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Comment by bob1029 | Hacker News Reader

> The solution: create your own toolchain

No thanks. I have an actual job & customer needs to tend to. I am about 80% of the way through integrating with the OAI assistant API.

The real secret is to already have a viable business that AI can subsequently improve. Making AI the business is a joke of a model to me. You'd have an easier time pitching javascript frameworks in our shop.

Our current application of AI is a 1:1 mapping between an OAI assistant thread and the comment chain for a given GitHub issue. In this context of use, latency is absolutely not a problem. We can spend 10 minutes looking for an answer and it would still feel entirely natural from the perspective of our employees and customers.

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Did you read the article or are you responding to what you imagine it says?

> a whole toolchain of specialized models, … all of these specialized models are combined with tons of just normal code and logic that creates the end result

They are not referring to a toolchain as “write a compiler”.

They are referring to it as “fine tune models with specific purposes and glue them together with normal code”.

It’s a no-brainer that any startup that doesnt do this is a thin wrapper around the openAI api, has zero moat, and is therefore:

A) deeply vulnerable to having any meaningful product copied by others (including openAI)

B) lazy AF now that fine tuning is so simple to do.

C) will be technically out competed by their competitors because fine tuned models are better.

D) therefore, probably doomed.

> The most important thing is to not use AI at first.

> Explore the problem space using normal programming practices to determine what areas need a specialized model in the first place.

> Remember, making “supermodels” is generally not the right approach.

This is good advice.

> The real secret is to already have a viable business that AI can subsequently improve

You realise that what you said, is the equivalent of what they said, which is: use AI to solve problems, rather than slapping it on meaninglessly.

I don't really have much beef with your comment as it has pretty substantive points, but I just wanted to remind and let everybody know about a Hacker News guideline outlined on their guidelines under the comments section. Sorry, I just recently re-read the guidelines, so I thought I might point others to it too. I honestly believe there are a lot more people breaking all these guidelines on this site, so the whole thing is a good read for anyone uninformed, and yes there are definitely more egregious breakages of guidelines elsewhere.

> Please don't comment on whether someone read an article. "Did you even read the article? It mentions that" can be shortened to "The article mentions that". [1]

I just mainly brought this one up, because I see it come up often, and because I didn't even notice it was really a violation until I reread the guidelines the other day.

[1]: https://news.ycombinator.com/newsguidelines.html#comments

> Please don't post insinuations about astroturfing, shilling, brigading, foreign agents, and the like. It degrades discussion and is usually mistaken. If you're worried about abuse, email hn@ycombinator.com and we'll look at the data.

Please don't break the guidelines while?

I’m genuinely curious on whether this is an insinuation on me breaking that rule you posted in my previous comment or towards the general public.

If anyone can clarify what is meant by the above comment then I will gladly fix whatever I’m doing wrong. I’m just unsure (a) whether I’ve done something wrong and (b) what part of that statement I did wrong.

Profiling individuals or taking on a moderator's role in discussions also goes against HN guidelines. It's more effective to DM moderators and keep the thread focused on constructive discussions.

Makes sense. Thanks for letting me know. I’ll ask a moderator if they’ll answer and if you’re correct then I will not do it again. I was simply trying to be helpful.

You didn't do anything wrong.

johnsonjo's post was fine. It's perfectly ok for users to remind each other of the HN guidelines, as long as they do so respectfully.

The parent comment didn't make any insinuations about astroturfing etc., so it didn't break the guideline you quoted. The phrase "if you're worried about abuse" is scoped to that form of abuse—we don't want users accusing each other of being shills and whatnot, but if people are worried that actual astroturfing or shillage is going on, they're welcome to email and we'll be happy to take a look.

I hope that is clear!

> They are referring to it as “fine tune models with specific purposes and glue them together with normal code”.

> will be technically out competed by their competitors because fine tuned models are better.

I disagree that fine tuning is the way to go. We spent a large amount of effort on that path and found it to be untenable for our business cases - not from an academic standpoint, but from a practical data management/discipline standpoint. For better or worse, we don't have super clean, structured data about our business. We also aren't big enough to run a full-time data science team.

Picking targeted feature verticals and applying few-shot learning w/ narrowly-scoped, dynamic prompts seems to give us a lot more value per $$$ and unit time. For us, things like the function calling API are fine-tuning, because we can now insist that we get a certain shape of response.

I have a hard time squaring an implied, simultaneous agreement with "supermodels are generally not the right approach" and "fine tuned models are better". These ideas seem (to me) to be generally at odds with one another. Few-shot learning is still the real magic trick in my book.

I think this is exactly the kind of issue that the startup Klu [0] is trying to solve. Not everybody should be building their own custom toolchains for finetuning/prompting AI models and there is really quite a lot of work involved in data management/evaluation.

There's definitely a lot of value in adding some AI features into your applications, but if it's not your core business you shouldn't be spending a lot of your time building a toolchain to do so.

[0] https://klu.ai

> and there is really quite a lot of work involved in data management/evaluation

This is boring tech already, we have been doing it for the past 2 decades in the web with CRUD. It doesn't make sense to be an openAI + VC-backed tools wrapper

I don't agree. You should be collecting data, running experiments and A/B tests and finetuning your own models, but you shouldn't be building CRUD apps to automate this yourself, even if you have two decades of experience doing so. You shouldn't be building out this stuff yourself, unless you are a massive business that can afford to, or it's the core of your business.

