[HN Gopher] Starting a Business Around GPT-3 Is a Bad Idea (2020)
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       Starting a Business Around GPT-3 Is a Bad Idea (2020)
        
       Author : swyx
       Score  : 78 points
       Date   : 2022-10-09 12:03 UTC (10 hours ago)
        
 (HTM) web link (www.allencheng.com)
 (TXT) w3m dump (www.allencheng.com)
        
       | yeck wrote:
       | Enjoying the article, but feel the "Economies of scale" section
       | makes an incorrect comparison between a Spotify business model to
       | a theoretical business using OpenAI's API. The author suggests
       | that since Spotify pays royalties per song played, getting more
       | users doesn't mean more money for them and then claims a business
       | using GPT-3 would have a similar limitation.
       | 
       | There are a couple things I think is wrong with this. First,
       | depending on the sort of users acquired by Spotify it does
       | directly translate to more earnings. What doesn't scale well for
       | Spotify seems to be how active the subscription-paying users are.
       | To which I mean that a user who listens to 50 songs a day will
       | cost more than a user only listening to 10 since the subscription
       | price is static and common across users despite usage.
       | 
       | That last point is where the author gets the next thing wrong:
       | assuming that services employing GPT-3 will be fixed
       | subscriptions instead of a pay-as-you-go model (like AWS). I am
       | sure there will be business using fixed sub prices that are
       | independent of usage, but we shouldn't assume that there is
       | anything about GPT-3 that makes that more likely or even very
       | different from other cases where fixed subs are used. There will
       | always be some costs per user, be it the raw cost of electricity
       | or cloud infrastructure. GPT-3's API would just be one more cost
       | per request to consider.
        
       | bloaf wrote:
       | The drive to be differentiated is a way more powerful force than
       | people appreciate. When big oil was deciding what to use as an
       | anti-knocking agent (tetraethyllead or ethanol) the two biggest
       | concerns that tipped the decision in favor of lead were:
       | 
       | 1. Ethanol might become a competitor to oil. 2. Lead could be
       | patented, licensed, and used to differentiate their gasoline from
       | competitors.
        
       | mark_l_watson wrote:
       | While I enjoyed reading this article, I more or less disagree
       | with it.
       | 
       | To me, using large language models like GPT-3 is now fungible
       | architecture component, multi sourced from OpenAI, Hugging Face,
       | etc. For many NLP tasks, not using modern deep learning models in
       | your infrastructure dooms you to writing inferior systems.
        
       | RobotToaster wrote:
       | Starting a business that relies on any SAAS, especially one not
       | easily fungible, seems like a terrible idea.
        
         | akudha wrote:
         | There was a site that was making 50k USD per month, providing
         | very basic analytics. This was in the early days of Twitter.
         | Even if it lasted only 6 months at 50k, that is 300k , for a
         | side project.
         | 
         | It all depends on timing, risk vs reward etc
        
       | tiborsaas wrote:
       | Given that it's a 2 yearish old article (although there's no date
       | in the post), I'm wondering if these predictions are proven
       | correct:
       | 
       | > The barrier to entry to developing a viable product gets low
       | for everyone, meaning hundreds of competitors will pop up
       | overnight.
       | 
       | > A lot of founders are going to try to start businesses based on
       | GPT-3, and a lot of money will go into them, and it's going to be
       | a blood bath.
       | 
       | I'm not really following the AI startup landscape, but I haven't
       | seen a Cambrian explosion of GPT-3 apps, although I noticed a few
       | ones. Blood bath is also way too dramatic. Anyone seen a post
       | where a founder of a heavily GPT-3 based startup cried out how
       | their startup was destroyed because "x"?
        
         | andreyk wrote:
         | It has happened in some cases, eg with all the "generate
         | marketing copy with AI" businesses.
         | 
         | But yeah, in general the article assumes that GPT-3 will have
         | lots of applications that make it super easy to make a useful
         | product with very little extra effort, and that is just not
         | true. Twitter demos are easy, robust and useful products are
         | not.
        
       | gjmacd wrote:
       | Unpopular opinion. But starting a business around AI is a bad
       | idea -- it's a tool not a business. AI is the "Object Oriented"
       | of our times. It'll end up being something that will be used in
       | our tooling, but I recall all those 90's companies who died
       | miserably basing their whole business model around objects... I
       | feel like AI has the same future.
        
         | Kiro wrote:
         | > but I recall all those 90's companies who died miserably
         | basing their whole business model around objects
         | 
         | Do you have any examples?
        
