All news with #ai evals tag

xAI's Grok 4.1 Debuts with Improved Quality and Speed

🚀 Elon Musk-owned xAI has begun rolling out Grok 4.1, offering two free variants—Grok 4.1 and Grok 4.1 Thinking—with paid tiers providing higher usage limits. xAI reports the update is roughly three times less likely to hallucinate than earlier versions and brings quality and speed improvements. Early LMArena Text Arena benchmarks place Grok 4.1 Thinking at the top of the Arena Expert leaderboard, though comparisons with rivals like GPT-5.1 and Google's upcoming Gemini 3.0 remain preliminary.

A Methodical Approach to Agent Evaluation: Quality Gate

🧭 Hugo Selbie presents a practical framework for evaluating modern multi-step AI agents, emphasizing that final-output metrics alone miss silent failures arising from incorrect reasoning or tool use. He recommends defining clear, measurable success criteria up front and assessing agents across three pillars: end-to-end quality, process/trajectory analysis, and trust & safety. The piece outlines mixed evaluation methods—human review, LLM-as-a-judge, programmatic checks, and adversarial testing—and prescribes operationalizing these checks in CI/CD with production monitoring and feedback loops.

The AI Fix #76 — AI self-awareness and the death of comedy

🧠 In episode 76 of The AI Fix, hosts Graham Cluley and Mark Stockley navigate a string of alarming and absurd AI stories from November 2025. They discuss US judges who blamed AI for invented case law, a Chinese humanoid that dramatically shed its outer skin onstage, Toyota’s unsettling walking chair, and Google’s plan to put specialised AI chips in orbit. The conversation explores reliability, public trust and whether prompting an LLM to "notice its noticing" changes how conscious it sounds.

Agent Factory Recap: Evaluating Agents, Tooling, and MAS

📡 This recap of the Agent Factory podcast episode, hosted by Annie Wang with guest Ivan Nardini, explains how to evaluate autonomous agents using a practical, full-stack approach. It outlines what to measure — final outcomes, chain-of-thought, tool use, and memory — and contrasts measurement techniques: ground truth, LLM-as-a-judge, and human review. The post demonstrates a 5-step debugging loop using the Agent Development Kit (ADK) and describes how to scale evaluation to production with Vertex AI.

Microsoft launches ExCyTIn-Bench to benchmark AI security

🛡️ Microsoft released ExCyTIn-Bench, an open-source benchmarking tool to evaluate how well AI systems perform realistic cybersecurity investigations. It simulates a multistage Azure SOC using 57 Microsoft Sentinel log tables and measures multistep reasoning, tool usage, and evidence synthesis. The benchmark offers fine-grained, actionable metrics for CISOs, product owners, and researchers.

Satisfaction Analysis for Untagged Chatbot Conversations

🔎 This article examines methods to infer user satisfaction from untagged chatbot conversations by combining linguistic and behavioral signals. It argues that conventional metrics such as accuracy and completion rates often miss subtle indicators of user sentiment, and recommends unsupervised and weakly supervised NLP techniques to surface those signals. The post highlights practical considerations including privacy-preserving aggregation, deployment complexity, and the potential business benefit of reducing churn and improving customer experience through targeted dialog improvements.

OpenAI Launches GPT-5 Codex Model for Coding, Broad Rollout

🤖 OpenAI is deploying a specialized GPT-5 Codex model across its Codex instances, including Terminal, IDE extensions, and Codex Web. The agent automates coding tasks so users — even those without programming experience — can generate and execute code and accelerate app development. OpenAI reported strong benchmark gains and says the staged rollout will reach all users in the coming days.

Google Cloud: Monthly AI product and security update

🔔 This month Google Cloud expanded its AI stack across models, tooling, and security. Highlights include Gemini 2.5 Flash with native image generation and SynthID watermarking on Vertex AI, new Veo video models, the Gemini CLI, and a global Anthropic Claude endpoint. Google also published 101 gen‑AI blueprints, developer guidance for choosing tools, and security advances for agents and AI workloads.

Background Removal: Evaluating Image Segmentation Models

🧠 Cloudflare introduces background removal for Images, running a dichotomous image segmentation model on Workers AI to isolate subjects and produce soft saliency masks that map pixel opacity (0–255). The team evaluated U2-Net, IS-Net, BiRefNet, and SAM via the open-source rembg interface on the Humans and DIS5K datasets, prioritizing IoU and Dice metrics over pixel accuracy. BiRefNet-general achieved the best overall balance of fidelity and detail (IoU 0.87, Dice 0.92) while lightweight models were faster on modest GPUs and SAM was excluded for unprompted tasks. The feature is available in open beta through the Images API using the segment parameter and can be combined with other transforms or draw() overlays.

Agent Factory: Top 5 Agent Observability Practices

🔍 This post outlines five practical observability best practices to improve the reliability, safety, and performance of agentic AI. It defines agent observability as continuous monitoring, detailed tracing, and logging of decisions and tool calls combined with systematic evaluations and governance across the lifecycle. The article highlights Azure AI Foundry Observability capabilities—evaluations, an AI Red Teaming Agent, Azure Monitor integration, CI/CD automation, and governance integrations—and recommends embedding evaluations into CI/CD, performing adversarial testing before production, and maintaining production tracing and alerts to detect drift and incidents.

SAFECOM/NCSWIC AI Guidance for Emergency Call Centers

📞 SAFECOM and NCSWIC released an infographic outlining how AI is being integrated into Emergency Communication Centers to provide decision-support for triage, translation/transcription, data confirmation, background-noise detection, and quality assurance. The resource also describes use of signal and sensor data to enhance first responder situational awareness. It highlights cybersecurity, operability, interoperability, and resiliency considerations for AI-enabled systems and encourages practitioners to review and share the guidance.