> You shouldn't be building out this stuff yourself, unless you are a massive business that can afford to, or it's the core of your business.

I think there is space for both reasoning. What led me to start creating my own framework on top of Lit because what's is available with the tech I know the most (React) has become utterly garbage recently. I don't like the direction it is going and I would recommend most companies to reevaluate their usage of React and then all the CRUD and things around it. Reinventing the wheel is what prevents monopoly in software development.

Just be prepared for OpenAI to pull the rug out from under you at some point... and probably sooner than you realize.

This is always the approach in our industry. During the land rush, you offer very affordable, very favorable terms for people building on your stack.

When they've wiped out most of the competition and have massive marketshare -- they shift from land-rush mode to rent-seeking mode, and your business is either dead entirely or you now live as a sharecropper.

It's why being platform independent as possible is critical. Even if it's an app in someone's store. Can't quite run it with just their stuff.

Who cares if you don’t have any paying customers?

If you don’t own the API AND the customer, you don’t own anything: you rent.

So the secret to building a viable AI business... is to build a viable business, with AI?

the secret is to already have a viable business and constantly sprinkle in the latest tech. trends to maintain the illusion of being something fresh and new.

That's why our bakery uses AI generated blockchains :D

My local bakery adopted a new Point of Sale that does a really good job making me feel like I have to tip $2 when buying a donut!

No blockchain or AI, but new tech (for them) nonetheless :)

My coffeeshop uses Dall-E to render flattering caricatures of customers in ground chocolate and cinnamon on the foamed milk. ;)

"what problem am I trying to solve?" if you can answer that question and justify AI as an optimization (and all the gray area fallouts that comes with early adoption) then you have a chance at building a viable business with AI.

Having a solution and looking for problems to solve (or create) isnt the mentality of an entrepreneur but of a grifter, in my crass cynical opinion. But I can't deny that you ma still make money that way.

Having a solution to an unknown problem and working towards finding a problem the solution fills can be rewritten as: Having a problem and looking for a solution.

Calling that grifting is strange.

I did say it was a crass opinion.

But just because the audience doesn't know the problem doesn't mean you (the entrepreneur) don't ask the question. I'm sure that not many people were asking for faster horse buggies in the late 19th century, but you certainly ask it and try to find a solution. Note that the problem doesn't have to be pressing to be asked.

"what problem am I trying to solve?" if you can answer that question and justify AI as an optimization...

Replace "AI" with "a machine" and you've just define Industrial Revolution.

Having a solution and looking for problems to solve (or create) isnt the mentality of an entrepreneur but of a grifter

Why? If the steam engine had just been invented, would it be only justified to use it for whatever problem the original inventor had conceived it?

Ai as a tool of the business not ai as the business.

It’s pretty straightforward.

They mean, don't build an email summarizer.

Instead if you already run an email service successfully on its own, you can easily include email summaries that are better due to AI.

Sometimes I see a request to create an AI product, when normal code works fine and it's already solved... except they might not be aware.

> I am about 80% of the way through integrating with the OAI assistant API.

I've been there. Turns out, the last 20% takes x10 the time and effort compared to these first 80%.

Sounds like a normal development project then.

Not really, no. In a normal development project last 20% take just as long. But AI applications are a very special beast.

If there's anything I would not trust an AI on its polish. It's amazing for prototyping, and has some viability at scaling up an existing operation. But the rough edges (literally in some industries) are the exact reason it's such a controversial tech as of now.

That's exactly my point, yes.

Just like the old joke: "I'm already 90 percent done, now I'm going for the other 90 percent."

Before we can finish automating this process, we just have to automate this one other little task inside.

Zeno's paradox of software development - you can complete 90% of the remaining work, but you can never be fully done.

Needs to be a sign

> The real secret is to already have a viable business that AI can subsequently improve. Making AI the business is a joke of a model to me.

Precisely. No doubt that the tons of VC fuelled so-called AI startups that are wrapping around the ChatGPT API are already getting themselves disrupted due to the platform risk by OpenAI.

They never learn. Even when the possibility of OpenAI competing against their own partners is 99.99% despite denying it a year ago.

> Precisely. No doubt that the tons of VC fuelled so-called AI startups that are wrapping around the ChatGPT API are already getting themselves disrupted due to the platform risk by OpenAI.

Eh - such startups are like a year in with a small headcount I'd think? They're still figuring out what they're gonna build imo. I don't think I'd be sad sinking a year of investment into folks who've been spending a year trying to build things with this stuff even if they are forced to find a new direction due to competition from the platform itself.

I slightly disagree. I think a business can have an AI focus rather than it being mere improvement over an already viable business if, without AI, the business model can't succeed due to excessive costs of scaling to serve enough users to have sufficient revenue. There are some cases like that where adding AI makes that previously non-viable business model viable again.

Sounds risky - if you can’t make a big enough improvement, you’re SOL. In their case, they keep making money regardless and just make more and more if they get better?

Sure, and then you'll wake up one morning and OpenAI will either have eaten your lunch, or quadrupled their prices because they'd have achieved wide adoption.

> Making AI the business is a joke of a model to me.

I don't think AI businesses are jokes, so long as you're selling a platform or a way to customize AI to some specific need or hardware. AI is a gold rush, and the most reliable way to get rich in a gold rush is to sell shovels.

But if you want to make money from actually using AI yourself, then yeah, you've gotta have a business that AI makes better.

> Making AI the business is a joke of a model to me.

By AI you just mean LLMs, like most people recently, right?

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