The maximum area a stepper can expose at the time. Effectively the limit of how big you can make a single microchip.
Making a single-chip inference engine, which NovuTensor appears to be, is a very different thing. So it's better compared to TPUv1, which is also an inference engine. I can't find the die area of TPUv1 out there, but it's not a monster, as you can probably infer from its 75W TDP.
It would be helpful in this discussion to be precise whether you're comparing to TPUv1, Cloud TPU (the v2), or something else, and if you're talking about inference or training.
(I assume my disclaimer is already obvious - I work part time at Google Brain - and that everything I'm writing is my own opinion, etc., etc., etc.)
193i immersion steppers have a reticle limit of 858mm^2, the TPU is nowhere near that.
To the previous parent, the TPU didn't take five years - I don't know where you got that. But, in any event, I'd argue the key innovation in TPUv1 wasn't actually the design of a specific optimized processor: It was seeing the need for a year or two before anyone else in industry did!
Also - I think translation problem, what's "reticule limit"? In any event, if you're comparing what someone produced today with TPUv1, that's a bit of a weird comparison considering that the v2 is live and available in beta. :)