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A related argument I raised a few days back on HN: What's the moat with with these giant data-centers that are being built with 100's of billions of dollars on
by freakynit 8mo ago
A related argument I raised a few days back on HN:
What's the moat with with these giant data-centers that are being built with 100's of billions of dollars on nvidia chips?
If such chips can be built so easily, and offer this insane level of performance at 10x efficiency, then one thing is 100% sure: more such startups are coming... and with that, an entire new ecosystem.
- codebje 8mo agoRAM hoarding is, AFAICT, the moat.
- freakynit 8mo agolol... true that for now though
- Windchaser 8mo agoYeah, just cause Cisco had a huge market lead on telecom in the late '90s, it doesn't mean they kept it. (And people nowadays: "Who's Cisco?")
- wmf 8mo agoThey did mostly keep it though.
- Windchaser 8mo agoSure, but it's taken their stock price about 20 years to recover.
- bee_rider 8mo agoI think their hope is that they’ll have the “brand name” and expertise to have a good head start when real inference hardware comes out. It does seem very strange, though, to have all these massive infrastructure investment on what is ultimately going to be useless prototyping hardware.
- elictronic 8mo agoTools like openclaw start making the models a commodity. I need some smarts to route my question to the correct model. I wont care which that is. Selling commodities is notorious for slow and steady growth.
- jzymbaluk 8mo agoYou'd still need those giant data centers for training new frontier models. These Taalas chips, if they work, seem to do the job of inference well, but training will still require general purpose GPU compute
- mlboss 8mo agoIf I am not mistaken this chip was build specifically for the llama 8b model. Nvidia chips are general purpose.
- wmf 8mo agoNvidia bought all the capacity so their competitors can't be manufactured at scale.