Yeah honestly. They could just try selling solutions and SLAs combining their TPU hardware with on-prem SOTA models and practically dominate enterprise. From what I understand, that's GCP's gameplay too for most regulated enterprise clients.
https://www.cnbc.com/2025/04/09/google-will-let-companies-ru...
Google has already started the process of letting companies self-host Gemini, even on NVidia Blackwell GPUs.
Although imho, they really should bundle it with their TPUs as a turnkey solution for those clients who haven't invested in large scale infra like DCs yet.
Its the same format as other software - you release the actual software for free but offer managed services that work with that software way better and easier.
Yeah but those are on Google's managed cloud, and not onprem. But that recent announcement has been specifically for Google Distributed Cloud, which is huge.
My point was a bit more specific though. To elaborate, I know of a number of publicly traded companies (USD $200M+ market cap) globally which have identified use cases for onprem AI and want to implement them actively but cannot, because they lack the knowhow to work with onprem, and hiring talent to implement that is just extremely expensive. Google should simply provide it as a turnkey bundle and milk them for it.
It’s my understanding that google makes bulk of ad money from search ads - sure they harvest a ton of data but it isn’t as valuable to them as you’d think. I suspect they know that could change so they’re hoovering up as much as they can to hedge their bets. Meta on the other hand is all about targeted ads.
Right so keeping things in house and seeing what people are asking Gemini would be probably better for them?
Relenting hardware like that would be such a cleansing old-school revenue stream for Google... just imagine...
Googles bread and butter is advertising, so they have a huge interest in keeping things in house. Data is more valuable to them than money from hardware sales.
Even then, I think that their primary use case is going to be consumer grade good AI on phones. I dunno why Gemma QAT model fly so low on the radar, but you can basically get full scale Llamma 3 like performance from a single 3090 now, at home.