Wall street undervalued Google even on day one (IPO). Bezos has said that some of the times the stock had been doing the worst were when the company was doing great.

So, to help you understand how they can be true: market cap is governed by something other than what a business is worth.

As an aside, here's a fun article that embarrasses wall street. [0]

[0] https://www.nbcnews.com/id/wbna15536386

Selling them and supporting that in the field requires quite some infrastructure you'd have to build. Why go through all that trouble if you already make higher margins renting them out?

Also, if they are so good, it's best to not level the playing field by sharing that with your competitors.

Also "chip makers with the best chips" == Nvidia, there aren't many others. And Alphabet does more than just produce TPUs.

Nvidia is selling a ton of chips on hype.

Google is saving a ton of money by making TPUs, which will pay off in the future when AI is better monetized, but so far no one is directly making a massive profit from foundation models. It's a long term play.

Also, I'd argue Nvidia is massively overvalued.

nvidia, who make AI chips with kinda good software support, and who have sales reflecting that, is worth 3.5T

google, who make AI chips with barely-adequate software, is worth 2.0T

AMD, who also make AI chips with barely-adequate software, is worth 0.2T

Google made a few decisions with TPUs that might have made business sense at the time, but with hindsight haven't helped adoption. They closely bound TPUs with their 'TensorFlow 1' framework (which was kinda hard to use) then they released 'TensorFlow 2' which was incompatible enough it was just as easy to switch to PyTorch, which has TPU support in theory but not in practice.

They also decided TPUs would be Google Cloud only. Might make sense, if they need water cooling or they have special power requirements. But it turns out the sort of big corporations that have multi-cloud setups and a workload where a 1.5x improvement in performance-per-dollar is worth pursuing aren't big open source contributors. And understandably, the academics and enthusiasts who are giving their time away for free aren't eager to pay Google for the privilege.

Perhaps Google's market cap already reflects the value of being a second-place AI chipmaker?

Ironically, despite Google ultimately being an advertising company, it is the absolute worst company at advertising itself.

Like other Google internal technologies, the amount of custom junk you'd need to support to use a TPU is pretty extreme, and the utility of the thing without the custom junk is questionable. You might as well ask why they aren't marketing their video compression cards.

Aside from the specifics of Nvidia vs Google, one thing to note regarding company valuations is that not all parts of the company are necessarily additive. As an example (read: a thing I’m making up), consider something like Netflix vs Blockbuster back in the early days - once Blockbuster started to also ship DVDs, you’d think it’d obviously be worth more than Netflix, because they’ve got the entire retail operation as well, but that presumes the retail operation is actually a long-term asset. If Blockbuster has a bunch of financial obligations relating to the retail business (leases, long-term agreements with shippers and suppliers, etc), it can very quickly wind up that the retail business is a substantial drag on Blockbuster’s valuation, as opposed to something that makes it more valuable.

AMD and even people like Huawei also make somewhat acceptable chips but using them is a bit of a nightmare. Is it a similar thing here? Using TPUs is more difficult, only exists inside Google cloud etc

I believe Broadcom is also very involved in the making of the TPU's and networking infrastructure and they are valued at 1.2T currently. Maybe consider the combined value of Broadcom and Google.

> can someone help me understand how the following can be true

You're conflating price with intrinsic value with market analysis. All different things.

If they think they’ve got a competitive advantage vs. GPUs which benefits one of their core products, it would make sense to retain that competitive advantage for the long term, no?

5. The efficient market hypothesis is true :-)

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!

Aren't Google's TPUs a bit like a research project with practical applications as a nice side effect?