           | BjoernKW wrote:
           | NeXT, for one. They didn't exactly die miserably, given their
           | technology is what ultimately still runs Apple's OS software
           | and APIs.
           | 
           | NeXT's business model was based on objects to some extent at
           | least and they were enthusiastically selling object-oriented
           | software as a business feature, rather than a technical
           | matter only software developers care about.
           | 
           | Here's Steve Jobs demoing NeXTSTEP's object-oriented
           | development environment:
           | https://www.youtube.com/watch?v=rf5o5liZxnA
           | 
           | The way he explains it, it makes perfect sense (as one would
           | expect): In an ideal world, an object-oriented software
           | development approach not only allows non-technical people to
           | define requirements but also enables them to compose and
           | build applications from existing components without having to
           | write a single line of code.
        
           | inopinatus wrote:
           | Or rather, any object lessons.
        
         | echelon wrote:
         | > starting a business around AI is a bad idea
         | 
         | It's not based around AI. It's based around content creation.
         | The AI part is just the means to the end.
         | 
         | These methods allow for easy content creation. It's akin to an
         | industrialization of the mind. We're now currently searching
         | for the best human interface to control the outputs so we can
         | attain the results we want immediately and with high fidelity.
         | 
         | Once the images and sounds in your brain can immediately jump
         | to the screen, you'll see what this has all been about.
         | 
         | I don't see how this is at all comparable to object oriented
         | programming. These techniques solve real business and social
         | needs. They automate entire decades of learning, hours of toil,
         | and free up enormous capital.
        
         | andreyk wrote:
         | The Implicit assumption here is that AI in general is one of
         | several possible tools to a given problem. This is true in some
         | cases, but not in others (eg media synthesis, automated
         | transcription/translation/classification, etc.). So I think
         | "starting a business around AI" should imply that AI is a core
         | necessity, not just a chosen tool. Granted, it may be just one
         | tool among many that could be useful, even if it necessary.
        
           | ducktective wrote:
           | >This is true in some cases, but not in others
           | 
           | yet...
           | 
           | Who would have thought of something like stable-fusion just 5
           | years ago? It generates images out of thin air.
        
             | alextheparrot wrote:
             | There is a great deal of GAN literature on the order of 5
             | years old...
        
               | mlyle wrote:
               | Even those of us following that literature were surprised
               | by the sudden improvement in image synthesis.
        
               | visarga wrote:
               | Probably even more surprised. GANs never solved the
               | diversity problem.
        
       | bcardarella wrote:
       | Yeah just wait for GTP-4. Of course by then you might as well
       | wait for GPT-5.
        
       | shisisms wrote:
       | That was a good skim. Already seeing wafer thin, and excellent,
       | consumer apps built on stable diffusion.
       | 
       | I've been increasingly concerned that given now the wide spread
       | skills to build consumer apps for example, the value will be
       | eaten up too quickly.
       | 
       | Thai article makes the point that in fact this isn't where
       | (economic) value really sits. Building a moat requires more than
       | just the ability to build.
       | 
       | Thus, it feels as though building simple consumer interfaces to
       | the latest AI models is a short-term and largely thankless play.
        
         | tjr225 wrote:
         | Was this comment generated by GPT-3?
        
           | m00dy wrote:
           | looks GPT-2 to me.
        
             | kirubakaran wrote:
             | The ultimate 2022 insult
        
         | langitbiru wrote:
         | The difference between stable diffusion and GPT-3 is the former
         | is open source, meaning you don't have to pay tributes to one
         | party.
         | 
         | The barrier entry to developing apps on top of Diffusion is
         | higher because you have to setup GPU instances. It's quite
         | expensive, compared to OpenAI's GPT-3 where you can just use
         | their API.
        
           | josephcsible wrote:
           | > The difference between stable diffusion and GPT-3 is the
           | former is open source, meaning you don't have to pay tributes
           | to one party.
           | 
           | That's not what open source means, and Stable Diffusion is
           | not open source, since its license discriminates against
           | fields of endeavor.
        
       | lokimedes wrote:
       | The idea that the use of GPT-3 in a product is not providing a
       | differentiator is true if we are rebottling the output with no
       | value added. Stock photos from Unsplash and software libraries
       | from Github also provides zero competitive advantage - but the
       | possibility of synthesizing a competitive new offering on the
       | back of these is still perfectly possible. Enablers and
       | Differentiators, not the same thing.
       | 
       | The obvious out of the way, I have learned never to underestimate
       | market timing. Having laughed at the IRC for Peeps they called
       | Slack, perhaps the asymmetry of knowing how to use GPT-3 is still
       | a great untapped opportunity.
        
         | swyx wrote:
         | this exactly is what i have been exploring/writing about.
         | productizing a tech is a whole other discipline than making the
         | tech itself and its not just "heh be good at marketing and
         | distribution lol"
        
           | chii wrote:
           | although good marketing and distribution is also required -
           | but only after productizing!
        
