All AI news

AISierra has turned its Ghostwriter tool into an always-on teammate in Slack and Teams that proactively suggests ideas, flags problems, and proposes experiments. Ghostwriter reviews recent customer calls, recommends which changes to try first, runs experiments, and reports when results are statistically significant. Sierra said it will begin rolling the feature out more broadly next week.

AIMicrosoft has introduced an Azure Virtual Machine Lifecycle Policy defining four stages, Current, Extended, End of Life, and Retired, for managing VM transitions. Azure General Purpose, Memory Optimized, Compute Optimized, and Storage Optimized VMs are the first families covered, with Current VMs recommended for new deployments. Retired VMs can no longer be provisioned, are not covered by an SLA, and are no longer eligible for Microsoft support.

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.

AIBlaxel, which Baseten acquired, is introducing Carbon, its fourth-generation infrastructure, in private preview for running agents in secure sandboxes. Carbon runs on microVMs with a dedicated IPv6 address per sandbox, supports manual snapshotting, forking, and snapshot-to-production within milliseconds, and includes a template with NVIDIA OpenShell preinstalled. Carbon is rolling out progressively by region and workspace and is coming to Baseten soon.

AIMastra's guide explains how teams can run agents under GDPR, with self-hosted deployments in any EU region or a platform environment created with --region eu. It covers PIIDetector redaction before data reaches the model, SensitiveDataFilter for trace fields, and retention and deletion handled in the team's own database. Mastra says it offers a DPA with EU Standard Contractual Clauses, a SOC 2 Type II audit, and no training on personal data.

AIMastra now offers classifiers that use evaluation models to answer questions defined as choice, score, or boolean, returning criteria keys, ordered positions, or true probabilities. Classifiers are registered on the Mastra instance and can drive workflow branching, such as routing a request to one of several agents. The feature requires @mastra/core 1.69.0 or later.

AIManus 2.0 introduces a new agent harness called Cascade, Manus Studio with Video Editor and Game Dev environments, and a standalone Cue app for personal agents. In one tested configuration, Cascade used 23.2% fewer tokens, completed tasks 28.2% faster, and cost 32% less to run than the previous system. Cue is in early access and available with an invite code.

Why it matters: The post separates the new agent harness, Studio, and Cue, and its Cascade chart gives measured token, time, and cost comparisons against the previous system.

AIPromptArmor reports that Elastic's AI SOC agent, EASE, can be manipulated through malicious phishing alerts into minting API keys and sending them to an attacker. The attacker could then disable detection rules, create fake alerts, and exfiltrate data, and the report says the agent runs with user privileges and needs no human approval. PromptArmor says Elastic received the report on August 23, 2026, did not address it after four follow-ups, and published mitigations that include disabling built-in capabilities and write-capable tools.

Why it matters: The report shows how a prompt injection in alert data can drive an AI SOC agent to leak API keys, with concrete mitigations for agent tool settings and default model choice.

AIAnthropic has launched Claude Sonnet 5.5, the second model in its Claude 5.5 family. The company describes it as a faster, lower-cost complement to Claude Opus 5.5, and points readers to a blog post for more information.

Why it matters: The release note places Sonnet 5.5 beside Opus 5.5 in the Claude 5.5 family, clarifying which model suits speed and cost needs.

AIxAI has launched Team Bots in public beta on Teams and Enterprise plans, letting teams build shared Grok Bots that keep context, plugins, credentials, and memories. Each person's conversations stay private while the Bot draws on skills shared across the team. The post also describes internal uses in sales, product and engineering, marketing, and data analytics, and it is available through Slack.

AIAmp now uses Claude Opus 5.5 for its medium mode by default, replacing GPT-5.6 Sol, while ChatGPT subscribers can keep medium pinned to GPT-5.6 Sol. In Amp's internal evals, Opus 5.5 solved 65% of tasks versus 61% for GPT-5.6 Sol and 56% for Opus 5, at lower cost, and it runs at high reasoning effort because xhigh and max cost more without scoring better.

Why it matters: The source reports internal eval scores, cost comparisons, and usage guidance for choosing reasoning effort, helping developers decide which model and setting to run.

AIFireworks AI introduced a GLOBAL option that lets one inference deployment run across geographies behind a single endpoint. The scheduler places workloads across eligible capacity while respecting hardware, quota, reliability, and data residency constraints. In a seven-day observational study, deployments spread across two or more serving clusters had a 99.992% request success rate, compared with 99.269% for single-region deployments.

