All AI news

AICursor is launching two bots, Rollouts and Security Review, for Teams and Enterprise plans. Rollouts monitors each pull request as it deploys and reports change health per environment, while Security Review reports exploitable bugs on every pull request.

AISierra says its platform makes enterprise AI agents visible and editable, with journeys, policies, and actions viewable in Agent Studio and testable through Simulations and Experiments before rollout. Customers can export agent logic in a portable structured format, access conversation logs and performance data through export APIs, and manage the agent's code in a Git repository. Sierra agents also connect to existing systems through MCP, REST, GraphQL, or custom integrations.

AIComfyUI's update makes the MiniMax H3 video VAE encode up to about 2.2x faster and decode 1.4-2.7x faster, cutting a 1344x768, 129-frame round trip on an RTX 5090 from 24.3 to 12.7 seconds. The gains come from a fused encoder kernel enabled by default, fp16 accumulation support in a custom convolution, and an int8 decoder, and the source says the changes are visually lossless to the eye. Users need ComfyUI v0.36.0 or above, and the int8 VAE file is a drop-in replacement for the standard one.

AICognition announced its expansion into Latin America at MASP in São Paulo, starting with a local team to help companies build more of their software in the region. Itaú reports more than 75% of its technology teams use Devin, with legacy .NET services migrated to Java 6x faster and about 70% of security vulnerabilities resolved automatically. Nubank says Devin cut a multi-million-line monolith migration from years to weeks, at over 20x lower cost.

AILovable now offers Opus 5.5, which it says matches Opus 5's results while finishing builds in a third to half fewer steps. Internal benchmarks showed Opus 5.5 scoring 4 to 6% ahead of Opus 5 on verification discipline, with step reductions of 26% to 57% and input token reductions of 21% to 59% across tasks.

AILovable joined AWS, Google Cloud, Databricks, Salesforce, and other firms as a founding member of the Blueprint Alliance, a coalition developing an open reference architecture for securing and governing enterprise AI agents. The blueprint covers registering agents as identities with accountable owners, scoping their access to tasks, enforcing policies through gateways, and responding to incidents by revoking tokens or quarantining agents.

AIBlack Forest Labs released FLUX 3 Action, an open-weights 7B world action model that outputs robot joint commands from camera frames, robot state, and a text instruction. On the RoboLab-120 benchmark it reports 42.92% task success, ahead of Cosmos3-Nano-Policy at 36.8% and π0.5 at 28.0%. The model is fine-tuned on DROID, is distributed under the FLUX Kommunity License v.1.0, and runs in about 32 GB of GPU memory in bfloat16.

Why it matters: The model card gives a benchmark comparison, parameter counts, and an action contract, so readers can judge how it compares with existing robot policies.

AIBlack Forest Labs has published FLUX 3 Action SO-101 on Hugging Face as an open-weights 7B world action model. It takes two camera frames, the robot state, and a text instruction, then returns the next 42 actions with predicted video frames, with 32 executed at 30 Hz before replanning. The card also provides a rank-32 LoRA fine-tuning recipe for user datasets and states that the application must enforce joint velocity, force, and workspace limits.

AIBlack Forest Labs has released flux-3-action-base, an open-weights 7B world action model that takes camera frames, robot state, and a text instruction to output the next action chunk. The release is an adaptation component rather than a complete robot policy, and new embodiments require their own action heads. The source says the weights are paired with shared video VAE and Qwen3-VL-4B-Instruct text encoders and is governed by the FLUX Kommunity License v.1.0.

Why it matters: The source separates the adaptation base from full robot policies and states the shared encoders and new-embodiment requirements, which clarifies what developers must still build for their robots.

AIMETR's preliminary evaluation concludes that Claude Opus 5.5 likely gives slightly higher AI R&D productivity uplift than Fable 5.1 but is unlikely to fully automate AI R&D. The evaluation used five capability tasks over 10 business days of API access, and METR says Anthropic reviewed and edited the summary before sign-off.

