Coming out saying they can give you a service no one else can right down to a custom chip may sway a few buyers in the market.
They've probably carefully modeled the energy savings over GPU/FPGA and found it to be substantial enough, even taking into account costs of design changes.
Interesting, as the nature/science paper made no mention of this, it was exclusively trained on GPUs.
It's a bit underhanded, however. IMHO, the player should be able to study recent games before the match. But this is pretty typical, there were similar late-stage improvements with Chinook (checkers) and Deep Blue (chess).
Between that time and the Lee Sedol match, the hardware running AlphaGo was switched, to these TPU.
From the paper: "The final version of AlphaGo used 40 search threads, 48 CPUs, and 8 GPUs. We also implemented a distributed version of AlphaGo that exploited multiple machines, 40 search threads, 1,202 CPUs and 176 GPUs."
My guess as to why they're announcing the TPU is that they are feeling the pressure from Facebook and other AI labs, and want to reinforce their reputation as being the best place to do AI research. By revealing that AlphaGo was based on this hardware, they indicate to researchers around the world that if you want to build the most advanced ML models you need to be at Google. Same reason they talked about MapReduce/GFS back in the day.