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    <title>Building software with AI — USASI news</title>
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    <description>Dated, sourced news items about the organizations and records featured in the USASI Building software with AI hub. Independent project. Not a United States government website.</description>
    <language>en-us</language>
    <lastBuildDate>Tue, 13 Oct 2026 12:00:00 GMT</lastBuildDate>
    <item>
      <title>DSPy 3.4.1 makes InstructionProposer the default for GEPA and adds Python 3.15 support</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/dspy-3-4-1-makes-instructionproposer-gepa-default/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>On October 12, 2026 DSPy 3.4.1 was published on the project's GitHub repository. The release notes say it makes GEPA's structured InstructionProposer the default instruction proposer, lets dspy.RLM build DSPy sub-agents from inside its REPL, adds Python 3.15 support, and fixes a 3.4.0 import crash. The notes warn that GEPA's default reflection request changes shape, so optimization results can differ from 3.4.0 even with the same seed, and that the reflection LM must now be a dspy.LM that can return JSON. USASI has not tested this release.</description>
    </item>
    <item>
      <title>OpenHands 1.27.0 adds OpenCode and Pi as built-in ACP agents</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/openhands-1-27-0-adds-opencode-and-pi-acp-agents/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>OpenHands 1.27.0 was published on the project's GitHub repository on October 12, 2026. Its release notes list adding OpenCode and Pi as built-in ACP agents on local backends, taking ACP model lists from the agent instead of hardcoding them, connecting Agent Canvas to DigitalOcean Managed Agents on desktop and web, and a persisted automation draft management UI. A separate bug-fix release, 1.27.1, followed the same day. USASI has not tested either release.</description>
    </item>
    <item>
      <title>TRL 1.15.0 released with a fused LM head enabled by default</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/trl-1-15-0-released/</link>
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      <pubDate>Fri, 09 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>On October 8, 2026 Hugging Face published version 1.15.0 of TRL on GitHub. The release notes say the SFT, DPO, KTO, GRPO, RLOO and Distillation trainers now score tokens with a fused LM head, a Triton kernel that avoids building the full logits tensor, and that it is on by default; scoring this way needs Triton on a GPU. The notes list breaking changes: a PEFT adapter on lm_head now raises an error, and use_liger_kernel=True is deprecated in the GRPO, RLOO, DPO and KTO trainers and will be removed in v2.0.0. The release also adds selective activation checkpointing in SFT. USASI has not tested these changes.</description>
    </item>
    <item>
      <title>MLflow 3.17.0 released with fine-grained permissions and TypeSafe judge support</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/mlflow-3-17-0-released/</link>
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      <pubDate>Thu, 08 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>On October 7, 2026 the MLflow project published version 3.17.0 on GitHub. The release notes list &quot;Jev Decisions Across Evaluation, Gateway, and Tracing&quot;, which lets TypeSafe models be used in built-in scorers and custom judges, and &quot;Fine-Grained Permissions for Shared Resources&quot;, with wildcard grants and explicit DENY for contained resource types such as runs, traces, and versions. They also describe opt-in daily summaries for trace analytics. The notes say SQL-backed servers need a coordinated mlflow db upgrade with all writers stopped, and that mixed-version rolling upgrades are not supported. USASI has not tested these changes.</description>
    </item>
    <item>
      <title>Diffusers 0.41.0 adds a Qwen-Image 2.1 pipeline and deprecates ONNX support</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/diffusers-0-41-0-released/</link>
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      <pubDate>Thu, 08 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>On October 6, 2026 Hugging Face published Diffusers 0.41.0 on GitHub. The release notes say it adds Qwen-Image 2.1, with text-to-image generation, image editing, native transparency, and LoRA training, and introduces tensor-parallel checkpoint loading in which each rank reads its own slice of sharded weights. The notes deprecate ONNX support in favor of Optimum and remove previously deprecated APIs, including the LuminaText2ImgPipeline and Lumina2Text2ImgPipeline aliases. They also say minor releases will now be coordinated around new model integrations, as in Transformers. Qwen-Image 2.1 is a third-party model and is not a catalog entry; the notes do not state its license.</description>
