Comment by ericjang | Hacker News Reader

Comment by ericjang | Hacker News Reader

The author's main points are all centered around the assumption that GPT-3 related technologies are ready to create market-disrupting products, and that the key business challenges remaining are mostly around figuring out how to build a defensible moat.

However, that assumption is dead wrong.

We don't know how well GPT-3 "works out of the box" (hence OpenAI's api release), and it's stupendously premature to assume that it is ready for products.

We don't have a good understanding of what inputs the model handles well vs. doesn't (a key pre-requisite for building a safe product), and it has been shown to regurgitate authoritative but untrue statements.

[EDIT]: by construction, it also cannot store information provided by the user for later use, nor can it "look up" facts.

I agree with the high level statement ("starting a business around gpt-3 is a bad idea") but almost none of the generic business advice, because it's founded on an assumption of technical capability that simply isn't there yet. The article talks about GPT-3 in an abstract "super powerful AI" sense, which leads me to suspect that the author doesn't really understand the technical limitations of GPT-3 beyond the demos that have been shown.

Author here. I agree it's early and we'll have to wait until real products hit the ground to see the full extent of its capabilities and limitations.

I was a skeptic of the performance too ("surely all these demos are cherrypicked") but having played with the beta for a dozen hours and gotten better at prompts, the performance is real, and it's good enough to build the mentioned products around that people are willing to pay money for.

Will these be good, airtight products at the same level as human-designed performance? No. But we're not talking about "self-driving car needs six 9's of reliability to meet regulations or face a PR nightmare" performance.

We're talking about "is this AI therapy bot fun to chat to and better than paying $200 per hour for a therapist?" performance.

We're talking about "is is cheaper to pay a writer $200 per news article or $0.05 for a good enough article?"

Fair enough, thanks for your reply and clarification. I think "PR nightmare" scenario might be more likely than you suspect.

1. What if an AI therapy bot tells a depressed person to kill themselves? How do you get a language model to obey confidentiality rules? How do you prevent it from memorizing and regurgitating someone's mental health conversation to another patient?

2. I think the implications of replacing journalists with far cheaper automated systems (with substantially less fact-checking capability) have not been well thought out, and I worry that some VC bro is going to rush a product to market before policy makers / stakeholders have thought carefully about whether this is something that we want.

It's telling that GPT-3's best writing successes have been of the "philosophical musing" variety, not of writing accurate articles. I'm not sure whether that says more about AI or Philosophy.

I agree, any morally conscious founder should build in extra safeguards to stifle the bad edge cases and launch only after pretty thorough testing. Even an immoral founder who wants to avoid bad PR would do so.

Ideally all creators to be as thoughtful and careful as you. But we all know 1) there will be plenty of builders will build and launch regardless of how ready the app is, 2) users happily use whatever's engaging, convenient, and low-cost, while ignoring problems with privacy, security, and whether the product is net negative for a % of users (see TikTok, Twitter, Whisper).

If the technology is here, then the products will exist, and regulation isn't going to come in time to stop it.

I feel that overestimation of fundamental capability is actually the cause of many morality/safety issues, if not at least a degradation of user experience (automated voice menus).

The big difference here is that TikTok, Twitter, Whisper actually have working technology, in spite of ethical concerns. What I am saying is that the people who want to use GPT-3 for business use case X, Y, and Z probably have not thought deeply enough about the limitations/implications of large language model methodology on specific nuances of X, Y, Z tasks.

Have you considered the fact that GPT-3 can't actually look up any information? Consider the implications of that before suggesting that GPT-3 could be used for therapy.

While GPT-3 cannot lookup information, a service using GPT-3 could. For instance one could include the past dialog/facts cleverly presented in the context window.

How well this would work in practice is up for debate.

> it's stupendously premature to assume that it is ready for products

Did you follow product development in recent decades? The iPhone was not ready for prime time as well but still people bought it and where very happy.

A lot of products nowadays are kind of MVP's or betas and people are willing to accept their flaws and edges just to be an early adopter of technologies which remind them of beloved Sci-Fi movies.

> by construction, it also cannot store information provided by the user for later use, nor can it "look up" facts

Other tools can do that. You can connect them just like you do with micro services or modular systems - what is the issue about this?

The statement "starting a business ... is a bad idea" cannot be proven and there are also no examples to strengthen this position. So until one does you just cannot prove this statement so this is just speculation.

> You can connect them just like you do with micro services or modular systems - what is the issue about this?

Clearly I'm missing something here. Can you walk me through how exactly a micro service would enable GPT-3 to look up facts, and incorporate that knowledge into a conversation? What would the microservice API look like? How are the outputs consumed?

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