Why it matters: The report separates two claims about AI R&D acceleration and discloses that Anthropic reviewed the summary, which helps readers weigh its independence and evidence.

AIGoogle made the Gemini 3.8 Flash TTS and Gemini 3.8 Flash-Lite TTS models generally available, along with the Gemini API Voices endpoint. Flash TTS is positioned for studio-grade voice fidelity and long-form multi-turn stability, while Flash-Lite TTS targets high-throughput, real-time voice agents and replaces gemini-3.1-flash-tts-preview. The update adds voice design, voice replication with consent verification, and access to 150+ prebuilt and custom voices.

AIAnthropic has launched Claude Opus 5.5, the first model in its new Claude 5.5 family. The company says it performs at the level of Claude Fable 5.1 on most work and costs 40% less to run than Opus 5.

Why it matters: The release note gives a direct comparison to Claude Fable 5.1 and a 40% running cost reduction versus Opus 5, which helps readers weigh the tradeoff.

AISpaceXAI says its combined support team handled a 175% rise in tickets without hiring, crediting Grok Bot, which it says would otherwise have required about 200 additional staff. The company reports resolving tickets for $0.20 to $0.30 each, versus the $1 to $4 per resolution it attributes to traditional AI support tools. Grok Bot is also reported to resolve 99% of refund requests without human intervention.

AIvllm-metal ports vLLM's scheduler, paged KV cache, and OpenAI-compatible server to Apple Silicon, with MLX and Metal handling execution. The v0.28.0 release added batched MTP, GGUF and hybrid-model support, and faster prefill on M5, and v0.29.0 is installable through Homebrew.

Why it matters: The post explains how vllm-metal packs requests and pages KV cache on Apple Silicon, with benchmarks showing where concurrent serving gains and tradeoffs appear.

AIAmp runners can now create Git worktrees from the directory picker, with each new worktree placed as a sibling folder on a new branch off the current HEAD while uncommitted changes stay in the original checkout. Runners can also opt in with --amp-env to inject Secrets & Env Vars configured on ampcode.com into thread shell commands, MCP servers, and plugins, with changes applied to the next thread without a restart.

AIGoogle AI subscribers now get premium Colab benefits, including priority access to faster accelerators and more powerful machines. Google AI Ultra subscribers also get uninterrupted background execution and Premium GPU access for long training runs. The benefits roll out over the next few weeks in Colab-supported countries, and existing Colab subscriptions are unchanged.

AITogether AI's canary rollouts shift production traffic between two model deployments on the same endpoint in staged percentages, with optional metric gates between steps. Operators can choose canary, blue-green, or rolling strategies, and a rollout starts only when explicitly launched; it can be paused, canceled, or reversed. The platform scales the target before moving traffic and waits for routing to converge before draining the source.

AIWaymo is launching a transit rewards program in the San Francisco Bay Area that issues $2.85 in Waymo Cash when riders take a Waymo trip and public transit within 2 hours, using a linked Visa card. The program covers all 27 Bay Area transit agencies that accept contactless Visa tap-to-pay, and employees get access first before a public rollout in the coming weeks. Waymo will also lease 40 dedicated Caltrain station parking spaces for staged vehicles.

AIFireworks AI launched the Specialized Intelligence Index, which compares open, closed, and specialized models on domain benchmarks in seven initial areas: healthcare, legal, cybersecurity, finance, customer support, productivity, and software.

AIAmazon and Stanford University have launched the Stanford and Amazon Research Initiative, a formal framework for research in AI, energy, and healthcare. More than 10 Amazon teams already fund active Stanford research and PhD fellowships, spanning humanoid robotics, post-quantum cryptography, causal measurement science, and AI-driven radiology. The initiative will support joint projects between Stanford faculty and Amazon scientists, PhD fellowships, and symposia and workshops.