    </item>
    <item>
      <title>Transformers 5.19.0 adds the EmbeddingGemma2 multimodal embedding model</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/transformers-5-19-0-adds-embeddinggemma2/</link>
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      <pubDate>Wed, 07 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>On October 6, 2026 Hugging Face published version 5.19.0 of its Transformers library on GitHub. The release notes add support for EmbeddingGemma2, which the notes describe as a multimodal embedding model from Google built on the Gemma 4 architecture that encodes text, images, audio, and video into a shared 768-dimensional vector space and uses Matryoshka Representation Learning so embeddings can be truncated to 512, 256, or 128 dimensions. The notes also list breaking changes: every mixture-of-experts model that computes router logits now returns them when output_router_logits=True, the &quot;paged|&quot; prefix for SDPA and flash attention implementations is deprecated in favor of continuous batching on the regular functions, and Owlv2ForObjectDetection.embed_image_query now selects the query box by objectness score. EmbeddingGemma2 itself is a Google model and is not a separate catalog entry; USASI has not tested these changes.</description>
    </item>
    <item>
      <title>vLLM 0.31.0 released with a preload command for faster engine restarts</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/vllm-0-31-0-released/</link>
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      <pubDate>Tue, 06 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>On October 5, 2026 the vLLM project published version 0.31.0 on GitHub. The release notes highlight a new vllm preload command that launches a weight-cache daemon to keep post-quantized weights in GPU memory across engine restarts, and experimental engine snapshots (vllm snapshot create/restore) that use CRIU to restore a fully initialized TP1 engine. Under security, the notes say per-request mm_processor_kwargs and media_io_kwargs are now rejected unless --trust-request-mm-kwargs is set. The release also lists breaking changes, including the removal of tokenizer_mode=&quot;slow&quot;, and performance work for DeepSeek-V4.1-Flash. USASI has not tested any of these changes.</description>
    </item>
    <item>
      <title>SGLang 0.5.21 adds a Decisions API and runtime prefill-decode role switching</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/sglang-0-5-21-released/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>The SGLang project published v0.5.21 on GitHub on October 2, 2026. The release notes highlight prefill-decode instances that can switch between prefill and decode without a restart, a Rust core for the prefix cache by default, a new Decisions API (/v1/decisions) that lets an LLM or VLM act as a low-latency classifier and scorer, and a Score API (/v1/score) that scores all candidates in one request. Under breaking changes, request-supplied chat_template values are rejected unless the server starts with --trust-request-chat-template, and deprecated endpoints, environment variables, and aliases, along with legacy radix cache implementations, were removed. The release also adds support for models including DeepSeek-V4.1 Flash and MiMo-V2.6. USASI has not tested these changes.</description>
    </item>
    <item>
      <title>llama.cpp server adds support for decision models through a /v1/systemone endpoint</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/llama-cpp-server-adds-decision-model-support/</link>
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      <pubDate>Mon, 05 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>On October 2, 2026 the ggml team announced on the Hugging Face blog that the llama.cpp server now supports decision models through a new /v1/systemone endpoint. Decision models score the options a caller supplies instead of generating text. The pull request that adds the endpoint (#29818) was merged into the llama.cpp repository the same day; it describes these models as wrappers around existing embedding-model architectures and adds a decision head and server handling for them. The announcement lists six supported models (Julia-1, Laya, Kev-4B, lev, OpenJev, and Clef), while the pull request itself covers five of them and lists Clef support as a planned follow-up.</description>
    </item>
    <item>
      <title>CoreWeave launches Forge, bringing Weights &amp; Biases Models into one AI development platform</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/coreweave-launches-forge-with-weights-and-biases/</link>
