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It’s interesting to think, when a company starts to vertically integrate, how deep do you go? Seems like OpenAI is exploring its own devices/OS as well, which

It’s interesting to think, when a company starts to vertically integrate, how deep do you go? Seems like OpenAI is exploring its own devices/OS as well, which makes sense to me, but it’s a vertical integration bet. This seems to be another big bet, but they could benefit from having their own optimized chips regardless of whether the device/OS bet wins out. Extremely exciting times for OpenAI!

hashtag-til 3y ago
Very exciting (from an engineer point of view), but there is much much more in a chips/devices/OS than "AI". It's a trap! To me, it seems like a distraction for them to go into devices stuff, rather than making their stuff so relevant that device vendors (Android/iOS) can't ignore. At the moment they can because they got good enough competitor solutions.
- baq 3y ago
  Depends what they've got under the hood. If they found a theoretical way to infer something like GPT-3.5 without using so much RAM and can build a chip which makes this feasible in laptops or (holy grail) phones, they've got their moat for a 12-24 months, possibly more if they manage to patent it. Big if though.
  - leetcodesucks 3y ago
    [dead]
  - Legend2440 3y ago
    There's almost certainly no way to avoid using massive amounts of memory. But you could build a device with more memory...
- vineyardmike 3y ago
  Considering the unit prices of NVidia chips, and the growing cuda software lock-in, it seems “obvious” to work on something to hedge against price increases. That might be the performance or cost edge they need. If they just make android phones better, they risk Google benefitting off their efforts and replacing the models. Besides that’s a lot more work to partner and manage across the industry. It seems risky to bet they can release consumer hardware (instead of server side) but that’s the ultimate big bet. Ask Meta how it feels to be “just an app”.
theptip 3y ago
> how deep do you go? As far as gives you a competitive edge! For AI, to win you need better data and compute than your competitors. Going up the stack to consumer devices seems like a somewhat speculative move, though I understand the underlying desire to secure a data moat. Going down the stack to chips makes a lot of sense; if you can secure an edge in compute efficiency then you will beat anybody that doesn't have substantially more data than you do.

hashtag-til 3y ago

Very exciting (from an engineer point of view), but there is much much more in a chips/devices/OS than "AI". It's a trap! To me, it seems like a distraction for them to go into devices stuff, rather than making their stuff so relevant that device vendors (Android/iOS) can't ignore. At the moment they can because they got good enough competitor solutions.

baq 3y ago
Depends what they've got under the hood. If they found a theoretical way to infer something like GPT-3.5 without using so much RAM and can build a chip which makes this feasible in laptops or (holy grail) phones, they've got their moat for a 12-24 months, possibly more if they manage to patent it. Big if though.
- leetcodesucks 3y ago
  [dead]
- Legend2440 3y ago
  There's almost certainly no way to avoid using massive amounts of memory. But you could build a device with more memory...
vineyardmike 3y ago
Considering the unit prices of NVidia chips, and the growing cuda software lock-in, it seems “obvious” to work on something to hedge against price increases. That might be the performance or cost edge they need. If they just make android phones better, they risk Google benefitting off their efforts and replacing the models. Besides that’s a lot more work to partner and manage across the industry. It seems risky to bet they can release consumer hardware (instead of server side) but that’s the ultimate big bet. Ask Meta how it feels to be “just an app”.

theptip 3y ago

> how deep do you go? As far as gives you a competitive edge! For AI, to win you need better data and compute than your competitors. Going up the stack to consumer devices seems like a somewhat speculative move, though I understand the underlying desire to secure a data moat. Going down the stack to chips makes a lot of sense; if you can secure an edge in compute efficiency then you will beat anybody that doesn't have substantially more data than you do.