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。
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]]
Nvidia buys Groq (language processing units faster than gpu's Nvidia's thing). Prevent the bubble from popping by blowing into the bubble? Acq of Groq is partly admission gpu's not a solid footing anymore?
Het bedrijf ontwikkelt al een AI-naar-FPGA-platform waarmee elk AI-model kan draaien op goedkope, in de EU geproduceerde herconfigureerbare chips. Als ze hierin slagen, zou dit de afhankelijkheid van Europa van buitenlandse GPU-fabrieken volledig kunnen wegnemen, een terugkerend thema in de strategie van Vydar.
A potential path away from NVIDIA it seems, but not at the moment, the text suggests.
NVIDIA Jetson.
NVIDIA Jetson is the industry default, source of strategic vuln, high cos.
SoftBank Japan cashing out on NVIDIA. Is this a 1st step down the hype curve into the trough? Although they are also highly invested in OpenAI.
1000x Increase in AI Demand
Google’s new AI chip is a rival to Nvidia, and its Arm-based CPU will compete with Microsoft and Amazon
For Nvidia, the speed of the 3080 package makes for a solid sales pitch: This cloud PC is probably faster than your home system, so cloud gaming is worth it. Cloud gaming will always present a latency tradeoff, but that latency is easier to accept if you're getting otherwise-unattainable graphics quality along with it.
Smart strategy by Nvidia.
Relative recent article on alternatives for optirun, primusrun, etc
someday, NVIDIA GPUs in the cloud will enable real-time transcription and translation for videoconferencing
... and that will be also the day when most of the simultaneous interpreters will go out of business https://en.wikipedia.org/wiki/Simultaneous_interpretation
Coming back to the two ‘FreeSync’ settings in the monitor OSD, they differ in the variable refresh rate range that they support. ‘Standard Engine’ supports 90 – 144Hz (90 – 119Hz via HDMI) whilst ‘Ultimate Engine’ gives a broader variable refresh rate range of 70 – 144Hz (62 – 119Hz via HDMI). We didn’t notice any adverse effects when using ‘Ultimate Engine’, so we’d suggest users simply stick to that option.
In my tests using Standard Engine, in combo with G-Sync Compatible Driver, I get more screen flickering during menus.