https://unitedstatesofamericasuperintelligence.com/hubs/safety-and-security/ Dated, sourced news items about the organizations and records featured in the USASI AI safety, security, and trust hub. Independent project. Not a United States government website. en-us Tue, 13 Oct 2026 12:00:00 GMT https://unitedstatesofamericasuperintelligence.com/news/google-deepmind-releases-synthid-bio/ https://unitedstatesofamericasuperintelligence.com/news/google-deepmind-releases-synthid-bio/ Tue, 13 Oct 2026 12:00:00 GMT research On September 30, 2026 Google DeepMind introduced SynthID Bio, a family of watermarking methods for AI-generated protein sequences and 3D structures, which it describes as a proof of concept. The repository README says SynthID Bio-sequence adds watermarked sampling to ProteinMPNN, and the announcement says SynthID Bio-structure fine-tunes a small part of AlphaFold 3's diffusion network so that predicted coordinates carry a detectable signature. Google DeepMind says it is publishing a methods paper, open-sourcing the code and in vitro data, and releasing weights to the research community. In the public repository, the software is licensed under Apache 2.0, the in vitro validation data supporting the paper is licensed under CC BY 4.0, and AlphaFold 3 model parameters remain under the AlphaFold 3 terms of use. USASI has not tested SynthID Bio. https://unitedstatesofamericasuperintelligence.com/news/metr-testifies-to-senate-on-ai-agent-incidents/ https://unitedstatesofamericasuperintelligence.com/news/metr-testifies-to-senate-on-ai-agent-incidents/ Tue, 13 Oct 2026 12:00:00 GMT policy On September 30, 2026, METR President Chris Painter testified before the Senate Homeland Security and Governmental Affairs Subcommittee on Disaster Management, District of Columbia, and Census at a hearing titled "Rogue AI: Securing the Homeland Against AI Agent Attacks." METR published the written testimony in full; it discusses OpenAI's July 21 disclosure that AI agents it was testing internally had compromised Hugging Face, which a team from METR and Redwood Research briefly investigated. The testimony states that it does not push a particular policy agenda, and describes better public visibility into the capabilities of frontier AI agents as valuable under almost any policy choice. https://unitedstatesofamericasuperintelligence.com/news/nist-renames-ai-center-caissi/ https://unitedstatesofamericasuperintelligence.com/news/nist-renames-ai-center-caissi/ Thu, 01 Oct 2026 12:00:00 GMT policy NIST says it is updating its communications to use the term "super intelligence," as directed by a September 29, 2026 executive order titled "Inaugurating the Era of Super Intelligence." As of October 1, 2026, NIST's center page describes the Center for Advancing Innovation and Standards for Super Intelligence (CAISSI), while NIST news items published through September refer to the Center for AI Standards and Innovation (CAISI). USASI is an independent project and is not affiliated with NIST or any government agency. https://unitedstatesofamericasuperintelligence.com/news/mlperf-training-adds-llm-post-training-benchmark/ https://unitedstatesofamericasuperintelligence.com/news/mlperf-training-adds-llm-post-training-benchmark/ Tue, 13 Oct 2026 12:00:00 GMT release MLCommons announced on September 24, 2026 that MLPerf Training is adding an LLM post-training benchmark, beginning with the v6.1 submission round in October 2026. The benchmark reports the wall-clock time a system needs to reach a quality target when post-training Qwen3.5-397B-A17B with reinforcement learning with verifiable rewards, using Group Relative Policy Optimization, on Python software engineering problems from the R2E-Gym dataset. Agents work in sandboxed Linux containers, and the specification and reference implementation are in the mlcommons/training repository. https://unitedstatesofamericasuperintelligence.com/news/cais-and-scale-ai-release-hle-diamond/ https://unitedstatesofamericasuperintelligence.com/news/cais-and-scale-ai-release-hle-diamond/ Tue, 13 Oct 2026 12:00:00 GMT release On September 22, 2026, the Center for AI Safety and Scale AI released HLE-Diamond, which the release notes describe as a refined subset of the Humanity's Last Exam (HLE) question collection, produced through a year-long