humans can do this in well under half an hour.

SubQ Sparse Attention is 52× faster than FlashAttention in our architecture-level comparison, while requiring 63% less compute.

With a research result at 12 million tokens, SubQ's architecture reduces attention compute by almost 1,000x compared to other frontier models.

Overall, it usually takes me about two hours to do this task. If only it were as simple as a single copy and paste, life would be so much easier — or so I thought.

By predicting these unified tokens, it effectively leverages diverse human data to achieve state-of-the-art data efficiency and robust out-of-distribution (OOD) generalization.

They also have the benefits of running on hardware that’s sipping power most of the time, rather than slurping it down in massive data centres.

What used to take reps 5-6 hours a week now runs automatically in the background on every deal.

🔹 **DeepSeek-V4-Flash:** 284B total / 13B active params. Your fast, efficient, and economical choice.

个人学习可能取决于他人行为的主张突出了将学习环境视为一个涉及多个互动参与者的系统的重要性

SSPP # 7.2 Power Usage Effectiveness (PUE) (Electronic Maximum annual weighted average PUE of 1.4 by FY15 )

Google’s ultra-efficient data centers, with a PUE of 1.12, are beating the PUE curve by miles.

When the project is complete later this year (all done while the existing data center remained in operation!), the data center's annual PUE will drop from 1.5 to 1.2, saving 20 percent of its annual electrical cost.

The MGHPCC is targeting a PUE of less than 1.3. A recent report cites typical data center PUEs at 1.9. This means that our facility can expect to