Software engineering

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Poetiq’s Meta-System Automatically Builds a Model-Agnostic Harness That Improved Every LLM Tested on LiveCodeBench Pro Without Fine-Tuning

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Poetiq has just published some very interesting results showing its Meta-System reached a new state-of-the-art on LiveCodeBench Pro (LCB Pro), a competitive coding benchmark, by automatically building and optimizing its own inference harness — without fine-tuning any underlying model or accessing model internals. The result: GPT 5.5 High with Poetiq’s harness scores 93.9% on LCB […]

Poetiq’s Meta-System Automatically Builds a Model-Agnostic Harness That Improved Every LLM Tested on LiveCodeBench Pro Without Fine-Tuning Read More »

A Coding Implementation to Master GPU Computing with CuPy, Custom CUDA Kernels, Streams, Sparse Matrices, and Profiling

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In this tutorial, we delve into CuPy as a powerful GPU-accelerated alternative to NumPy for high-performance numerical computing in Python. We start by inspecting the available CUDA device, checking the CuPy version, runtime details, GPU memory, and compute capability so that we understand the hardware environment before running heavy computations. Then, we compare NumPy and

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Cline Releases Cline SDK: An Open-Source Agent Runtime Now Powering Its CLI and Kanban, With IDE Extensions Being Migrated

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Cline became ‘agentic’ before it was cool, but building on the bleeding edge usually leads to some structural debt. Over time, the agent loop and the VS Code extension became a package deal—making it a headache to maintain or move to new environments. Its tough to just keep layering features on a rigid core. Cline,

Cline Releases Cline SDK: An Open-Source Agent Runtime Now Powering Its CLI and Kanban, With IDE Extensions Being Migrated Read More »

How to Build a Dynamic Zero-Trust Network Simulation with Graph-Based Micro-Segmentation, Adaptive Policy Engine, and Insider Threat Detection

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In this tutorial, we build a realistic Zero-Trust network simulation by modeling a micro-segmented environment as a directed graph and forcing every request to earn access through continuous verification. We implement a dynamic policy engine that blends ABAC-style permissions with device posture, MFA, path reachability, zone sensitivity, and live risk signals such as anomaly and

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Fastino Labs Open-Sources GLiGuard: A 300M Parameter Safety Moderation Model That Matches or Exceeds Accuracy of Models 23–90x Its Size

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As LLM-powered applications move into production — and as AI agents take on more consequential tasks like browsing the web, writing and executing code, and interacting with external services — safety moderation has quietly become one of the most operationally expensive parts of the stack. Most developers who’ve deployed a production LLM system know the

Fastino Labs Open-Sources GLiGuard: A 300M Parameter Safety Moderation Model That Matches or Exceeds Accuracy of Models 23–90x Its Size Read More »

Mira Murati’s Thinking Machines Lab Introduces Interaction Models: A Native Multimodal Architecture for Real-Time Human-AI Collaboration

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Most AI systems today work in turns. You type or speak, the model waits, processes your input, and then responds. That’s the entire interaction loop. Thinking Machines Lab, an AI research lab, is arguing that this model of interaction is a fundamental bottleneck. Thinking Machines Lab team introduced a research preview of a new class

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Google DeepMind Introduces an AI-Enabled Mouse Pointer Powered by Gemini That Captures Visual and Semantic Context Around the Cursor

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The mouse pointer has sat at the center of personal computing for more than half a century. It tracks cursor position. It registers clicks. Beyond that, it does almost nothing. Google DeepMind researchers outlined a set of experimental principles and demos for an AI-enabled pointer that goes considerably further: one that understands not just where

Google DeepMind Introduces an AI-Enabled Mouse Pointer Powered by Gemini That Captures Visual and Semantic Context Around the Cursor Read More »

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Build a Hybrid-Memory Autonomous Agent with Modular Architecture and Tool Dispatch Using OpenAI

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In this tutorial, we begin by exploring the architecture behind a hybrid-memory autonomous agent. This system combines semantic vector search, keyword-based retrieval, and a modular tool-dispatching loop to create an agent capable of reasoning, remembering, and acting autonomously. We walk through each layer of the design from the ground up, starting with abstract interfaces that

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Meet AntAngelMed: A 103B-Parameter Open-Source Medical Language Model Built on a 1/32 Activation-Ratio MoE Architecture

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A team researchers from China have released AntAngelMed, a large open-source medical language model that the team describes as the largest and most capable of its kind currently available. What Is AntAngelMed? AntAngelMed is a medical-domain language model with 103 billion total parameters, but it does not activate all of those parameters during inference. Instead,

Meet AntAngelMed: A 103B-Parameter Open-Source Medical Language Model Built on a 1/32 Activation-Ratio MoE Architecture Read More »