| ▲ | VirusNewbie 4 hours ago |
| If there was no moat, nvidia and meta would have SoTA models too. |
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| ▲ | evilduck 2 hours ago | parent | next [-] |
| Nvidia does have one of the best completely open models. Open weights are nice but Nemotron is open training data too. |
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| ▲ | seunosewa 4 hours ago | parent | prev | next [-] |
| Meta is awfully close. |
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| ▲ | amazingamazing 4 hours ago | parent | prev | next [-] |
| It is not in nvidia’s interest to be too good at model creation |
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| ▲ | reilly3000 2 hours ago | parent | next [-] | | But it is in their interest that their customers can use their models as a base for post-training and LoRAs. | | | |
| ▲ | david-gpu 3 hours ago | parent | prev [-] | | Why not? Commoditize your complement, and all that. | | |
| ▲ | angulardragon03 2 hours ago | parent [-] | | And if they get too good, they risk harming or otherwise killing their golden geese (their customers), who they are heavily invested in. | | |
| ▲ | david-gpu 2 hours ago | parent [-] | | How? Imagine an open-weight model comes out that is somehow better than proprietary solutions. Now the marginal cost for the consumer is just the cost of renting the inference hardware, without having to pay the overhead of the owner of a proprietary model. And because it is cheaper, more customers want to use it, and Nvidia will sell the providers the inference hardware that they need. | | |
| ▲ | amazingamazing 34 minutes ago | parent [-] | | 1. No open ai and anthropic means no buying gpus to train. Now nvidia spends money on hardware training their own models. Opportunity cost plus expense. 2. Any open models created from this will not necessarily need their silicon, see apple mlx. |
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| ▲ | sensanaty 3 hours ago | parent | prev [-] |
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