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Why did NVIDIA jump into building its own open-source AI models?



We grabbed some time with Bryan Catanzaro—VP of Applied Deep Learning Research at NVIDIA—right after his session at a major AI conference. The conversation? All about Nemotron and what's driving their open-source push.

Catanzaro broke down the thinking behind NVIDIA's move into open AI model development, touching on everything from research priorities to what Nemotron brings to the table for developers. It's a rare peek into how one of the biggest players in AI infrastructure is approaching the open-source landscape.

The full conversation covers their research direction, community impact, and where they see things headed.
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GasFeeAssassinvip
· 10h ago
NGL, Jensen Huang’s move here is pretty brilliant... In this open-source model game, it seems like Nvidia wants to benefit from the infrastructure while also not being completely held hostage by OpenAI and the like.
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ProtocolRebelvip
· 10h ago
It's stuck, huh? Is Nvidia shifting from selling chips to selling models? Or is open source just a front...
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WhaleMistakervip
· 10h ago
Is it lagging? Open-source models aren't anything new. Is Nvidia really going head-to-head with Meta and Google now?
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Blockblindvip
· 10h ago
Open-source cards? Nvidia's move is interesting—it feels like they're trying to lock down the ecosystem using free stuff, haha.
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SandwichHuntervip
· 10h ago
Another major company has open-sourced its model... Is NVIDIA trying to take everyone's jobs this time?
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StakeOrRegretvip
· 10h ago
Nvidia is trying to secure its position here. If they didn't go open source, they would have been criticized to death, but now by going open source, they can ride the hype. This move is pretty shrewd... Nemotron sounds good, but can it really outperform all those open-source models?
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ReverseTrendSistervip
· 10h ago
Haha, NVIDIA finally couldn't hold back and had to start working on models themselves. Is it because chip sales are slowing down, or have they truly realized the importance of the ecosystem? Nemotron sounds pretty impressive, but I wonder how it actually performs in practice...
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