What's your source, because it looks wildly out of proportion compared to numbers we have now.

Andoryuuta 3 hours ago | parent | next [-]

To add an actual source to this thread, a brief paper by researchers at the International Labour Organization (ILO) states that for knowledge workers globally "... there are between 644 and 997 million jobs, which represents between 19.6 per cent and 30.4 per cent of global employment respectively." [1]

[1]: Berg, Janine and Gmyrek, Pawel, Automation Hits the Knowledge Worker: ChatGPT and the Future of Work (April 21, 2023). UN Multi-Stakeholder Forum on Science, Technology and Innovation for the SDGs (STI Forum) 2023, Available at SSRN: https://ssrn.com/abstract=4458221

	▲	windexh8er 2 hours ago \| parent [-]
		Globally, sure. The assumption here is all users are on the same economic footing, they are not. Only about a 1/3rd (at most) of that count can afford $1000+ monthly, and even then that is wildly out of line with what most will.

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elliotec 3 hours ago | parent | prev | next [-]

Here's a source from 2019 that says: "By 2023, the number of knowledge workers in the world will increase to 1.14 billion, with more than four-fifths of that growth coming from the emerging world."

https://www.gartner.com/en/newsroom/press-releases/09-24-201...

	▲	windexh8er 2 hours ago \| parent [-]
		Thank you for validating my point. > "...with more than four-fifths of that growth coming from the emerging world." If anyone thinks this is a part of the global TAM that's got $1000 a month to blow, well then I've got a stable of flying unicorns to sell you.

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HDThoreaun 3 hours ago | parent | prev [-]

I googled "number of knowledge workers worldwide" and read the top results. If you read it as I was confident in a billion I apologize, Im just trying to get an accurate count. What numbers do you have now and where did you find them?

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windexh8er 3 hours ago | parent [-]

That's not the TAM of 1B knowledge workers globally. If that were the case many industries would have a 2-3x target market.

To simplify break that 1B up into 3 levels of purchasing:

1) High-tier (US, Western EU, ANZ, Japan, South Korea, Singapore, UAE, etc) - 200-250M knowledge workers.

2) Mid-tier (Eastern EU, Latin America, urban China, India tech sector, etc) - 300-400M

3) Low-tier (Rest of the world) - 300-400M

Low-tier users are mostly free tier or heavily subsidized pricing.

Mid-tier are going to account for USD sub-$100 tiers. Probably averaging less than $50/seat.

High-tier are who you are assuming is the 1B. Users are not equal in that knowledge worker count, so there aren't 1B knowledge workers to charge money.

And when you consider Low-tier users a majority of those are free users which need to be subsidized by the High-tier users. So either free tiers get much more restrictive or the providers lose additional training data. A bulk of Low-tier users cost money and provide little to no revenue.

Edit: And think about Mid-tier and Low-tier for 5 seconds. Why would they pay Anthropic or OAI when they get get 100x+ inference from DeepSeek or Xiaomi? Mid-tier may be the only area that is willing to spend money on a US provider, but I would wager significantly on the fact that users in the Low-tier almost universally do not care.

	▲	HDThoreaun 34 minutes ago \| parent [-]
		Thank you. So with these numbers it seems like half a billion subscriptions at $500/yr is on the table. Obviously theres going to be competition in this market and self hosting cheap models may become the dominant use case. Assuming the labs are able to get most of the market though, the market size is something like a quarter trillion a year within the next decade. It's hard for me to imagine the whole sector failing if that happens. I do think free accounts are going to end pretty soon, and some of the workers in your tier 3 will pay, but even without them this seems like a pretty healthy market size. I also wouldnt be surprised if mid tier workers are able to afford the $1000/yr vs $500. I use yearly rates because I find it easier to compare them to GDP/salary numbers