Good questions, below I attempt to respond to each point then wrap it up. TLDR: even if TPU is good (and it is good for Google) it wouldn’t be “almost as good a business as every other part of their company” because the value add isn’t FROM Google in the form of a good chip design(TPU). Instead the value add is TO Google in form of specific compute (ergo) that is cheap and fast FROM relatively simple ASICs(TPU chip) stitched together into massively complex systems (TPU super pods).

If interesting in further details:

1) TPUs are a serious competitor to Nvidia chips for Google’s needs, per the article they are not nearly as flexible as a GPU (dependence on precompiled workloads, high usage of PEs in systolic array). Thus for broad ML market usage, they may not be competitive with Nvidia gpu/rack/clusters.

2)chip makers with the best chips are not valued at 1-3.5T, per other comments to OC only Nvidia and Broadcomm are worth this much. These are not just “chip makers”, they are (the best) “system makers” driving designs for chips and interconnect required to go from a diced piece of silicon to a data center consuming MWs. This part is much harder, this is why Google (who design TPU) still has to work with Broadcomm to integrate their solution. Indeed every hyperscalar is designing chips and software for their needs, but every hyperscalar works with companies like Broadcomm or Marvell to actually create a complete competitive system. Side note, Marvell has deals with Amazon, Microsoft and Meta to mostly design these systems they are worth “only” 66B. So, you can’t just design chips to be valuable, you have to design systems. The complete systems have to be the best, wanted by everyone (Nvidia, Broadcomm) in order to be in Ts, otherwise you’re in Bs(Marvell).

4. I see two problems with selling TPU, customers and margins. If you want to sell someone a product, it needs to match their use, currently the use only matches Google’s needs so who are the customers? Maybe you want to capture hyperscalars / big AI labs, their use case is likely similar to google. If so, margins would have to be thin, otherwise they just work directly with Broadcomm/Marvell(and they all do). If Google wants everyone using cuda /Nvidia as a customer then you massively change the purpose of TPU and even Google.

To wrap up, even if TPU is good (and it is good for Google) it wouldn’t be “almost as good a business as every other part of their company” because the value add isn’t FROM Google in the form of a good chip design(TPU). Instead the value add is TO Google in form of specific compute (ergo) that is cheap and fast FROM relatively simple ASICs(TPU chip) stitched together into massively complex systems (TPU super pods).

Sorry that got a bit long winded, hope it’s helpful!