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      <pubDate>Thu, 01 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>CoreWeave announced CoreWeave Forge on September 30, 2026, a development platform that brings training, inference, evaluation, and agent development into one environment. Forge includes Weights &amp; Biases Models for tracking and comparing experiments. Weights &amp; Biases, which CoreWeave acquired in 2025, says W&amp;B software-as-a-service accounts now sign in through CoreWeave Forge and that self-hosted and dedicated deployments are unchanged. The open-source wandb client library remains available under the MIT License.</description>
    </item>
    <item>
      <title>llm-d 0.10.0 focuses on operational hardening and deprecates its own CUDA and AWS images</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/llm-d-0-10-0-released/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>The llm-d project published version 0.10.0 on GitHub on September 29, 2026. The release notes name operational hardening and production readiness as the main themes and describe a new image build arrangement: images from main and official releases go to ghcr.io and are signed publicly with cosign, while images built from open pull requests go to quay.io and are not signed. The notes deprecate the ghcr.io/llm-d/llm-d-cuda image in favor of docker.io/vllm/vllm-openai and the llm-d-aws image in favor of an AWS vLLM container, and say the llmd-fs-connector has been integrated into vLLM as the OffloadingConnector. The llm-d-workload-variant-autoscaler repository has been renamed llm-d-autoscaling. USASI has not tested this release.</description>
    </item>
    <item>
      <title>Hugging Face adds reinforcement learning environments to the Hub as tagged dataset repositories</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/hugging-face-adds-rl-environments-to-the-hub/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>Hugging Face announced RL Environments on the Hub on September 28, 2026. The post says there is no new repository type, registry, or sign-up: an environment is published as a dataset repository with the rl-environment tag plus a tag for each framework that can load its files, and the Hub offers an RL Environments filter. The post says four environment frameworks are registered as dataset libraries, each with its own tag: Harbor, Verifiers, OpenEnv, and NeMo Gym. The &quot;Use this dataset&quot; button provides a command to run an environment in a given framework, and frameworks run environments locally or on a supported cloud backend such as Hugging Face Jobs. The post says adding a tag does not start a job or sandbox. USASI has not tested this feature.</description>
    </item>
    <item>
      <title>Red Hat AI 3.5 becomes generally available with EvalHub and wider llm-d support</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/red-hat-ai-3-5-generally-available/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>Red Hat announced on September 9, 2026 that Red Hat AI 3.5 is generally available, including as part of Red Hat AI Factory with NVIDIA. The release makes EvalHub generally available for safety benchmarking and compliance reporting before deployment, shows Garak results on evaluated catalog models, integrates NeMo Guardrails to intercept malicious tool calls, and adds AutoRAG and observability features such as per-user token metering and MLflow agentic tracing. Red Hat says llm-d distributed inference now extends beyond OpenShift to third-party Kubernetes services, generally available on CoreWeave CKS and Microsoft Azure, with Amazon EKS in technology preview. USASI has not tested Red Hat AI 3.5.</description>
    </item>
    <item>
      <title>PyTorch 2.14.0 released with torch.switch, NVGEMM in Inductor, and a preview NCCL backend rewrite</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/pytorch-2-14-0-released/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>PyTorch 2.14.0 was published on GitHub on September 2, 2026. The release notes highlight NVGEMM, which brings CuTeDSL-generated CUTLASS kernels to Inductor, and torch.switch, which generalizes torch.cond to multi-way branching. Other highlights include declarative dynamic shapes via @dynamic_spec, experimental torch.compile support for complex-valued tensors, a preview of a rewritten NCCL backend ported from torchcomms, and native linear algebra on Apple Silicon. The notes also say Inductor now targets Rubin (sm_107). USASI has not tested this release.</description>
    </item>
    <item>
      <title>NVIDIA agrees to acquire Hugging Face; the deal has not yet closed</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/nvidia-agrees-to-acquire-hugging-face/</link>
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      <pubDate>Tue, 29 Sep 2026 12:00:00 GMT</pubDate>
      <category>acquisition</category>
      <description>NVIDIA entered into a definitive agreement to acquire Hugging Face, Inc. on September 2, 2026, and announced it the next day. NVIDIA's Form 8-K says the transaction is expected to close in the first half of 2027, subject to closing conditions including regulatory approvals, so Hugging Face is still listed as a privately held company with no parent organization. NVIDIA says the Hugging Face platform will stay open to models from other developers and will not require NVIDIA hardware.</description>
