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@LinkNeal celebrate your birthday like the legend you are! 🎉🎉🎉
Therapist: Linear Mandarin is not real, it cannot hurt you. Linear Mandarin:
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Closing out Linea Exponent. Read the full update:
Codex @OpenAI + @linear + @zeddotdev is all you need. - Codex for feature development, terminal, git workflow - Linear for team context collaboration, git diff review, ticket management - Zed for fast manual code editing
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OpenAI dropped Symphony: agents that claim your Linear tickets, spin up isolated workspaces, and only ping you for review. Install by giving your AI a 2,000-line spec. Would you trust agents with your backlog?
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🚀 Introducing FlashQLA: high-performance linear attention kernels built on TileLang. ⚡ 2–3× forward speedup. 2× backward speedup. 💻 Purpose-built for agentic AI on your personal devices. 💡Key insights: 1. Gate-driven automatic intra-card CP. 2. Hardware-friendly algebraic reformulation. 3. TileLang fused warp-specialized kernels. FlashQLA boosts SM utilization via automatic intra-device CP. The gains are especially pronounced for TP setups, small models, and long-context workloads. Instead of fusing the entire GDN flow into a single kernel, we split it into two kernels optimized for CP and backward efficiency. At large batch sizes this incurs extra memory I/O overhead vs. a fully fused approach, but it delivers better real-world performance on edge devices and long-context workloads. The backward pass was the hardest part: we built a 16-stage warp-specialized pipeline under extremely tight on-chip memory constraints, ultimately achieving 2×+ kernel-level speedups. We hope this is useful to the community!🫶🫶 Learn more: 📖 Blog: 💻 Code:
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the function health designer really took the linear logo, threw in some more lines, and called it a day