       | andybak wrote:
       | > Meanwhile, the profits will accrue to the true beneficiaries:
       | 1) the algorithm owners, OpenAI [...]
       | 
       | This seems incorrect to me. The crucial parts have been
       | reimplemented. The weights are their only secret sauce and
       | equally good free replacements are only a matter of time.
        
         | visarga wrote:
         | I agree, they get replicated fast. But large language models
         | also have a democratising effect even when they are under paid
         | API - they are lowering the barrier to many NLP tasks. They
         | take skills from the internet and repackage them in useful and
         | customised forms. This means the benefit is really being spread
         | around to everyone building on them, they can build in a day
         | what used to take a month or a year. I see them as "open
         | sourcing" all these previously hard to access AI skills.
         | 
         | I see LLMs as part of a wider trend - we used to transmit
         | information orally, then we invented writing, then printing,
         | then media and internet. Now we can transmit the distillation
         | of our whole culture as a model, it can be applied directly to
         | solve problems. It's the next step in the propagation of
         | culture.
        
       | dzink wrote:
       | When the tech is open sourced, the product managers get to shine.
       | Requiring less engineering skill to pull off something means a
       | wider range of product people (founders, marketers, corporate
       | product managers) get to show their skills in finding product
       | market fit in more niches. Starting a business around Excel was
       | not a bad idea at all. OpenAI is becoming the Fairchild of our
       | time - keeping things closed has triggered an exodus of brains
       | and open source activity that creates the cambrian explosion. If
       | they keep up with their strategy, they would become the marketers
       | of tech that is commercialized by open source instead.
        
       | gennarro wrote:
       | Recent google updates disprove this. There have been a hugh
       | number of highly successful, albeit short-term, websites built
       | off of gpt-3 tech.
        
         | davidklemke wrote:
         | Could you share a few examples? Keen to understand why they
         | used GPT-3 to generate the content.
        
           | chrisfrantz wrote:
           | We did this! Built and sold.
           | https://techcrunch.com/2021/05/19/unbounce-snags-snazzy-
           | ai-t...
        
       | chrisfrantz wrote:
       | Read this article a few years ago and was glad it was published!
       | It definitely reduced competition judging by the popularity on HN
       | when it first debuted.
       | 
       | We were building our company on the back of GPT-3 and soon sold
       | it for a life-changing amount of money.
       | 
       | So starting a business around GPT-3 ended up being a very good
       | idea :)
        
       | amelius wrote:
       | Seeing Grammarly doing quite well (judging from all the adverts
       | on yt), I can imagine a GPT-3 based editor that improves the
       | user's prosaic output, and I suppose it could be quite popular.
       | Perhaps writing technical documentation can even become fun.
        
         | swyx wrote:
         | grammarly raised at a $13b valuation last - hearing that it is
         | in the mid 9 figures revenue. so yeah, quite well.
        
         | nradov wrote:
         | Writing technical documentation already is fun.
        
         | simonw wrote:
         | GitHub Copilot (in markdown mode) provides that already. I'm
         | increasingly using it to help write technical documentation and
         | blog posts - it works great.
         | 
         | You can even paste in a chunk of code to give it some hints,
         | start writing about it (with Copilot assistance) and then
         | delete the code later.
        
       | [deleted]
        
       | swyx wrote:
       | submitted this because i have been doing a bunch of research
       | around productized AI businesses (https://lspace.swyx.io/) in
       | preparation for someday pivoting
       | 
       | and my latest post is here
       | https://news.ycombinator.com/item?id=33144039
       | 
       | notable that in the small, this post was "wrong" - Jasper AI went
       | from 0 to $60m/ARR in the 2 years since this post. sure, you
       | could regard them as "winning the lottery", but i'm sure if you
       | asked their bank accounts they wouldn't agree starting a biz
       | around GPT3 is a bad idea :)
        
         | samuelstros wrote:
         | Jasper AI seems to prove the point though.
         | 
         | If your technological advantage is not high (enough), you have
         | to compete on marketing and distribution.
         | 
         | Jasper AI is heavy on marketing and distribution.
        
           | swyx wrote:
           | well, on a very superficial level, but
           | [this](https://www.youtube.com/c/jarvisai) is real work man
           | and it also involves solid "product thinking" for
           | nontechnical users to hold it right.
           | 
           | http://interiorai.com/ is on the surface just
           | stablediffusion, and sure pieter is an incredible
           | marketer/has huge distribution, but he is doing real product
           | level work to make it more usable for his chosen usecase, and
           | that should not be ignored
        
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       (page generated 2022-10-09 23:00 UTC)