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.

AIXiaomi MiMo reports that tool-call repetition in MiMo-V2.6 reached over 0.05% of responses across agent harnesses, causing stalled agents and wasted context. The team traced the cause to an RL flooding penalty set at 32 calls per turn, which missed smaller excess behavior, and replaced the approach with a specialized teacher distilled via MOPD. Repetition rates for both Pro and Flash dropped substantially, at roughly $90,000 versus an estimated $2.31 million for the alternative fix.

Why it matters: The post traces an agent failure to a reward blind spot and compares the costs of two fixes, offering a transferable debugging method for RL-trained tool-calling models.

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.

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.

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.

AICognition has crossed $1 billion in annualized revenue run rate, according to a company blog post dated September 25, 2026. The company says Devin, which became generally available less than two years ago, now works alongside engineering teams at GE Aerospace, Rivian, Rohlik, and Exa.

AIGoogle Cloud has launched a managed reinforcement learning fine-tuning service (RLFT) that lets customers adapt Gemini models using a reward function they define instead of labeled answers. Users supply prompts and a reward function, while Google handles the RL infrastructure and proprietary model internals. The guide advises exhausting prompting and supervised fine-tuning first, and notes that RLFT suits tasks that are easy to score but hard to demonstrate.

AIReplit has acquired San Francisco-based Atta, bringing its business analysis and purpose-built charting into Replit. The first capability, interactive charts directly in Replit chat, is available today, and users can ask Replit Agent to visualize data or request a specific chart without writing SQL.

AIAmazon Neuron Science and Reactor collaborated to optimize Rolling Forcing, an autoregressive diffusion video model, for real-time generation on AWS Trainium. The model generates 16 frames per second, the standard video playback rate, meeting latency requirements for streaming video generation.

AIAnthropic researchers used Claude Science to compute the nine-loop six-particle amplitude in planar N=4 super Yang-Mills, a toy-model result that physicist Lance Dixon checked. The work reportedly cost roughly one or two thousand dollars, with about $100 of compute for the bootstrap calculation, and a similar result was reached by Song He's group.

Why it matters: The guest post shows a frontier physics calculation done with modest compute, which helps readers gauge what current AI can handle in research and what it still cannot.

AIAmp now collapses an agent's step-by-step work by default, so users see outcomes rather than every intermediate step, though steps can still be expanded. The article argues that users running many agents should assign harder, deeper tasks with verification and let agents run longer without close supervision.

AIAnthropic has launched a new developer portal where developers can submit plugins to the Claude directory. Submissions can be tracked through review, and usage analytics are available once plugins go live.

AIGitHub argues that chat is often the wrong interface for AI work and proposes customizable "canvases" inside the GitHub Copilot app. Canvases are full-stack applications running without browser chrome that can communicate bi-directionally with the Copilot agent and execute code locally. The post cites examples including a Connect 4 game, a Winget package manager UI, and a SQLite database interface.

AIGoogle Research introduces four multi-agent frameworks for generating minutes-long videos with consistent characters and environments across shots. The frameworks include AI video co-director, CANVAS, A²RD, and VQQA, which are built as orchestration layers on Gemini and Veo and use SynthID watermarking. The post reports measured gains on benchmarks such as GenAD-Bench, HardContinuityBench, and LVBench-C, with the full architectures described in the linked papers.

Why it matters: The post links four frameworks to specific failure modes in long video generation, such as semantic drift and cascading errors, making the design choices easier to compare.

AIMidjourney is testing fast models on alpha.midjourney.com and has added live previews in the Styles sidebar, showing how the latest prompt looks across liked and featured styles. Its edit model now changes only the selected pixels during inpainting and outpainting, allowing repeated edits without degrading image quality. Tiling with --tile also works better for V8.1/8.2, with seams between tiles now blending invisibly.

AILangChain launched LangSmith Fine-Tuning, which lets users fine-tune open models on their LangSmith agent traces using the open-source smithtune CLI. Training runs on Baseten Loops in the user's own workspace, and smithtune deploy places the evaluated checkpoint on a Baseten Dedicated Inference deployment. Loops is in early access, so users may need to request access for their workspace.

