Kubernetes v1.35: Fine-grained Supplemental Groups Control Graduates to GA - kubernetes.io/blog/2025/12/2… #Kubernetes

6月11日 (木) 19時から開催します。ぜひご参加くださいー！ "#Kubernetes Meetup Tokyo #74 KubeCon Europe 2026 - connpass" #k8sjp k8sjp.connpass.com/event/395…

Introducing DiffusionBlocks: Block-wise Neural Network Training via Diffusion Interpretation pub.sakana.ai/diffusionblock… What if we didn’t have to hold an entire neural network in memory to train it? Standard neural net training optimizes all parameters jointly. As a result, the memory required during training grows linearly with the depth of the network. In our #ICLR2026 paper, we propose DiffusionBlocks, a principled framework to train networks one block at a time, drastically reducing memory requirements while matching end-to-end performance. With DiffusionBlocks, we split the network into blocks and train them one at a time, so you only need memory for a single block. How? We explicitly assign each block a role: to move the representation a little closer to the target than the block before it did. That role turns out to be precisely what a diffusion model does, step by step. Each block only needs to optimize its own objective and can be trained independently. We validated this across five different architectures: • ViT • DiT • Masked diffusion • Autoregressive transformers • Recurrent-depth transformers In each case, performance is competitive with end-to-end training while using a fraction of the memory. This perspective also extends naturally to recurrent-depth (Looped) transformers, which apply the same network iteratively and normally require expensive backpropagation through time (BPTT). Viewed through DiffusionBlocks, we can replace those multiple iterations with a single forward pass during training. Read our paper and code, to learn more. Paper: arxiv.org/abs/2506.14202 GitHub: github.com/SakanaAI/Diffusio… 🐟

KubeCon CloudNativeCon Japan 2026のCo-located Eventとして、Japan Community Day 2026を今年も開催します！ 参加登録も開始！ 前回は参加枠が早い段階で埋まったのでお早めに登録お願いします🙇 昨年実施の内容 ocgroups.dev/cncf/group/bqd9… #CNCF #CNCJ #Kubernetes #k8sjp #ebpfjp #oteljp

本日 5/21 (木) 19時からの開催です。 "Kubernetes 変更内容共有会（v1.36） - connpass" kubernetes-updates.connpass.…