#Adaptive Recall
34 related articles
Adaptive Recall: A Deep Dive into Pers…
·2 min
Adaptive Recall: A Deep Dive into Persistent Memory for AI Assistants via MCP
Adaptive Recall uses MCP (Model Context Protocol) to give AI assistants like Claude persistent memory across sessions, featuring vector storage, semantic retrieval, and adaptive forgetting.
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·5 min
Is the Self an Illusion? Neuroscience Reveals the True Nature of Identity
Emory neuroscientist Gregory Burns argues the self is a story the brain weaves. From the Ship of Theseus to memory confabulation, explore how identity is shaped by narrative and how we can rewrite it.
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·4 min
Java Developer to AI Architect: A Three-Layer Capability Upgrade Roadmap
How can Java engineers transition to AI Architect? This article breaks down three core capability layers — AI app development, production RAG, and AI Agent orchestration — using Spring AI Alibaba and LangChain4j to turn your Java foundation into a competitive edge.
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·7 min
Context Engineering: A Systematic Approach to Stop AI Agents from 'Talking Nonsense'
Context engineering is the core methodology for building efficient AI Agents, covering query enhancement, RAG retrieval, prompt design, memory management, and tool invocation. Master Write, Select, Compress, and Isolate to solve LLM hallucination at its root.
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Kronos Financial Foundation Model: Usi…
·7 min
Kronos Financial Foundation Model: Using AI to Read the Market Language of Candlesticks
Kronos is the first open-source foundation model treating candlestick data as the "language of financial markets," using an autoregressive Transformer and earning 32K GitHub Stars. A deep dive into its principles, applications, and limits.
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·3 min
Enterprise RAG Knowledge Isolation in Practice: Physical Isolation vs. Adaptive Soft Boundaries
A deep dive into two enterprise RAG knowledge isolation strategies: physical isolation vs. adaptive soft boundaries — covering metadata tagging, dynamic user-profile filtering, hybrid retrieval architecture, and data quality best practices.
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·3 min
Understanding RAG from Scratch: A Complete Guide to Retrieval-Augmented Generation
RAG (Retrieval-Augmented Generation) is a key technology for solving LLM hallucinations. This guide breaks down how RAG works, its advantages, and real-world use cases — no math required.
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·7 min
Training Machine Learning Models from Scratch: A Complete Beginner's Guide
A complete walkthrough of training machine learning models from scratch—covering problem definition, data preprocessing, algorithm selection, hyperparameter tuning, and evaluation, with tool recommendations for beginners.
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·7 min
OpenClaw vs Hermes: An In-Depth Comparison and Selection Guide for AI Agent Tools
An in-depth comparison of OpenClaw and Hermes Agent, covering skill management, memory mechanisms, security, and gateway configuration to help you find the right AI agent solution.
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·7 min
Turning Any AI Agent into an Orchestration Hub: A Deep Dive into Multi-Agent Collaboration Architecture
An in-depth analysis of the "any Agent as an orchestrator" design philosophy, exploring the technical implementation of multi-Agent collaboration, context management, and workflow automation.
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·5 min
Real-World Comparison of 6 Open-Source LLMs for On-Premise Deployment: A Selection Guide to Avoid Pitfalls
A hands-on comparison of 6 open-source LLMs (DeepSeek, Qwen3, Zhipu GLM, Kimi K2, MiniMax M3, Tencent Hunyuan 3) for on-premise deployment—covering hardware cost, inference efficiency, and deployment difficulty.
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·4 min
DeepSeek-V4 Deep Dive: Million-Token Context Architecture Breakthrough and Core Innovations
Deep dive into DeepSeek-V4: 1.6T-parameter MoE, CSA+HCA hybrid attention, MHC & MUON optimizer. Inference FLOPs drop to 27% of V3.2, redefining open-source LLM SOTA.
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·3 min
GBrain Local Deployment: 12-Step Deep Retrieval Pipeline Outperforms Traditional RAG by 31%
GBrain's 12-step deep retrieval pipeline and knowledge graph construction outperforms traditional RAG by 31% — with full local offline deployment for data security and lower API costs.
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·6 min
Unsloth Major Update: DeepSeek-V4 Support and a Deep Dive into NVFP4 Quantized Export
Unsloth v0.1.481-beta adds full DeepSeek-V4-Flash support, NVFP4/FP8/imatrix GGUF quantized export, 1.3x faster GRPO, 3-5x faster MoE training, and an OpenAI-compatible API service in Studio.
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·6 min
From Video to Notes to Knowledge Base: A Practical Guide to AI-Assisted Learning Workflows
A complete AI learning workflow: batch download videos, auto-transcribe, generate structured notes with AI, then build intelligent search and Q&A via Dify. Turn scattered videos into a reusable personal knowledge base.
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·5 min
Major Unsloth Update: NVFP4 Quantization Export and DeepSeek-V4 Training Support
Unsloth v0.1.48-beta released, adding NVFP4/FP8 quantization export, OpenAI-compatible API hot-swapping, 3-5x faster MoE training, and 1.3x faster GRPO, covering the full LLM fine-tuning, quantization, and local deployment pipeline.
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·5 min
How an MD Is Reshaping Biological Research with AI Codex: A Practical Path to Accelerating the Fight Against Cancer
Immunologist Derya Unutmaz shares how he used OpenAI Codex to build research-grade apps for flow cytometry analysis and CRISPR design, exploring AI-driven digital twins and personalized cancer treatment.
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·7 min
Spring AI 2.0 in Practice: A Beginner's Guide for Java Developers Building AI Agents
A complete Spring AI 2.0 guide for Java developers covering unified API abstraction, RAG, tool calling, MCP protocol, and enterprise projects to build AI Agents.
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·7 min
The Complete Guide to AI-Powered Customer Service: How AI Is Reshaping Enterprise Service Systems
AI customer service is a core tool for digital transformation. This guide covers its value, use cases, and implementation logic, including efficiency gains, cost reduction, and data-driven optimization.
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·3 min
LLM Development Learning Path: From Zero to Enterprise-Level Projects
A complete LLM development learning roadmap covering prompt engineering, RAG, AI Agents, and fine-tuning — helping beginners master LangChain, LlamaIndex, and more.
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