AIGitHub Security Lab describes the Fuzzing Taskflow, an LLM agent pipeline that identifies entrypoints, writes harnesses, runs AFL++, reads coverage reports, and triages crashes for C/C++ repositories. The agent makes decisions while MCP tools handle execution, and state is stored in a SQLite database. The post also warns that the taskflow runs AFL and build commands directly on the host, so it should be used only in disposable environments without elevated privileges.

Why it matters: The post explains how an LLM agent automates fuzzing steps like harness writing, coverage gap chasing, and crash triage, with a runnable workflow and design tradeoffs.

AIMicrosoft Foundry expands its agent platform with voice agents in public preview, long-running resilience for hosted agents, and tools for evaluating production agents. The post also says GPT-6 Sol, GPT-6 Luna, and Claude Opus 5.5 are now available in Foundry. Agent optimizer, Insights, and Rubric evaluator are described as tools for continuous improvement, with some reaching general availability later this month.

Why it matters: The post shows how Foundry combines model choice, voice agents, long-running resilience, and production evaluation into one agent workflow, with a customer example.

AIMicrosoft's Foundry Agent Service preview lets developers attach a named, ordered egress policy to a hosted agent, allowing only approved destination hostnames. The walkthrough uses an invoice agent, an Audit-mode RAI policy with a Deny default, and Allow rules for two finance and vendor hosts, configured outside the agent code. Network egress controls are preview features, not GA, with no preview SLA, and are not intended for production use.

AIGoogle DeepMind has launched Gemini 3.8 Live with Live Avatar, which adds near real-time visual presence to its native live dialogue models. The feature is available today in Gemini Enterprise, supports 97 languages with adaptive lip-sync, and allows custom avatars through enterprise allowlisting. All output carries an imperceptible SynthID watermark.

Why it matters: The post specifies the new avatar capabilities, the Gemini Enterprise access path, and the SynthID watermark, which helps readers judge its enterprise deployment fit.

AIHuawei will likely remain about four years behind Nvidia in AI chip performance and production through 2030, Epoch AI estimates. Its flagship Ascend 950 delivers roughly half the performance of Nvidia's 2022 H100, and Huawei is projected to produce about 1.5 million chips in 2026 versus Nvidia's roughly 6 million, leaving it about 25 times behind in total compute.

AIGoogle introduced Gemini 3.8 Live with Live Avatar, which adds a visual persona with lip-syncing and expressions to its live dialogue models. The feature is available in Gemini Enterprise and supports 97 languages, with custom avatars available through enterprise allowlisting. Google says all output is watermarked with SynthID.

Why it matters: The post specifies enterprise availability, custom avatar allowlisting, and 97-language support, which clarifies who can use the feature and how far it reaches.

AIMicrosoft announced general availability of Routines in Foundry Agent Service, a managed way to run agents on a timer, on a recurring schedule, or in response to GitHub issue events and new Microsoft Teams channel messages. Routines keep the trigger, agent action, identity, connections, and run history in the Foundry project, and each routine can run under the creator's identity or the agent's own Microsoft Entra ID identity. A preview reminder tool lets a Hosted Agent schedule itself to resume later on the same conversation.

Why it matters: The post explains how scheduled, event-based, and self-reminding agent runs are managed in one place, along with the creator versus agent identity choice for unattended tasks.

AIGoogle says Gemini 3.8 Live with Live Avatar is now generally available in Gemini Enterprise, with US and EU endpoints, provisioned throughput, and enterprise compliance. Its video avatars use synchronized lip-syncing, custom avatars are limited to an allowlist, and generated audio and video carry SynthID watermarks. The model also understands and speaks 97 languages and can run tool calls in the background while the conversation continues.

AIAI adoption among Latin American small and medium-sized businesses has surged, with Google Cloud AI tool users growing 8x year-over-year across the region and 9x in Brazil. Companies such as AdGoat, Angelus, and BunkerDB are using Gemini Enterprise and Cloud infrastructure to automate content analysis, project management, and marketing workflows. BunkerDB reports cutting creative turnaround times from weeks to hours and reducing cost per lead by up to 25%.

AILiquid AI announced its on-device Liquid Context layer is now optimized for Snapdragon processors using the Qualcomm Hexagon NPU, letting edge agents learn user routines and share context across devices. Separately, Liquid AI released LFM2-1.2B-Longevity and LFM2-2.6B-Longevity, which the company says often match or outperform much larger frontier LLMs on longevity prediction tasks.