Red Hat

Headlines · 4

1. 2d
   Linux kernel to drop Assisted-by tag requiring disclosure of AI tool use

   Linux kernel maintainers reached consensus at the Maintainers Summit to deprecate the “Assisted-by” tag, which since January had asked contributors using “any sort of advanced coding tool” to declare it in commit messages, and to remove the documentation requiring it. The patch was proposed on 9 October by kernel developer and Nvidia engineer Sasha Levin and drew more than 50 replies; Red Hat's Jeff Layton argued the tag is unevenly followed and “basically serves as free advertising for proprietary LLM companies.” Laurent Pinchart objected to removing it without a replacement disclosure mechanism, while Linus Torvalds called such mandatory rules “utterly stupid” in a 13 October mailing-list reply, saying what matters is whether submitters understand their own code. The change is not yet in effect, and developers are still expected to review their code, follow licensing rules and sign off the DCO.

   科技新报 · 🔥 6
2. 4d
   AI doubters grow louder as IBM bets on commodity models and inference shift

   On the latest theCUBE Pod, SiliconANGLE's John Furrier and Dave Vellante discussed rising public doubt about AI against reports that OpenAI's annualized net revenue is about $50 billion — roughly $20 billion below earlier figures — with shares of Nvidia, CoreWeave, Oracle and Nebius falling. The analysts called the backlash an “AI freakout moment” and said IBM is betting on model commoditization, building on Red Hat's open-source foundation to offer a four-part architecture of agents, data, automation and hybrid infrastructure plus an orchestration layer that can integrate agents from multiple vendors. The episode also cited Marvell's target of $70 billion to $90 billion in revenue for fiscal 2031 and a workload mix that has moved from about 90/10 training-to-inference a year ago to roughly 60/40, with an expected flip to 10/90.

   SiliconANGLE AI · 🔥 0
3. 5d
   Intel to retire SGX after Xeon Diamond Rapids, pivoting to TDX

   Intel has announced that its upcoming Xeon "Diamond Rapids" will be the last generation to support Software Guard Extensions (SGX), after which the company will concentrate its confidential computing efforts on Trust Domain Extensions (TDX), according to Tom's Hardware. Existing SGX-enabled platforms will keep receiving security updates and support into the early 2030s, giving customers time to validate and migrate to TDX, which isolates entire virtual machines from the host and other VMs so existing workloads can be protected with minimal application changes. Intel also plans to expand TDX with TDX Connect trusted I/O, post-quantum cryptography and enhanced attestation, and says TDX can give multiple agents hardware-isolated VMs on shared infrastructure for agentic AI workloads.

   Tom’s Hardware · 🔥 0
4. Oct 9
   vLLM adds Vera Rubin NVL72 support, citing 7.8x throughput over GB200 NVL72

   The vLLM team, working with Inferact, Red Hat and NVIDIA, says vLLM now runs on NVIDIA Vera Rubin NVL72 with daily container builds (vllm/vllm-openai:cu134-nightly on CUDA 13.4 and PyTorch 2.15) and can serve models including DeepSeek, Kimi, GLM and MiniMax. Because Rubin continues the Blackwell architecture family (sm100f kernels can run unmodified), early results claim up to 7.84x throughput per GPU versus GB200 NVL72 on SemiAnalysis AgentX with MiniMax M3 at matched interactivity, and up to 3.7x VLM throughput versus GB300 NVL72 in MLPerf Inference v6.1 using Qwen3-VL-235B-A22B. Rubin NVL72 is described as offering 5x NVFP4 FLOPS, about 2.4x HBM bandwidth and 1.7x sixth-generation NVLink bandwidth over GB200 NVL72, while vLLM uses FlashInfer 0.7.0 Rubin-tuned kernels and CUDA 13.4 locality domains to speed up MoE decode by roughly 1.2x in preliminary tests. All figures are early, self-reported results from the collaborating teams.

   vLLM Blog · 🔥 0

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