Rice research could make weird AI images a thing of the past - Rice University
<a href="https://news.google.com/rss/articles/CBMiiwFBVV95cUxQNS1kWUFDT0hrcmoxTnM1cmxhM1MwcUVyaWNSSHNGSVA5M1lTXzRzVFpzZWRQdHF1azNXQ081dmpqZVdpNTU0MWNtbGRUa3g3T2J1UkxYM21OZ3FfWEVSaGNiUWpuaVh6eHVxZEl2V2NkMHNseXVsRmRqakhNVno1NTZVYV9PWGQzWUw4?oc=5" target="_blank">Rice research could make weird AI images a thing of the past</a> <font color="#6f6f6f">Rice University</font>
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research![[P] GPU friendly lossless 12-bit BF16 format with 0.03% escape rate and 1 integer ADD decode works for AMD & NVIDIA](https://d2xsxph8kpxj0f.cloudfront.net/310419663032563854/konzwo8nGf8Z4uZsMefwMr/default-img-robot-hand-JvPW6jsLFTCtkgtb97Kys5.webp)
[P] GPU friendly lossless 12-bit BF16 format with 0.03% escape rate and 1 integer ADD decode works for AMD & NVIDIA
Hi everyone, I am from Australia : ) I just released a new research prototype It’s a lossless BF16 compression format that stores weights in 12 bits by replacing the 8-bit exponent with a 4-bit group code . For 99.97% of weights , decoding is just one integer ADD . Byte-aligned split storage: true 12-bit per weight, no 16-bit padding waste, and zero HBM read amplification. Yes 12 bit not 11 bit !! The main idea was not just “compress weights more”, but to make the format GPU-friendly enough to use directly during inference : sign + mantissa: exactly 1 byte per element group: two nibbles packed into exactly 1 byte too https://preview.redd.it/qbx94xeeo2tg1.png?width=1536 format=png auto=webp s=831da49f6b1729bd0a0e2d1f075786274e5a7398 1.33x smaller than BF16 Fixed-rate 12-bit per weight , no
Quoting Greg Kroah-Hartman
Months ago, we were getting what we called 'AI slop,' AI-generated security reports that were obviously wrong or low quality. It was kind of funny. It didn't really worry us. Something happened a month ago, and the world switched. Now we have real reports. All open source projects have real reports that are made with AI, but they're good, and they're real. Greg Kroah-Hartman , Linux kernel maintainer ( bio ), in conversation with Steven J. Vaughan-Nichols Tags: security , linux , generative-ai , ai , llms , ai-security-research
Quoting Daniel Stenberg
The challenge with AI in open source security has transitioned from an AI slop tsunami into more of a ... plain security report tsunami. Less slop but lots of reports. Many of them really good. I'm spending hours per day on this now. It's intense. Daniel Stenberg , lead developer of cURL Tags: daniel-stenberg , security , curl , generative-ai , ai , llms , ai-security-research
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