Their DPO will be interested so he can laugh about it and ask ChatGPT for an excuse letter. Their EU customers may be concerned but it’s not like anything will be done about it - especially not now when there are talks of relaxing the already non-enforced GDPR.
It looks like changing the permissions triggered creation of a new feature file, and it was ingestion of that file leading to blowing a size limit that crashed the systems.
The file should be versioned and rollout of new versions should be staged.
(There is definitely a trade-off; often times in the security critical path, you want to go as fast as possible because changes may be blocking a malicious actor. But if you move too fast, you break things. Here, they had a potential poison input in the pathway for synchronizing this state and Murphy's Law suggests it was going to break eventually, so the question becomes "How much damage can we tolerate when it does?")
> It looks like changing the permissions triggered creation of a new feature file, and it was ingestion of that file leading to blowing a size limit that crashed the systems.
That feature file is generated every 5 minutes at all times; the change to permissions was rolled out gradually over the clickhouse cluster, and whether a bad version of that file was generated depended on whether the part of the cluster that had the bad permissions generated the file.
If you're in SF, you don't want to miss this.
The Qwen team is making their first public appearance in the United States, with the VP of Qwen Lab speaking at the meetup below during SF teach week.
https://partiful.com/e/P7E418jd6Ti6hA40H6Qm
Rare opportunity to directly engage with the Qwen team members.
Honestly depends on when they got in. Seed investors? They're probably fine with their preferences. Series B and beyond? That's where it gets messy. What round you thinking?
It appears that they have really good toolings so they can focus on hiring really smart new grads and giving them a lot of leeway on choosing what to work on without worrying about how productive they will be. One particular memorable response when the CEO Liang was asked about not using KPI goes roughly like this: since we all reviewd and worked with the candidate, if he is not productive it must be our fault to not have given him the right support to make him productive.
It's probably more about the size of the firm. Once a company is large enough with middle layers and silos it seems some form of KPI is inevitable. This could also explain why Deepseek doesn't mind open sourcing as they have not raised outside capital for expansion so they can't really scale rapidly on their own.
- Up to 1350+ FP8 TFLOPS on Hopper GPUs
- No heavy dependency, as clean as a tutorial
- Fully Just-In-Time compiled
- Core logic at ~300 lines - yet outperforms expert-tuned kernels across most matrix sizes
- Supports dense layout and two MoE layouts
Wan2.1, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. Wan2.1 offers these key features:
- SOTA Performance: Wan2.1 consistently outperforms existing open-source models and state-of-the-art commercial solutions across multiple benchmarks.
- Supports Consumer-grade GPUs: The T2V-1.3B model requires only 8.19 GB VRAM, making it compatible with almost all consumer-grade GPUs. It can generate a 5-second 480P video on an RTX 4090 in about 4 minutes (without optimization techniques like quantization). Its performance is even comparable to some closed-source models.
- Multiple Tasks: Wan2.1 excels in Text-to-Video, Image-to-Video, Video Editing, Text-to-Image, and Video-to-Audio, advancing the field of video generation.
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- Powerful Video VAE: Wan-VAE delivers exceptional efficiency and performance, encoding and decoding 1080P videos of any length while preserving temporal information, making it an ideal foundation for video and image generation.
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