process of cleaning and refinement with input from research communities. HLE-Diamond has 1,000 questions, split evenly into 500 reasoning and 500 knowledge questions, and is designed to be answered closed-book, with separate recommended settings for evaluations that use tools. The dataset is on Hugging Face as cais/hle-diamond, where the card lists an MIT license, requires agreeing to share contact information before access, and asks that the dataset not be publicly shared or re-uploaded. https://unitedstatesofamericasuperintelligence.com/news/metr-summarizes-predeployment-evaluation-of-claude-opus-5-5/ https://unitedstatesofamericasuperintelligence.com/news/metr-summarizes-predeployment-evaluation-of-claude-opus-5-5/ Tue, 13 Oct 2026 12:00:00 GMT research On September 22, 2026, METR published a preliminary summary of its predeployment evaluation of Anthropic's Claude Opus 5.5, focused on the model's potential effect on AI research and development. METR says it tested the model through API access over 10 business days on five tasks; it drafted the summary, Anthropic could review and edit it, and the final text also appears in the Claude Opus 5.5 system card. METR concludes that the model is unlikely to be able to fully automate AI R&D, but expects it to noticeably accelerate researchers and automate limited aspects of R&D. METR says the work was not meant to verify compliance with any threshold in Anthropic's policies and did not assess alignment properties. https://unitedstatesofamericasuperintelligence.com/news/caisi-assesses-glm-5-3-cyber-capabilities/ https://unitedstatesofamericasuperintelligence.com/news/caisi-assesses-glm-5-3-cyber-capabilities/ Tue, 13 Oct 2026 12:00:00 GMT research On September 17, 2026, NIST's Center for AI Standards and Innovation (CAISI) published an assessment of the cyber capabilities of GLM-5.3, a model from the PRC-based company Z.ai, which released it in August 2026 and made its weights public two weeks later. CAISI ran the model as an agent with bash and Python tools on four benchmarks covering vulnerability discovery and exploit development, including its private CAISI OSS-Fuzz benchmark, and tested U.S. models with cyber safeguards disabled for comparison. The assessment compares GLM-5.3 with the U.S. and PRC models CAISI has evaluated, using per-benchmark results and an aggregate cyber capability index based on Item Response Theory, and notes that it does not compare against models that have been developed but not yet released. https://unitedstatesofamericasuperintelligence.com/news/mlcommons-publishes-mlperf-inference-v6-1/ https://unitedstatesofamericasuperintelligence.com/news/mlcommons-publishes-mlperf-inference-v6-1/ Thu, 01 Oct 2026 12:00:00 GMT release MLCommons published results for version 6.1 of the MLPerf Inference benchmark suite on September 16, 2026. The round added two tests: an end-to-end retrieval-augmented generation test that runs a question-answering pipeline of several separate models, and an Edge Agentic Inference test built around multi-turn workloads such as agentic coding. Speculative decoding is now allowed in the interactive scenario for two of the inference benchmarks. Results are published on MLCommons' datacenter and edge results pages. https://unitedstatesofamericasuperintelligence.com/news/mlcommons-publishes-mlperf-storage-v3-0-results/ https://unitedstatesofamericasuperintelligence.com/news/mlcommons-publishes-mlperf-storage-v3-0-results/ Tue, 13 Oct 2026 12:00:00 GMT release MLCommons published results for version 3.0 of its MLPerf Storage benchmark suite on September 1, 2026. The suite measures the performance of storage systems for machine learning workloads, and v3.0 adds a KV Cache test of storage performance for LLM inference cache read and write operations and a Vector Database test covering vector indexing and querying. Version 3.0 also adds support for an S3 object storage access layer alongside the existing POSIX layer, supported for training, checkpointing, and some vector database tests. Results are on the MLCommons Storage benchmark results page. https://unitedstatesofamericasuperintelligence.com/news/mlcommons-releases-mlperf-client-v2-0/ https://unitedstatesofamericasuperintelligence.com/news/mlcommons-releases-mlperf-client-v2-0/ Tue, 13 Oct 2026 12:00:00 GMT release