Tagged articles

8 articles

Page 1 of 1

Apr 13, 2026 · Artificial Intelligence

Deploy AI Agents from Business Requirements to Amazon Bedrock in Hours with Kiro

This article shows how to use Kiro IDE to turn business needs into AI Agent solutions, generate SPEC‑driven documentation, and deploy the agents on Amazon Bedrock AgentCore, covering the AI‑driven development workflow, architecture choices, code examples, deployment steps, and common troubleshooting tips.

AI AgentsAgentCoreAmazon Bedrock

0 likes · 35 min read

Deploy AI Agents from Business Requirements to Amazon Bedrock in Hours with Kiro

Machine Learning Algorithms & Natural Language Processing

Apr 1, 2026 · Artificial Intelligence

Claude Code’s Source Code Reveals Anthropic’s Move from Tool to Self‑Evolving AI Agent

A deep dive into Claude Code’s 500 k‑line TypeScript repository shows how Anthropic is turning a programming assistant into a memory‑rich, autonomous AI agent platform with multi‑agent collaboration, cloud‑native scheduling, speculative execution, and even a pet‑style companion.

AnthropicClaude Codecloud scheduling

0 likes · 20 min read

Claude Code’s Source Code Reveals Anthropic’s Move from Tool to Self‑Evolving AI Agent

Bighead's Algorithm Notes

Jan 6, 2026 · Artificial Intelligence

FinRS: A Risk‑Sensitive Trading Framework for Real‑World Financial Markets

FinRS integrates hierarchical market analysis, dual decision agents, and multi‑time‑scale reward feedback to enable risk‑aware multi‑stage trading, achieving higher cumulative returns, better Sharpe ratios, and lower maximum drawdowns than existing LLM‑based and reinforcement‑learning baselines across diverse stocks.

FinRSLLMfinancial markets

0 likes · 14 min read

FinRS: A Risk‑Sensitive Trading Framework for Real‑World Financial Markets

Fun with Large Models

Jan 5, 2026 · Artificial Intelligence

LangGraph Agent Design Patterns Part 3: Supervisor and Hierarchical Architectures

This article explains LangGraph's multi‑agent design patterns, focusing on the Supervisor Architecture for centralized coordination and the Hierarchical Architecture for scalable team‑based management, and provides step‑by‑step code examples that demonstrate how to implement both patterns.

AI AgentsAgent CoordinationHierarchical Architecture

0 likes · 21 min read

LangGraph Agent Design Patterns Part 3: Supervisor and Hierarchical Architectures

Amap Tech

Dec 11, 2025 · Artificial Intelligence

How ACoder Achieved Up to 24× Faster Multi‑Platform Development with AI

The ACoder platform combines multi‑model AI, a panoramic code‑understanding engine, and a layered knowledge‑management system to automate the entire software‑development lifecycle, delivering 5‑20× overall efficiency gains, up to 24× speed‑up for cross‑platform code migration, and dramatically higher code‑recall accuracy.

AI codingKnowledge Managementcode generation

0 likes · 19 min read

How ACoder Achieved Up to 24× Faster Multi‑Platform Development with AI

JD Tech Talk

Mar 24, 2025 · Artificial Intelligence

MaRCA: Multi‑Agent Reinforcement Learning Computation Allocation for Full‑Chain Ad Serving

This article presents MaRCA, a multi‑agent reinforcement learning framework that allocates computation resources across the full ad‑serving chain by modeling user value, compute consumption, and action rewards, enabling fine‑grained power‑tilting toward high‑quality traffic and achieving significant business gains under strict latency constraints.

ad servingai-optimizationcomputation allocation

0 likes · 16 min read

MaRCA: Multi‑Agent Reinforcement Learning Computation Allocation for Full‑Chain Ad Serving

JD Retail Technology

Mar 18, 2025 · Artificial Intelligence

Multi‑Agent Reinforcement Learning Based Full‑Chain Computation Allocation (MaRCA) for Advertising Systems

MaRCA, a multi‑agent reinforcement‑learning framework, allocates compute across JD’s advertising playback chain by jointly estimating user value, resource consumption, and action outcomes while dynamically adjusting to real‑time load, achieving roughly 15 % higher ad revenue without extra compute resources.

AdvertisingCompute SchedulingResource Allocation

0 likes · 18 min read

Multi‑Agent Reinforcement Learning Based Full‑Chain Computation Allocation (MaRCA) for Advertising Systems

DataFunSummit

Nov 14, 2024 · Artificial Intelligence

Building Multi‑Scenario Personal and Office AI Assistants with Large Models at Huolala

Huolala leverages large language models to create a suite of AI assistants—ranging from professional troubleshooting bots to multimodal insurance quoting tools—across more than 14 logistics scenarios, detailing platform architecture, prompt engineering, multi‑agent coordination, and future AI‑driven business empowerment.

AI assistantsBusiness AutomationLLM platform

0 likes · 13 min read

Building Multi‑Scenario Personal and Office AI Assistants with Large Models at Huolala