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Discussion (24 Comments)Read Original on HackerNews
1) push the frontier in a way only massive scale can, and cash in on it (mythos level cyber security, recursive training, frontier science work). There’s big money for never before possible capabilities.
2) own the app layer with their edge in reputation and powered by their infrastructure. Be apple where everyone else is Linux. Do design, coding, research, SMBs, legal, finance, healthcare and more (they are doing all of this).
Will it be enough to justify a Google level valuation? We’ll see how fast they can push it.
In this case the people tasked with using the product won’t actually mind.
If the price difference is 50x? No way.
The problem with this is that there are incumbents in all those spaces doing their own AI agents / platforms, and they're the ones choosing the models they use internally and they sell to their own customers. The margins and the possibility to fine tunie using open weight models, as well as the guarantee they'll keep running at predictable costs (no US orders yanking access), make them a very appealing option.
And if you're a company that needs an AI powered legal software, would you buy it from OpenAI/Anthropic, or from someone who you've already bought legal software from before and has the domain knowledge?
A question for economists... It seems plainly clear to me that information and information processing is commodifying (for the first time in human history?). Without the age-old bottlenecks at the top of the value chain, capital will surely flow downwards, right?
Having said that, while one can always hope, I would assume that Oracle is one of these companies that will be bailed out or find a way to survive.
AGI? Too loosely defined. They lack a lot of competences which humans recognise when we see them but find it hard to put into words; on the other hand what they can do already do faster than any human (and have greater bredth than any single human, but this usually doesn't matter because "coder" and "economist" and "translator" gets solved in human teams by hiring three people).
I do not think current ML has the tools to solve for quality. But we know it's possible for a really mediocre intelligence to make human level intelligence, because evolution made us, so I for me the question of AGI is more a practical one: is it affordable?
(I also think not at the present time, but that's an "I think" not "I am analyzing it carefully").
Cheap access to space was once a pipe dream.
Reusable boosters were once a pipe dream.
A new player beating Boeing to the ISS was once a pipe dream.
LEO constellations were once a pipe dream.
Launching thousands of satellites was once a pipe dream.
You should know that a) they are already running "AI" chips on their current sats. and b) they are already producing kW of power on orbit and have ~10k sats on orbit. You can watch Scott Manley's video on it, where he does some rough calculations and explains the overall architecture. There is nothing stopping them to do this, from an engineering perspective. If it makes commercial sense, that's another question, but 5-10-20 years in the future things might change there as well.
I never used Fable, maybe it is that much better. DeepSeek has no problems with the workloads I give it though - if it only keeps marginally improving with each interaction I don't see myself needing to come back.