[bootsmann]

Google has historically been weak at breaking into markets that someone else has already established and I think the TPUs are suffering from the same fate. There is not enough investment in making the chips compatible with anything other googles preferred stack (which happens to not be the established industry stack). Committing to getting torch to switch from device = “cuda” to device = “tpu” (or whatever) without breaking the models would go a long way imo.

[ugh123]

I always thought Google was actually pretty good at taking over established, or rising markets, depending on the opportunity or threat they see from a competitor. Either by timely acquisition and/or ability to scale faster due to their own infrastructure capabilities.

- Google search (vs previous entrenched search engines in the early '00s)

- Adsense/doubleclick (vs early ad networks at the time)

- Gmail (vs aol, hotmail, etc)

- Android (vs iOS, palm, etc)

- Chrome (vs all other browsers)

Sure, i'm picking the obvious winners, but these are all market leaders now (Android by global share) where earlier incumbents were big, but not Google-big.

Even if Google's use of TPUs are purely self-serving, it will have a noticeable effect on their ability to scale their consumer AI usage at diminishing costs. Their ability to scale AI inference to meet "Google scale" demand, and do it cheaply (at least by industry standards), will make them formidable in the "ai race". This is why altman/microsoft and others are investing heavily in AI chips.

But I don't think their TPU will be only self-serving, rather, they'll scale it's use through GCP for enterprise customers to run AI. Microsoft is already tapping their enterprise customers for this new "product". But those kinds of customers will care more about cost than anything else.

The long-term game here is a cost game, and Google is very, very good at that and has a headstart on the chip side.

[dekhn]

TPUs were originally intended to just be for internal use (to keep google from being dependent on Intel and nvidia). Making them an external product through cloud was a mistake (in my opinion). It was a huge drain on internal resources in many ways and few customers were truly using them in the optimal way. They also competed with google's own nvidia GPU offering in cloud.

The TPU hardware is great in a lot of ways and it allowed google to move quickly in ML research and product deployments, but I don't think it was ever a money-maker for cloud.