agentic ai

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Mend.io Releases AI Security Governance Framework Covering Asset Inventory, Risk Tiering, AI Supply Chain Security, and Maturity Model

There’s a pattern playing out inside almost every engineering organization right now. A developer installs GitHub Copilot to ship code faster. A data analyst starts querying a new LLM tool for reporting. A product team quietly embeds a third-party model into a feature branch. By the time the security team hears about any of it,

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OpenAI Releases GPT-5.5, a Fully Retrained Agentic Model That Scores 82.7% on Terminal-Bench 2.0 and 84.9% on GDPval

OpenAI has released GPT-5.5, its most capable model to date and the first fully retrained base model since GPT-4.5. GPT-5.5 is designed to complete complex, multi-step computer tasks with minimal human direction. Think of it as the difference between an assistant who needs a checklist and one who understands the underlying goal and figures out

OpenAI Releases GPT-5.5, a Fully Retrained Agentic Model That Scores 82.7% on Terminal-Bench 2.0 and 84.9% on GDPval Read More »

A Coding Tutorial on OpenMythos on Recurrent-Depth Transformers with Depth Extrapolation, Adaptive Computation, and Mixture-of-Experts Routing

In this tutorial, we explore the implementation of OpenMythos, a theoretical reconstruction of the Claude Mythos architecture that enables deeper reasoning through iterative computation rather than increased parameter size. We build and analyze models using both GQA and MLA attention mechanisms, examine memory efficiency through KV-cache comparisons, and validate stability via the spectral properties of

A Coding Tutorial on OpenMythos on Recurrent-Depth Transformers with Depth Extrapolation, Adaptive Computation, and Mixture-of-Experts Routing Read More »

NVIDIA and Google infrastructure cuts AI inference costs

At the Google Cloud Next conference, Google and NVIDIA outlined their hardware roadmap designed to address the cost of AI inference at scale. The companies detailed the new A5X bare-metal instances, which run on NVIDIA Vera Rubin NVL72 rack-scale systems. Through hardware and software codesign, this architecture aims to deliver up to ten times lower

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Your factory floor is asking for better decisions. Are you listening?

You don’t lose sleep over dashboards. You lose sleep over decisions. You’re standing on the factory floor, surrounded by the hum of million-dollar assets, and you know something is off. An alert flashes on a screen: “Anomaly Detected.” But what now? In that split second, the gap between a minor […] The post Your factory

Your factory floor is asking for better decisions. Are you listening? Read More »

Google Cloud AI Research Introduces ReasoningBank: A Memory Framework that Distills Reasoning Strategies from Agent Successes and Failures

Most AI agents today have a fundamental amnesia problem. Deploy one to browse the web, resolve GitHub issues, or navigate a shopping platform, and it approaches every single task as if it has never seen anything like it before. No matter how many times it has stumbled on the same type of problem, it repeats

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Xiaomi Releases MiMo-V2.5-Pro and MiMo-V2.5: Matching Frontier Model Benchmarks at Significantly Lower Token Cost

Xiaomi MiMo team publicly released two new models: MiMo-V2.5-Pro and MiMo-V2.5. The benchmarks, combined with some genuinely striking real-world task demos, make a compelling case that open agentic AI is catching up to the frontier faster than most expected. Both models are available immediately via API, and priced competitively. What is an Agentic Model, and

Xiaomi Releases MiMo-V2.5-Pro and MiMo-V2.5: Matching Frontier Model Benchmarks at Significantly Lower Token Cost Read More »

How to Design a Production-Grade CAMEL Multi-Agent System with Planning, Tool Use, Self-Consistency, and Critique-Driven Refinement

In this tutorial, we implement an advanced agentic AI system using the CAMEL framework, orchestrating multiple specialized agents to collaboratively solve a complex task. We design a structured multi-agent pipeline consisting of a planner, researcher, writer, critic, and rewriter, each with clearly defined responsibilities and schema-constrained outputs. We integrate tool usage, self-consistency sampling, structured validation

How to Design a Production-Grade CAMEL Multi-Agent System with Planning, Tool Use, Self-Consistency, and Critique-Driven Refinement Read More »

Alibaba Qwen Team Releases Qwen3.6-27B: A Dense Open-Weight Model Outperforming 397B MoE on Agentic Coding Benchmarks

Alibaba’s Qwen Team has released Qwen3.6-27B, the first dense open-weight model in the Qwen3.6 family — and arguably the most capable 27-billion-parameter model available today for coding agents. It brings substantial improvements in agentic coding, a novel Thinking Preservation mechanism, and a hybrid architecture that blends Gated DeltaNet linear attention with traditional self-attention — all

Alibaba Qwen Team Releases Qwen3.6-27B: A Dense Open-Weight Model Outperforming 397B MoE on Agentic Coding Benchmarks Read More »