Notably among hyperscalers, Google's compute comes primarily from its own custom TPU chips rather than NVIDIA's GPUs.
Google 是四大超大规模云厂商中唯一不主要依赖 NVIDIA 的。微软、Meta、亚马逊的算力主体仍是 NVIDIA GPU，而 Google 用自研 TPU 走出了一条独立路线。这意味着在 AI 算力版图上，真正存在两套「操作系统」：NVIDIA 生态和 Google 生态——而前者的统治地位被严重高估了。
Google holds the equivalent of around 5 million Nvidia H100 GPUs in compute capacity, roughly 25% of the world's total!
大多数人可能认为Nvidia是AI计算能力的最大拥有者，因为他们的芯片被广泛使用，但作者认为谷歌通过其自研TPU芯片拥有相当于500万块H100 GPU的计算能力，占全球总量的25%。这表明自研芯片战略可能比购买商用芯片更能建立计算优势。
https://www.facebook.com/groups/TypewriterCollectors/posts/10163311006014678/
Some interesting 3-D printing advice for replacement typewriter feet here.
Zach Hubbird recommends using a filament dryer and Shore A 85 (or lower) TPU from Siraya Tech as 95A isn't great. Many feel that 95A isn't as "grippy".
Erik Bruchez also recommends 85A while Marty Morren suggests 70A and is contemplating sourcing 60A in the future.
Google’s biggest advantage lies under the hood. Almost every other AI lab trains with NVIDIA GPUs, which are sold at a margin that props up NVIDIA’s multi-trillion dollar valuation. Google use their own in-house hardware, TPUs, which they’ve demonstrated this year work exceptionally well for both training and inference of their models. When your number one expense is time spent on GPUs, having a competitor with their own, optimized and presumably much cheaper hardware stack is a daunting prospect.
Google has a hardware stack advantage: they have their own hardware / processors, and not dependent on Nvidia GPUs. Vgl Nvidia's acq of Groq [[Nvidia koopt AI-technologie Groq voor 20 miljard dollar]]
https://www.reddit.com/r/typewriters/comments/1ov02h8/backing_material_2/
Experiments with different backing sheets in typewriters.
A Shore A 60 silicone backing sheet wasn't a great improvement. A 0.3mm TPU sheet with 75A to 80A may prove better results?
Google said Axion provides “up to 30% better performance than the fastest general-purpose Arm-based instances available in the cloud today” and “up to 50% better performance and up to 60% better energy-efficiency” than other general purpose Arm chips.
Google’s new AI chip is a rival to Nvidia, and its Arm-based CPU will compete with Microsoft and Amazon
The on-board Edge TPU coprocessor