AIXiaomi MiMo released MiMo-V2.6-Distill-Qwen-9B, a 9B agentic model made by supervised fine-tuning Qwen3.5-9B on MiMo-generated data, as an open starting point for agentic reinforcement learning research. It scored 61.1 on SWE Verified, versus 60.0 for Qwen3.5-9B, and 44.6 on SWE Pro, versus 32.0. The checkpoint is served with SGLang and a MiMo chat template, and its SFT data totals 77.4B tokens.

AIApple has released LensVLM-9B on Hugging Face, a 9B-parameter Vision Language Model that scans compressed images of text and selectively expands relevant pages to their uncompressed form. The repository provides a demo script and supports compression settings of 5x, 10x, and 15x. Model files are under the Apple Machine Learning Research Model License, and the accompanying source code is distributed separately under the Apple Sample Code License.

AIAmazon Science describes three papers on AI for antibody discovery: MochiBind ranks antibody binding strength from sequence alone, CA-MAP predicts developability properties using batch-aware context, and an agent-guided pipeline designed nanobody binders against a novel cancer target. In the pipeline, 116 candidates survived lab screening, and 46 were identified as strong binders, which are being used to train the next design cycle.

Why it matters: The source reports the method, benchmark setup, and experimental validation in a single design workflow, showing how predictors, agents, and lab screening connect in antibody discovery.

AIMeta has open-sourced Rebalancer, an assignment-problem solver it has used for over nine years to allocate resources across its infrastructure. The library separates problem specification, in-memory storage, solving, and debugging, and translates problems into expression graphs solved via local search or mixed integer programs using FICO Xpress, Gurobi, or the open-source HiGHS solver.

AIXiaomi released MiMo-V2.6-Flash-RL, an efficiency-balanced checkpoint in its MiMo-V2.6 series, on Hugging Face. The model is a sparse MoE with 309B total and 15B activated parameters, supports text, image, video, and audio input, and offers a 1M-token context. The technical report says it was trained with a single mixed reinforcement learning run across coding, agent, visual, and cybersecurity tasks.

Why it matters: The report pairs its benchmark tables with the RL training method, which helps readers judge how the checkpoint's scores relate to its training approach.

AIXiaomi MiMo released MiMo-V2.6-Pro-RL on Hugging Face, a sparse MoE model with 1.02T total and 42B activated parameters and a 1M-token context. The technical report says it accepts text, image, video, and audio, and was trained with a single mixed reinforcement learning run across coding, agent, visual, and cybersecurity tasks.

Why it matters: The report pairs a 1.02T-parameter MoE model with an RL-based self-improvement method, useful for judging how reinforcement learning is scaled in frontier open models.

AIMicrosoft Research published RetroChimera, a retrosynthesis framework that combines the R-SMILES 2 Transformer model and the NeuralLoc graph neural network through learned ensembling to propose synthesis routes for small molecules. In blind tests, PhD-level chemists preferred its individual reaction predictions over those from preceding models and recorded literature reactions. The implementation and weights are open-sourced for researchers developing new medicinal molecules and materials.

AIFireworks AI reports that an oracle router choosing among 18 models per DeepSWE task reaches 97.6% at $1.88 per task, versus 74.1% at $6.52 for GPT-6 Astra alone. The oracle is hindsight-based, so the authors say a production router must predict the best model before the task starts, which is the harder problem.

AIxAI released Grok 4.7, which it calls its most capable model for coding and knowledge work, built on a larger base model than Grok 4.6 and trained with a longer reinforcement learning run. It is priced from $2 per million input tokens and $6 per million output tokens, the same as Grok 4.6, and is available in Cursor, Grok Build, and the Grok API. xAI reports gains on CursorBench 4.0 (46.3%) and AA Briefcase v1.1 (1,657) over Grok 4.6, and says it posts the strongest safety results it has tested on refusals and jailbreak resistance.

Why it matters: The release pairs a new base model with benchmark tables against named rivals and pricing, letting readers compare its coding and office-work gains against Grok 4.6 and frontier models.

