6 of 34 papers at SBC this year are co-authored by Category Labs researchers. We're at Stanford all week, presenting across the main program, the MEV Workshop, and the Whitepaper Reading Club. Schedule below. Come say hi!

Most motion papers tailor one controller to one specific task. This year at SIGGRAPH, our research team asks: can motor control itself be pretrained and reused? Generative Pretrained Controllers, or GPC, turn motor skills into a vocabulary of discrete tokens and train a transformer-based generative controller through next-token prediction. Just like GPT, the same pretrained controller can then be fine-tuned to solve new tasks. Trained on 600+ hours of motion, GPC runs in real-time inside a physics simulation, producing natural and physically grounded behaviors for interactive control.

🌐 Microsoft brought 11 papers to NSDI 2026, the frontier of large-scale networked systems. This digest spans concrete advances for AI infrastructure: 4x throughput from KV-cache reuse, 3.2x over RDMA with CXL memory, and more. Title: Microsoft at NSDI 2026: Advances in large-scale networked systems URL: 📝 Overview NSDI is a leading venue for sharing new research on the design and operation of cloud, AI, and distributed application infrastructure. This post highlights Microsoft's 11 accepted papers spanning datacenter networks, wide-area networking, AI systems, and cloud infrastructure. ❓ Challenges Solved As AI workloads surge, scaling datacenter network, memory, and CPU resources while preserving reliability and cost efficiency keeps getting harder. The papers tackle that frontier from both production operation and research angles. 💡 Key Research Contributions ・DroidSpeak reuses KV caches across same-architecture language model variants for up to 4x throughput with minimal impact on output quality ・SONiC DASH SmartSwitch redesigns cloud network offloading and is deployed at scale in Azure, significantly improving power and space efficiency (community award winner) ・Octopus, a CXL disaggregated memory pod, achieves RPCs 3.2x faster than in-rack RDMA and 2.4x faster than CXL switches on three-server prototypes ・HarvestContainers dynamically harvests cores from latency-sensitive containers, using up to 75% of spare CPU while keeping tail latency within 4% of standalone 🎯 Use Cases It informs design decisions for faster LLM serving, memory disaggregation, container resource utilization, and network-protocol verification across cloud and AI infrastructure. 📊 Other Results ・Eywa used LLM-based model generation to find 33 bugs (16 previously unknown) in protocol implementations ・ForestColl generates theoretically optimal collective-communication schedules in polynomial time ・AVA is a video-analytics benchmark reaching 75.8% accuracy on 10+ hour videos ・KRAKENGUARD provides fine-grained eBPF isolation for multi-tenant security #NetworkedSystems# #AIInfrastructure#