure" \-- Elon clearly distrust Amazon.

~~~
jfoster
Elon is no longer part of OpenAI. Microsoft invested $1b.

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

~~~
benatkin
Does this mean Microsoft isn't going to sue their customers for patent
infringement?

~~~
google234123
Why would you say this?

~~~
jfoster
I presume it's reference to OpenAI's patent pledge:

> Researchers will be strongly encouraged to publish their work, whether as
> papers, blog posts, or code, and our patents (if any) will be shared with
> the world.

I'm not sure if it's ever been publicly elaborated on.

[https://openai.com/blog/introducing-
openai/](https://openai.com/blog/introducing-openai/)

~~~
google234123
Still seems like a low effort, bad hot-take.

------
Grimm1
Awesome! Just signed onto the wait list.

------
jaimex2
"OpenAI technology, just an HTTPS call away"

'an' is only mean to proceed a vowel. Should say

"OpenAI technology, just a HTTPS call away"

~~~
wfme
It depends how you pronounce "H". If you pronounce it aitch instead of haitch
then using "an" in this context is totally correct.
[https://blog.apastyle.org/apastyle/2012/04/using-a-or-an-
wit...](https://blog.apastyle.org/apastyle/2012/04/using-a-or-an-with-
acronyms-and-
abbreviations.html#:~:text=The%20general%20rule%20for%20indefinite,an%20HIV%20patient%20is%20correct).

~~~
jaimex2
You're right! Wow, I never realised rules get changed by pronunciation before.
It's not vowels at all but whatever sounds like one in the writers mind.

------
organicfigs
On a side note, has anyone noticed a lack of diversity on the group photo on
their careers page: [https://openai.com/content/images/2020/04/openai-offsite-
jul...](https://openai.com/content/images/2020/04/openai-offsite-
july-2019.jpg)

I remember coming across it not too long ago and felt unwelcomed/disappointed.

~~~
JoeAltmaier
I dunno - looks fairly representative of the Silicon Valley population
demographic. Maybe not so much an issue with this company? I notice (as usual)
under-representation of women. But that's endemic to the industry.

~~~
organicfigs
To an extent I agree that most startups are made up of Caucasians/Chinese
males, I think one of the reasons I left tech professionally is because I
didn't feel comfortable/enjoy the lack of diversity.

------
brainless
This is what I submitted for beta list:

I want to create a software that can generate new code given business case
hints, by studying existing open source code and their documentation.

I know this is vague, but sounds like what we eventually want for ourselves
right?

~~~
anaganisk
Remember how Microsoft trained their bot from reddit comments and it went anti
human? Well I guess I have to start dropping hints for the skynet in all my
repos.

