Open source

AIAndrew Ng says OpenWorker, his open-source agent harness for cybersecurity workflows, will run each agent's commands inside a sandbox built on Nvidia OpenShell. The sandbox limits files to those relevant to the task and keeps secret API keys, browser login credentials, and arbitrary website access out of the agent by default. Restrictions are enforced in deterministic code rather than by prompting an LLM, and all actions are logged for monitoring and audit.

AIK3-Node is a graph neural network library built natively on Keras 3, with models that run on JAX, PyTorch, and TensorFlow with hardware acceleration including Apple Silicon and TPU. According to the post, it achieves 100% public API parity with PyG and incorporates foundation models and architectures from Spektral and StellarGraph.

AIHugging Face is inviting developers to suggest features for Gradio, its tool for building AI app frontends. The post follows a quoted message from Abid Lab noting that Gradio's original purpose has shifted and that the team is redesigning it from scratch around developers' current challenges with AI apps.

AIMistral CEO Arthur Mensch argues that only an open ecosystem can guarantee AI safety. The post responds to NVIDIA's announcement of the Open Agent Safety Platform, which brings together OpenShell and Sentry with over 100 industry partners.

AIwhich links to a page for trying the model. The quoted announcement describes it as the second model in the Claude 5.5 family, a clear upgrade over Sonnet 5 that runs more than 30% faster and costs up to 30% less for most work.

Why it matters: The post shows the model's availability inside v0 and links a test entry point, though it gives no performance details beyond the quoted claims.

AIGoogle Gemma announces a competition with two tracks: an Autonomous SWE Track focused on open-source model fine-tuning, reinforcement learning, and repository navigation, and a Research Paper Track for unpublished work advancing agentic software engineering. The post says top research papers will be featured at NeurIPS.

AIKilo participated in two Builders & Brews events last Friday, with Jo Riet Bergen speaking in Amsterdam and Cold Open in NYC. The Nebius and Tavily series is part of the Nebius x NVIDIA online hackathon, and Kilo says builders can use Nebius Token Factory inference inside Kilo.

AIGoogle Cloud argues startups should combine open-weight models with frontier APIs rather than routing every request to one frontier model. It cites Gemma 4, which spans five sizes including a 31B dense model and a 26B A4B Mixture-of-Experts model, released under Apache 2.0. The article's examples report a 44% latency drop for Cue, from 876 ms to 488 ms, and a $0 server cost for BetterSpeak's on-device Gemma 4 E2B.

AILovable announced a partnership with Microsoft that lets users publish apps into their company's Microsoft Entra tenant using Copilot Managed Runtime. Apps can connect to Microsoft 365, Fabric, Dataverse, and SQL data, and staff sign in with their work login. Copilot Managed Runtime is in public preview, and Microsoft 365 connectors, Fabric, and Microsoft sign-in are available on every Lovable plan, while Entra workspace sign-in is included on Business and Enterprise.

AINVIDIA announced the NVIDIA Open Agent Safety Platform with more than 100 industry partners to set security boundaries for AI agents. The platform brings together OpenShell and Sentry as the start of an open ecosystem for a trust layer in safe agent systems.

AIXiaomi has released MiMo-V2.6-Flash-MOPD on Hugging Face, an upgrade of the MiMo-V2.6-Flash-RL checkpoint that fuses several domain-specialized teachers into one model. The sparse MoE model has 309B total and 15B activated parameters, a 1M-token context length, and supports text, image, video, and audio inputs. The checkpoint targets tool-call repetition, a failure mode where the model repeatedly issues the same or similar tool calls without making progress.

AIWill Depue says a pretraining API for Tinker would be very successful, likely mainly through enterprise and quote-based sales. He notes there is no good open-source pretraining stack, unlike the available open-source options for RL.

AIXiaomi has released MiMo-V2.6-Pro-MOPD, an upgrade of the MiMo-V2.6-Pro-RL checkpoint that fuses several domain-specialized teachers into one model via MOPD2 and targets tool-call repetition. The sparse MoE model has 1.02T total and 42B activated parameters, a 1M-token context length, and accepts text, image, video, and audio inputs. Weights are available on Hugging Face and ModelScope, with deployment recipes for SGLang and vLLM.

AIXiaomi released an open-source RL environments repository, MiMo-V2.6-RL-oss, on Hugging Face. Hugging Face CEO Clément Delangue promoted the release, and a commenter estimated that comparable commercially sold tasks cost hundreds to thousands of dollars each.

AIAlexander Doria reports that the released set is a smaller selection of 989 environments for RL training a 9B distilled model, not the full MiMo. Rewards are not self-contained: the general part requires setting up a judge, and webdev relies on its own grader service and VLM. The most important content is in the general/envs directory and Docker setup rather than the Hugging Face dataset, offering a solid mix of real and simulated documents.

AIShanghai AI Lab's InternLM released Intern-Decision-4B, a multimodal structured decision model fine-tuned from Qwen3.5-4B, which returns answer distributions for multiple questions in one forward pass. On its benchmark table it scores an average of 90.02 with a Brier score of 0.347 and an ECE of 0.065, and per-query latency averages 44.16 ms on a single RTX 4090. The model is available with a Python DecisionEngine inference interface.

AIShanghai AI Lab's InternLM released Intern-Decision-2B, a multimodal structured decision model fine-tuned from Qwen3.5-2B that returns calibrated answer distributions for multiple questions in one forward pass. It averages 84.68 across listed benchmarks with a 0.437 Brier score and 33.28 ms mean latency on a single RTX 4090. Model weights, a Python DecisionEngine API, and GitHub code are available, with support for up to 16 questions and eight images.

AIInternLM released Intern-Decision-0.8B, a multimodal structured decision model fine-tuned from Qwen3.5-0.8B that scores answers to multiple questions in one forward pass. The model reports a 79.38 average score and a 33.98 ms mean latency on a single RTX 4090, with 0.8B, 2B, and 4B sizes available. It is accessed through a Python DecisionEngine API that returns calibrated probabilities rather than generating free-form text.

AIMicrosoft announced Autopilot, an always-on agent built on OpenClaw. The OpenClaw account highlights that Microsoft contributors, including Omar Shahine, have contributed back to the OpenClaw project.

AIHiggsfield AI published an open-source breakdown of its "Passport Rush" project, including every prompt and asset used. The post links to the project page on higgsfield.ai for readers to explore the materials.

AICanvases in the GitHub Copilot app are customizable interfaces that you and the agent share, such as kanban boards, dashboards, or checklists. You create one by running /create-canvas and describing the workflow, what you can do in the interface, and what the agent can do. Changes made by either you or the agent appear immediately in the shared canvas, and completed canvases can be saved as reusable extensions.