Interesting examples. Personally, I don't really consider Ebay, AirBnB, Reddit, or Substack to be "technology companies". They are businesses that happen to be online, imo. I'm sure that e.g. AirBnB has lots of machine learning technology now, but I reckon it's doing niche stuff like optimizing conversion rates and profits by customer tracking, recommending, etc. So basically, after-the-fact value optimization. Nothing really invented or new created, aside from their novel ideas and unique executions.
Other actual tech examples seem to fall into 1 of 2 camps: obvious but hard to do (better search engine, better rockets, electric cars, etc), or cool but non-obvious customer end uses (maybe LLMs, VR/AR, curved or flexible high def screens, etc). The latter category has more risk but probably lower hanging fruit to get started, because the market needs are less obvious.
In your example, do you think the customer focus lead to pre-mature optimization and kind of tunnel-visioned the team away from further LLM development? That's another type of trade-off that's probably impossible to predict at the time. I mean who doesn't want customers.
I'm not entirely surprised that OpenAI was able to achieve so much given their structure - they had the mandate of a trendy new research lab, top talent, with 100M+ funding and no need to cater to any early customers. Seems like a great (though typically impractical) way to build big new things. Then they had the right top-level guidance when the tech was getting ready, to pivot and raise more money (unlike XEROX PARC for example).
Other actual tech examples seem to fall into 1 of 2 camps: obvious but hard to do (better search engine, better rockets, electric cars, etc), or cool but non-obvious customer end uses (maybe LLMs, VR/AR, curved or flexible high def screens, etc). The latter category has more risk but probably lower hanging fruit to get started, because the market needs are less obvious.
In your example, do you think the customer focus lead to pre-mature optimization and kind of tunnel-visioned the team away from further LLM development? That's another type of trade-off that's probably impossible to predict at the time. I mean who doesn't want customers.
I'm not entirely surprised that OpenAI was able to achieve so much given their structure - they had the mandate of a trendy new research lab, top talent, with 100M+ funding and no need to cater to any early customers. Seems like a great (though typically impractical) way to build big new things. Then they had the right top-level guidance when the tech was getting ready, to pivot and raise more money (unlike XEROX PARC for example).