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Which kinds of GPT startups will thrive?

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Re: Which kinds of GPT startups will thrive?

#3
They need to find a niche that won't be threatening to any of the big honchos. Possibly marketing themselves as "lawyer AI", "MBA AI", "MD AI" etc. Ideally if there was some common opensource base like Linux distros but for GPT models, constantly getting updated and fine-tuned with anyone simply pulling them and using them when needed.

Re: Which kinds of GPT startups will thrive?

#5
post #3

They need to find a niche that won't be threatening to any of the big honchos. Possibly marketing themselves as "lawyer AI", "MBA AI", "MD AI" etc. Ideally if there was some common opensource base like Linux distros but for GPT models, constantly getting updated and fine-tuned with anyone simply pulling them and using them when needed.

I can't imagine what kind of liability insurance would be needed for a GPT solution aimed at such heavily regulated fields as law, medicine or finance.

You can add all the caveats you want, but I suspect ml chat is stuck in the uncanny valley of not good enough to be trusted and not bad enough to be a toy.

Re: Which kinds of GPT startups will thrive?

#7
I heard an argument that many GPT startups (more specifically the products they make) could be the new consumer products. As in, they come up with something interesting that creates a buzz, makes some or a lot of money, then people move on to the next thing.

Re: Which kinds of GPT startups will thrive?

#8
I think there are a few opportunities for startups that want to leverage GPT technology:

1) Fine tuning base models with data that big tech doesn't have access to. E.g legal, medical, support data. Offering custom fine-tuned private hosted models for companies that can't leverage the base models APIs due to data privacy and lack of domain specific training.

2) Using GPT on the backend to do data transformation that the user doesn't interact with directly, e.g parsing logs, events, moderating content etc.

I don't think the opportunity lies in creating a thin wrapper to a custom prompt in a chat interface.

Re: Which kinds of GPT startups will thrive?

#9
Let's call the other guys "Gatekeepers" (Open.AI, Google with Bard, etc).

Option 1: none. Most of the value will be captured by Gatekeepers

Option 2: Gatekeepers will partially commoditize their service, and on top of them, several startups will thrive by creating something not easily replicable by Gatekeepers (via patents, via speed of execution, via viral growth, etc). Example: biggest GPT-powered media startup will compete with Netflix. Another: biggest GPT-powered e-learning startup will compete with higher ed - Stanford, MIT, etc.

Option 3: A single GPT-powered Coding startup will become > $100B. My bet is on Replit. (disclaimer: very early investor). When you hire a programmer, much like you pay for Jira, AWS and such, you will also pay for Replit. This partially overlaps with e-learning (see above).

Option 4: there's an even bigger revolution coming in AI, and it's not in the segment owned by LLMs. Or, it's a different interpretation of LLMs. Could it be... finally a real self-driving car?

Option 5, very unlikely: regulation will stifle competition and innovation, and most things will be killed by governments. Perhaps something smart can be said about US vs China. WWIII will be fought with virtual agents powered by GPT, over Twitter. Elon Musk will be kidnapped by GPT-6. /s

What else?

Re: Which kinds of GPT startups will thrive?

#10
I'm surprised how long the "solution in search of a problem" trend has dominated tech product design, despite obvious and repeated failures of this approach to produce results.

AI/ML products fundamentally don't make sense compared to products that happen to use some AI/ML to aid in solving a problem.

It's sort of like loving to use redis (which I do) and thinking you want to found a company based on using redis in the product, or start a redis product team, dedicated to shipping products that use redis.

It's one thing if you want to host redis as your business, which is solving a problem involving redis, but if your aim is to use redis to solve a problem then you're going to be in trouble.

Imagine a PM on the "use redis" team rejecting a great idea for customers because it could be more efficiently solved using a traditional database, or forcing the use of redis when a cheaper, easier solution already works just as well if not better. This is actually the case on AI/ML teams.

GPT startups that will thrive are the ones that aren't GPT startups, but instead solving some other, real, problem that happens to only be solvable in a post-GPT word.

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