Thread

1. ryanschaefer · 1790190580 · focus · HN ↗

   I’m confused why AI companies are using agents in-house for this type of research instead of partnering externally.

   I guess the improvement loop is tighter and they have more control over how discoveries can be used for marketing?

   But, in my mind, it begins to feel like they are setting themselves up to be “everything” companies instead of focusing on their core product…

   1. Insanity · 1790190735 · focus · HN ↗

      Because their core product is not a long-term sustainable business strategy. Local hardware and models will continue to improve to the point of not needing the hosted solutions. And if you do need a hosted solution, remember that the big cloud providers already offer these solutions, so signing up for OpenAI/Anthropic _and_ AWS/GCP/Azure is not a sound business decision compared to just signing up with 1 of them that offers your cloud infra + GenAI infra. (Which is why the long-term benefits for cloud companies will probably be for the likes of AWS and not the likes of OpenAI).

      They'll continue to burn money for marginal model improvements in the next few years all the while having no moat _and_ having Open-Weight / Local models eat their lunch.

      The only way for them to stay relevant as a company is to expand beyond simply providing the models.

      1. beachy · 1790191102 · focus · HN ↗

         I'm old enough to remember the arrival of RDBMS, once IBM primed the space with DB2.

         There was a pitched battle over features like row-level locking as competitors like Sybase, Ingress and Oracle scrapped it out. New features arrived on a monthly cadence, with immense engineering effort behind them. The winners (Oracle mostly) won a great moat which led to them to where they are today.

         The fact that so many AI companies can produce amazing coding tools so quickly shows there is no moat, supporting your theory.

         1. dormento · 1790192035 · focus · HN ↗

            The AI companies moat, if any, is hoarding all the hardware so local solutions are no longer cost-effective.

            1. xdertz · 1790194385 · focus · HN ↗

               This is not really sustainable when there is a constant supply of increasingly powerful and efficient hardware.

               1. HappMacDonald · 1790208235 · focus · HN ↗

                  The hardware miniaturization gains have finally dried up, though.

                  I am pretty certain that the current state of the art silicon feature size won't shrink again for at least another decade or two.

                  It normally takes about a decade to mature a tech which can create a smaller feature size into something commercially viable for mass production scale, and no further improvements have been in the pipeline for that long now.

                  So it's like the "next piece" indicator while playing Tetris is just blank.

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