#Foundation Models framework
2085 related articles
·1 min
iPadOS 27 Developer Guide: A Comprehensive Breakdown of Foundation Models Framework and Core AI
Deep dive into iPadOS 27's core developer updates: Foundation Models framework, Core AI on-device inference, Siri App Intents integration, PaperKit, and free cloud policy for small developers.
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·4 min
LangChain Guardrails Explained: Building Safe and Controllable AI Agents
A detailed guide to LangChain Guardrails covering layered ecosystem architecture, middleware implementation, deterministic and model-driven protection for building production-grade secure AI Agents.
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·4 min
OpenAI Employee Shares How to Build an AI Work Operating System with Codex
OpenAI's Jason Liu shares how he uses ChatGPT Workbench and Codex to build an AI work OS: Chief of Staff automation, persistent threads, Skills/Plugins, browser control, and app-building methodology.
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·3 min
Learning AI Large Language Models: A Complete Roadmap from Beginner to Practitioner
A systematic breakdown of the AI LLM learning roadmap covering prompt engineering, AI Agent development, RAG knowledge bases, model fine-tuning, and hands-on projects for beginners.
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·5 min
Learn AI Agent Development from Scratch: A 3-Step Practical Path to Get Started Quickly
How to learn AI Agent development from scratch? This article outlines a clear 3-step path: Python crash course, LLM theory & practice, and LangChain framework project implementation.
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·3 min
Backend Developer Transition to AI/LLM: 4 Core Skills and a Practical Learning Roadmap
Complete guide for backend developers transitioning to AI/LLM engineering. Covers the 4 core skills—Python, RAG, Fine-tuning, and Agents—with a phased learning roadmap and practical project advice.
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·2 min
Enterprise RAG in Practice: A Complete Guide to the Core Challenges from Setup to Production Optimization
A deep dive into enterprise RAG from setup to production, covering document chunking, vector search, query rewrite, reranking, and quality evaluation frameworks.
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·3 min
Spring AI Explained: Unified API, RAG, and Enterprise AI Development Practical Guide
Deep dive into Spring AI framework's core features including provider-agnostic unified API abstraction, RAG retrieval-augmented generation, and structured output to help Java developers build enterprise AI apps.
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·3 min
Spring AI Explained: Unified API, RAG, and Enterprise AI Development Guide
Deep dive into Spring AI framework's core features including provider-agnostic unified API abstraction, RAG retrieval-augmented generation, and structured output to help Java developers build enterprise AI apps.
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·3 min
Agent Skill Routing: Engineering Trade-offs Between Retrieval and LLM, and the Two-Stage Layered Architecture
Deep dive into Agent skill routing: comparing pure model vs. pure retrieval approaches, with a detailed two-stage layered architecture balancing accuracy, latency, and cost.
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·2 min
A Beginner's Guide to Vibe Coding: Building Your Career Moat with AI Programming
A detailed guide to Vibe Coding with AI programming tools like Claude Code, Cursor, and Codex. Learn how to leverage AI-driven development to ship products independently and build lasting career value.
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·3 min
OpenAI Academy Hands-On Training: How Small Business Owners Can Use ChatGPT to Boost Operational Efficiency
OpenAI Academy hosted hands-on ChatGPT training for small businesses in California. This article analyzes the training design, core value, and practical insights for entrepreneurs.
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·3 min
OpenAI Admin API Explained: How Enterprises Manage ChatGPT at Scale
Deep dive into how OpenAI Admin API and ChatGPT Work help IT admins manage enterprise ChatGPT at scale—covering access control, cost monitoring, usage insights, and smart quota recommendations.
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·3 min
Legora's Legal AI Practice: How Vertical AI Empowers Law Firms and Corporate Legal Transformation
Explore Legora's legal vertical AI practice, covering AI model selection strategies, enterprise legal transformation challenges, and the path to deploying vertical AI in the legal industry.
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·4 min
Opus 5 Real-World Testing: Cheaper Yet Stronger — Why It's Now My Default Coding Model
In-depth testing of Claude Opus 5's coding abilities vs Fable 5 and 5.6 Sol. Why Opus 5 outperforms pricier models at half the token cost, plus selection guide and distillation explained.
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·4 min
Kimi K2/K3 Technical Speculation: Deep Dive into RL Hyperparameters and Multi-Teacher Distillation
Deep analysis of RL hyperparameter tuning challenges and 9-policy multi-teacher distillation in Kimi K2/K3 training, exploring the shift from scale to training craft.
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·4 min
AI Companies Buy Books, Scan Them, Then Destroy Them: Pulping of Rare Books Sparks Cultural Preservation Debate
Some AI companies are mass-purchasing physical books for destructive scanning and pulping to obtain training data, even targeting rare antiquarian volumes. This article analyzes the technical motivations, legal gray areas, and cultural preservation controversies.
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·5 min
WebMCP in Practice: Building Browser AI Agent Tools & DevTools Debugging Guide
A detailed guide to Google's WebMCP standard proposal, covering imperative and declarative tool building, smart home and car configuration demos, and Chrome DevTools debugging for AI agent tools.
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·3 min
Replacing spaCy's Sentencizer with yasbd: Accuracy Jumps from 55% to 98.9%
spaCy's default Sentencizer achieves only 55.4% accuracy on edge cases, while open-source library yasbd reaches 98.9%. Analysis of limitations and integration code examples.
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·3 min
A 9B Model Beats Frontier LLMs After Just $500 in RL Fine-Tuning
Just $500 in RL fine-tuning enables a 9B open-source model to outperform frontier LLMs on catalog review tasks. Analysis of when small-model RL works and its enterprise implications.
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