    </item>
    <item>
      <title>GitHub's Spec Kit reaches version 1.0.0</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/spec-kit-1-0-0-released/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>GitHub's Spec Kit project published version 1.0.0 on GitHub on August 21, 2026. The release notes give instructions for installing the specify CLI from the v1.0.0 tag and list the changes in the version, which are mostly fixes and updates to extensions and presets in the community catalog, including an update of the Security Review extension to v2.0.0 and a fix that rejects duplicate template entries in presets. The change list shows the version follows the 0.16.5 release. USASI has not tested Spec Kit 1.0.0.</description>
    </item>
    <item>
      <title>Sentence Transformers 6.0.0 adds MultiVectorEncoder for ColBERT-style late-interaction models</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/sentence-transformers-6-0-0-adds-multivectorencoder/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>Sentence Transformers version 6.0.0 was published on GitHub on August 18, 2026. The release notes describe it as a major release that introduces Multi-Vector Embedding models, also known as late-interaction or ColBERT-style models, as a fourth model type, MultiVectorEncoder, alongside SentenceTransformer, CrossEncoder, and SparseEncoder. The notes say PyLate and Stanford-NLP ColBERT checkpoints load directly into it, that the dependency floor moves to transformers v5, and that the release contains breaking changes covered in a migration guide. USASI has not tested this release.</description>
    </item>
    <item>
      <title>Agent Plugins 1.0.0 published as an open specification for packaging agent skills and MCP servers</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/agent-plugins-1-0-0-specification-published/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>governance</category>
      <description>On August 6, 2026 Vercel announced Agent Plugins 1.0.0, an open, vendor-neutral specification for packaging extensions for AI agents so that one plugin format works across compatible clients. A plugin is a directory with a plugin.json manifest and fixed locations for its components, with Agent Skills under skills/ and MCP server configuration in mcp.json. Vercel says it initiated the proposal, that representatives from AWS, Anysphere, GitHub, Microsoft, OpenAI, and Vercel refined it into version 1.0.0, and that the initial Technical Steering Committee includes core maintainers from AWS, Cursor, Microsoft, OpenAI, and Vercel. ChatGPT and Codex, Cursor, GitHub Copilot, Kiro, and VS Code are listed as supported at launch.</description>
    </item>
    <item>
      <title>PyTorch 2.13.0 released with FlexAttention on Apple Silicon and the torchcomms backend</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/pytorch-2-13-0-released/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>release</category>
      <description>PyTorch 2.13.0 was published on GitHub on July 8, 2026. The release notes highlight FlexAttention support on Apple Silicon (MPS) and a deterministic FlexAttention backward path on CUDA, a prototype CuTeDSL &quot;Native DSL&quot; backend for Inductor alongside Triton, and nn.LinearCrossEntropyLoss, which combines the final prediction and loss computation to reduce peak GPU memory. They also introduce torchcomms, a new communications backend for PyTorch Distributed, and Python 3.15 wheels on Linux, while dropping free-threaded CPython 3.13t binaries and Bazel build support. USASI has not tested this release.</description>
    </item>
    <item>
      <title>Vercel announces it is acquiring Better Auth; the authentication library stays MIT-licensed</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/vercel-acquires-better-auth/</link>
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      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>acquisition</category>
      <description>On July 7, 2026 Vercel announced that it is acquiring Better Auth, the company behind the open-source TypeScript authentication library of the same name. Vercel says the library remains free and open source under the MIT license and keeps its name, and that the team will continue to lead development with the same open contribution model and community governance. Better Auth's founder and core team are joining Vercel, and Vercel says the team will continue its Agent Auth work, which gives each agent its own identity, bringing agent identity to Vercel Connect and eve. The post does not say whether the deal has closed and does not disclose financial terms.</description>
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