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Today on Digital Foundry, Alexander Battaglia spends some time talking machine learning, DLSS and more with Nvidia's Bryan Catanzaro - Bryan Catanzaro:

61,507 次观看 • 1 年前 •via X (Twitter)

4 条评论

Nucleosynthesis 的头像
Nucleosynthesis1 年前

@Dachsjaeger @ctnzr That Nvidia man looks like he's from the far future :p

SecBriefs | Making Cybersecurity Simple 的头像
SecBriefs | Making Cybersecurity Simple2 年前

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Vincent Adultman 的头像
Vincent Adultman1 年前

@Dachsjaeger @ctnzr "Gamers don't care about V-Sync" That's so blatantly wrong. It is very hard to get VRR right. Most VA and OLED panels have VRR Flicker when using G-Sync. Frame Gen being not compatible with V-Sync basically makes Frame Gen worthless to me as a 4090 owner.

Sam - The MN Tesla Guy 的头像
Sam - The MN Tesla Guy1 年前

@Dachsjaeger @ctnzr This was an awesome interview. Always love listening to Bryan! Very excited to see how neural rendering advances.

相关视频

Inside Nemotron and NVIDIA's AI lab: my conversation with Bryan Catanzaro (Bryan Catanzaro). NVIDIA is a chip company. So why does it put hundreds of researchers on building AI models - and then give them away for free? We go deep into the Nemotron models, what it takes to build a top AI lab, and the future of frontier AI. 01:33 - Is open source AI catching the frontier? 05:29 - Do closed labs blocking distillation slow open source down? 07:42 - Is the US falling behind China? 10:30 - Why companies actually choose open models 12:39 - A "crazy" 2008 bet: machine learning on GPUs 15:33 - Working with Andrew Ng and Dario Amodei at Baidu 17:41 - Coming back to NVIDIA: DLSS and the birth of Megatron 21:55 - The real reason NVIDIA builds its own models 24:28 - Is Moore's Law really dead? 33:37 - The Nemotron family: Nano, Super, Ultra 35:09 - Built for agents: why NVIDIA bets on speed 36:02 - How you train a 550B model in 4 bits 39:25 - Hybrid Mamba-Transformer, explained simply 42:31 - Mixture of experts, and why NVIDIA built NVL72 around it 47:26 - Why a 1-million-token context window matters 49:26 - Multi-token prediction: how the model predicts 5 tokens at once 52:47 - Multi-teacher distillation: teaching one model from many 58:01 - Where reinforcement learning goes next 01:00:16 - Inside NVIDIA's research org: "the mission is the boss" 01:04:03 - How NVIDIA decides who gets the GPUs 01:10:53 - Why NVIDIA still feels entrepreneurial after 33 years 01:12:58 - Why Bryan doesn't believe in the singularity 01:17:50 - The AI backlash 01:19:18 - The controversial case: open AI is safer than closed

Matt Turck

56,954 次观看 • 2 个月前