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swyx

(author here) There are at least 4 killer apps ($100m/yr revenue potential) so far:

1. Generative Text for writing - Jasper AI going 0 to $75m ARR in 2 years

2. Generative Art for non-artists - Midjourney has by some accounts $80m ARR

3. Copilot for knowledge workers - GitHub’s Copilot has roughly 50-80m ARR as well

4. Conversational AI UX - ChatGPT probably has >$100m ARR by now, Bing Chat has brought $m's worth of attention to Bing

(More on agents as the immature #5: https://www.latent.space/p/agents)

what else do you need to see to believe? (geniune question)

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The tech problems will eventually get sorted out I'm sure, the most uncertain problems are legal. The world's copyright law is not even up to date enough to deal with the internet without crappy patchwork workarounds (like Youtube's contentID nonsense), much less LLMs.

Steam just banned AI art and text assets and built in generators because they don't want the liability of hosting it. Midjourney is getting sued by Getty, Copilot breaks GPL licenses and was even facing class action lawsuits, OpenAI trained using copyrighted and even pirated content, LLama models are unavailable for commercial use, AGI alarmists want to ban the whole thing altogether, etc.

A lot of end usage depends on how all of this plays out in courts over the next few years. Why would people dump capital into something that will be declared illegal?

Because if they don't, their competitors will, even if those competitors are overseas in a more lax environment.

Either IP laws will catch up, or the countries with better IP laws will become more competitively successful.

If people get used to LLMs governing their lives, those copyright laws will "just" be changed. People will not accept a legal challenge taking away their toys. Granted, we're not at that point yet. But the window for the legal stuff really making a difference is slowly closing. Meanwhile, the legal system is pretty slow.

75+80+80+100 is £335m per year in revenue. For a point of comparison, that's approximately 11 hours of Google's revenue.

but rate of growth is likely 100-1000 times higher

On a smaller time scale, is rate of growth that meaningful?

I guess I'm just thinking, until we see the how this all pans out over the next decade, we don't really know if the current rate of growth will hold, or if it'll plateau/slow down.

Yes, it’s meaningful. If Google doesn’t fix search in the next decade then Bing (or some other winner) will be the service earning Google’s ARR in 11 hours.

> On a smaller time scale, is rate of growth that meaningful?

revenue in initial stage of extreme growth is much less meaningful.

I find myself using Bing Chat more and more instead of googling specific questions. And no, hallucinations are not a problem, because the questions are concrete and the answers immediately verifiable.

The innovator's dilemma on display.

Consider the possibility that may be a point in a technology's evolution where you can "look at what is being done with it" and conclude that it's useful from that, rather than just comparing revenue figures across domains.

Yeah the dollar values here are a distraction. I use copilot everyday at my Data Science job. Its useful!

What we are not considering is integrating a custom trained LLM into our work because the tech just isn’t there yet.

LLMs today are great for certain use cases, which is amazing when it suits your needs. Need to extract a hotel name, city, address and confirmation number from emails and return it as JSON? Not a problem. Need it to validate postal codes in Canada? It's the wrong tool.

> what else do you need to see to believe? (geniune question)

It's not that I don't believe in LLMs.

It's that the level of media attention AI is getting isn't backed by the same level of real world use cases, yet. (All of the use cases you listed are awesome, no denying that, but I don't think those alone justify the amount of hype in mainstream media)

i mean, theres nothing i can do about mainstream media hype, but i guess my main point is this is a growing field with real money and utility behind it, and so will professionalize. if I am correct on that then AI Engineer will be a thing (because it is Least Bad title for the thing)

AI Engineers are just software engineers who use specific tools. If we want to use a fancy title then that's fine, I guess. But let's not pretend that a typical dev can't easily learn vector DBs, data pre-processing, fine tuning, etc.

None of these things require specialized knowledge in the way that say being an AI researcher would.

You could say the same about things like SREs or Devops. In fact, many of them transitioned from regular "software engineer" to these roles simply by learning closely related skills.

That won't stop the industry from inventing new, useful titles.

You are actively contributing to the hype cycle lol.

I'd add these use cases:

5. automated processing of unstructured paperwork and ingestion into ERP systems. Basically, upload any kind of bill and get all of the information into the system, not just "find out the total amount". That can save so much in accounting it's not even funny any more.

6. related to this, something that sorts incoming emails. Classify stuff into "look into it now" vs "look into it later" vs "yet another bullshit marketing email".

My problem with this is that AI at the moment is a kind of 80% thing.

And you want to plug that into ERPs and accounting?!?

We don't even really understand its failure modes.

Yea but humans manually retyping things is also a 80% thing.

The thing is it can be used to get rid of the tedious and error-prone busywork. Instead of having highly paid accountants manually type monetary amounts into SAP, the accountants can now just look over and check if the AI was accurate in transcription.

Why AI, though? Why not OCR and regular software? What does AI bring to this table?

Except for VC money.

OCR can't grasp context, it needs incoming bills to be formatted in exactly the same way or at least in somewhat consistent area patterns.

AI doesn't have that problem, so you can use it to detect areas of interest and then follow up on that with classic OCR.

The longer HN continues to doubt in AI's deliverables, the bigger our revenues and our moats can grow. Don't tell them.

(It's not that hard to hit $1M ARR with a good AI product. So many classes of new products and solutions have opened up.)

I’m sure I could find a similar comment about cryptocurrency or NFTs. There’s always snake oil salesmen.

I remember thinking this about Tesla too. They built a fairly massive automaker while everyone kept saying their whole approach was fundamentally doomed.

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