First‑line development experience at multiple leading tech firms; now a software architect at a Shanghai state‑owned enterprise and founder of Programming Yanxuan. Nearly 300k followers online; expertise in distributed system design, AIGC application development, and quantitative finance investing.
Google’s Agent Development Kit (ADK) has added Go language support, enabling developers to build modular, high‑concurrency AI agents with code‑first workflows, integrated debugging UI, A2A protocol for agent collaboration, and a suite of pre‑built tools for tasks like Gemini search and Cloud API calls.
Anthropic introduced a sandbox for Claude Code that isolates file system and network access at the operating‑system level, reducing permission prompts and security risks while allowing developers to run, test, and submit code changes from a secure cloud VM.
This report outlines emerging AI trends for the coming year, highlighting Physical AI, AI agents, multimodal models, the MCP standard, and the growing role of AI‑driven DevOps, while also discussing security implications and adoption stages across the technology lifecycle.
This article examines why AI‑assisted coding often falls short on quality and integration, introduces a structured PDCA workflow to guide AI interactions, presents experimental data comparing PDCA‑guided and unstructured approaches, and outlines practical guidelines and future enhancements for sustainable AI‑driven software development.
Hugging Face AI Sheets lets users employ large language models through a spreadsheet‑like interface to clean, transform, enrich, and generate datasets without writing code, offering both zero‑shot dataset creation and import‑based bulk processing, with optional self‑hosting via Docker for privacy‑sensitive workflows.
This article provides a detailed overview of Kiro, Amazon's AI‑driven IDE that integrates Claude models to bring specification‑driven structure to vibe coding, covering its core concepts, installation steps, key features, workflow, pricing, and practical insights from a hands‑on experience.
The article examines Kimi K2, Moonshot AI’s open‑source large language model, detailing its MoE architecture, low‑cost pricing, agentic capabilities, performance comparisons with Claude and DeepSeek, and real‑world developer experiences, while discussing its potential impact on the AI landscape.
GPULlama3.java, released by Manchester University's Beehive Lab, is the first native Java implementation of Llama 3 that leverages TornadoVM to automatically accelerate inference on GPUs without writing CUDA or native code, supporting NVIDIA, Intel and Apple Silicon back‑ends and modern Java 21 features.
This guide explains why Java architects should understand CUDA, describes the GPU programming model, compares CPU and GPU designs, and details three practical ways—JNI, JCuda, and TornadoVM—to integrate CUDA acceleration into Java applications, with tips for using A100 GPUs effectively.
The article explains what inference engines are, why they are needed beyond raw Python scripts, and outlines best practices such as model quantization, batching, and parallelism, while comparing popular open‑source and commercial options for production AI workloads.