AIvLLM achieved 5000 total token throughput per GPU in high-throughput PD serving of Qwen3.8-2.4T on a GB300 NVL72 cluster under an 8K/1K workload. The low-latency scenario reached 180 generated tokens per user, with both results shown on the Pareto frontier. The post also provides srt-slurm recipes and explains the tuning process used to create them.

AIQwen has open-sourced Qwen-Image-2.1, a unified text-to-image generation and image editing model with 7B visual generation parameters. The Hugging Face page for Qwen-Image-2.1-PE-I2I is a fine-tuned Qwen3.5-VL 9B prompt rewriter that turns vague editing instructions and input images into precise editing prompts, supporting up to 10 reference images.

Why it matters: The model card documents usage with transformers and diffusers, letting readers see how the editing prompt rewriter connects to the generation pipeline.

AIQwen has open-sourced Qwen-Image-2.1, a unified text-to-image generation and image editing model with a 7B-parameter visual generation component. The release also includes Qwen-Image-2.1-PE-T2I, a fine-tuned Qwen3.5-VL 9B model that rewrites brief image requests in any language into detailed English prompts with a recommended aspect ratio.

Why it matters: The release pairs a 7B visual generation component with a separate prompt rewriting model, showing how a brief image request becomes a detailed English prompt before rendering.

AIGitHub's latest podcast episode examines five common AI hot takes, including whether developers must still read AI-generated code. It argues review effort should match risk, and that Skills and MCP solve different problems. It also says retrieval-augmented generation (RAG) remains useful and works alongside agents, skills, and MCP.

AIGoogle's AI & Economy Research Program has added Nobel laureate Philippe Aghion as an Academic Advisor and Ajay Agrawal as a Visiting Fellow, with Anu Madgavkar and Daniel Rock named Directors. The program covers the future of work, productivity and growth, global technology diffusion, and AI's impact on scientific discovery, and builds on the recently launched AI & Economy ATLAS v1.0.

AIGoogle's Envisioning Studio, with Google Labs, co-developed custom Google Flow tools with designers Jane Wade and Sergio Hudson ahead of New York Fashion Week. Wade's Styling Suite let her style runway looks on digital models before producing physical samples, while Hudson's Runway Visualization helped him stage his show within a tight budget. The source says the tools are built with natural language and no coding experience.

AILovable has acquired Sutro, a company that built a language, compiler, and backend platform making application behavior and rules explicit. Sutro founder Tomas Halgas and three engineers, Max Gfeller, Tony Zhan, and Hirad Arshadi, are joining Lovable, with Halgas leading its technical evangelism.

AILiquid AI released LFM2.5-VL-3B-DSpark, a speculative-decoding draft model for its LFM2.5-VL-3B vision-language model. The source reports decoding up to 2.66× faster on a single H100 with SGLang, up to 3.13× on Apple M5 Max with MLX-VLM, and up to 2.14× on Apple M3 Ultra with llama.cpp, with output unchanged under greedy decoding.

AIAnthropic is partnering with Accenture, through its specialist AI business Faculty, on independent evaluation of frontier models, including red-teaming, alignment assessments, and safeguard testing. Anthropic and Accenture each expect to invest at least $1 billion in this capacity over five years. The source says embedded evaluators would have employee-comparable access, but standards for access and reporting, and a settled funding system, do not yet exist.

Why it matters: The source ties a new evaluation arrangement to an unresolved question of who funds and sets standards for independent AI evaluators, which is useful context for governance debates.

AIGoogle is restricting access to its Gemini 2.5 models to users who have actively used them in the past, to keep performance reliable. The models are not deprecated and remain available through the API until further notice. For new projects, Google recommends its latest models, 3.5 Flash-Lite or 3.8 Flash.

AIA global fintech scaled its AI coding agent traffic by running the GLM-5.2 model on Together AI's Dedicated Model Inference, after capacity planning failed to keep pace with unpredictable engineering-hour bursts. The customer gained self-service endpoint provisioning, a metrics API for diagnosing queuing, and live configuration changes that shipped with zero downtime. The setup runs dozens of B200 GPUs at 256K context across multiple replicas.