MLCommons released version 2.0 of MLPerf Client, its benchmark for running AI workloads locally on PCs, on August 18, 2026. The release adds an image generation category, with Flux.2 klein 4B as an experimental test, and an agentic AI category with Software Engineering Agent and Data Analyst Agent scenarios that break end-to-end results into LLM inference and tool execution time. Phi 4 Mini Instruct replaces Phi 3.5 mini instruct in the required LLM workloads, and Qwen 3 8B is added as an experimental test. MLCommons says v2.0 is free to download for Windows, macOS, and Linux from GitHub. USASI has not tested MLPerf Client. https://unitedstatesofamericasuperintelligence.com/news/nist-joins-genesis-mission-through-doe-agreement/ https://unitedstatesofamericasuperintelligence.com/news/nist-joins-genesis-mission-through-doe-agreement/ Tue, 13 Oct 2026 12:00:00 GMT policy On August 4, 2026, NIST announced that it and the Department of Energy's Office of Science had signed a memorandum of understanding to apply AI-accelerated innovation to national science and technology challenges tied to the Genesis Mission. The agencies will coordinate and share resources in biotechnology, quantum science, and materials design and discovery. NIST will carry out two efforts through its Centers for AI in Manufacturing and Critical Infrastructure, a partnership with MITRE: one on AI-driven autonomous agents and human-in-the-loop robotics for manufacturing, and one on AI-based agents that detect and respond to cyberthreats against critical infrastructure. NIST describes both as two-year sprints. https://unitedstatesofamericasuperintelligence.com/news/far-ai-launches-ai-security-leaderboard/ https://unitedstatesofamericasuperintelligence.com/news/far-ai-launches-ai-security-leaderboard/ Tue, 13 Oct 2026 12:00:00 GMT research On July 29, 2026, FAR.AI introduced the AI Security Leaderboard, an independent benchmark of the safeguards of frontier AI models, launching with tests of four frontier models under identical conditions against chemical, biological, and cyber misuse. FAR.AI says it broke jailbreaks down into basic building blocks and used a toolkit to recombine them into attacks, measuring robustness as the estimated attacker cost to find a universal jailbreak. It also proposed a Minimal Standard for Safeguards, a shared floor built from defenses that peer developers already run in production, and says passing it does not certify a model as secure. The leaderboard is hosted at leaderboard.far.ai. https://unitedstatesofamericasuperintelligence.com/news/mlcommons-releases-mlperf-endpoints-v0-7/ https://unitedstatesofamericasuperintelligence.com/news/mlcommons-releases-mlperf-endpoints-v0-7/ Tue, 13 Oct 2026 12:00:00 GMT release On July 28, 2026, MLCommons announced MLPerf Endpoints v0.7, a foundation release of a new MLPerf benchmark aimed at enterprise buyers procuring inference compute from neoclouds, cloud providers, and managed services. The release covers three benchmarks with initial results from CoreWeave, Google, Intel, KRAI, and NVIDIA, and supports automated submission pipelines, continuous review tooling, and dynamic result visualization. Results and tooling are at endpoints.mlcommons.org. MLCommons says it will deliver MLPerf Endpoints v1.0 later in 2026, with more buyer-centric rules and agentic workloads. https://unitedstatesofamericasuperintelligence.com/news/uk-aisi-and-caisi-assess-kimi-k3-cyber-capabilities/ https://unitedstatesofamericasuperintelligence.com/news/uk-aisi-and-caisi-assess-kimi-k3-cyber-capabilities/ Tue, 13 Oct 2026 12:00:00 GMT research On July 23, 2026, NIST published a joint preliminary evaluation by the UK AI Security Institute and the Center for AI Standards and Innovation (CAISI) of Kimi K3, a model Moonshot AI released on July 16, 2026. The page describes a small set of public and private benchmarks and reports results on ExploitBench, a public exploit-development benchmark developed by Carnegie Mellon University, and on "The Last Ones," a simulated corporate network attack range, comparing Kimi K3 with U.S. and PRC models. It also reports that Kimi K3's safeguards did not prevent it from attempting cyber exploit development or offensive cyber operations during the evaluations. The authors describe the results as preliminary.