<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>w-m</author><text>Impressions from last week’s CVPR, a conference with 12k attendees on computer vision - Pretty much everyone is using NVIDIA GPUs, and pretty much everyone isn’t happy with the prices, and would like some competition in the space:&lt;p&gt;NVIDIA was there with 57 papers, a website dedicated to their research presented at the conference, a full day tutorial on accelerating deep learning, and ever present with shirts and backpacks in the corridors and at poster presentations.&lt;p&gt;AMD had a booth at the expo part, where they were raffling off some GPUs. I went up to them to ask what framework I should look into, when writing kernels (ideally from Python) for GPGPU. They referred me to the “technical guy”, who it turns out had a demo on inference on an LLM. Which he couldn’t show me, as the laptop with the APU had crashed and wouldn’t reboot. He didn’t know about writing kernels, but told me there was a compiler guy who might be able to help, but he wasn’t to be found at that moment, and I couldn’t find him when returning to the booth later.&lt;p&gt;I’m not at all happy with this situation. As long as AMDs investment into software and evangelism remains at ~$0, I don’t see how any hardware they put out will make a difference. And you’ll continue to hear people walking away from their booth, saying “oh when I win it I’m going to sell it to buy myself an NVIDIA GPU”.</text><parent_chain></parent_chain></comment><story><title>Testing AMD&apos;s Giant MI300X</title><url>https://chipsandcheese.com/2024/06/25/testing-amds-giant-mi300x/</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>jsheard</author><text>All eyes are of course on AI, but with 192GB of VRAM I wonder if this or something like it could be good enough for high end production rendering. Pixar and co still use CPU clusters for all of their final frame rendering, even though the task is ostensibly a better fit for GPUs, mainly because their memory demands have usually been so far ahead of what even the biggest GPUs could offer.&lt;p&gt;Much like with AI, Nvidia has the software side of GPU production rendering locked down tight though so that&amp;#x27;s just as much of an uphill battle for AMD.</text><parent_chain></parent_chain></comment><story><title>Testing AMD&apos;s Giant MI300X</title><url>https://chipsandcheese.com/2024/06/25/testing-amds-giant-mi300x/</url></story>