Thinking of ACE? We Can Do It with Fewer Tokens
Thinking of ACE? A recent IBM Research blog post, published on August 11, 2026, examines how local models can achieve the same effect with...
50 articles
Thinking of ACE? A recent IBM Research blog post, published on August 11, 2026, examines how local models can achieve the same effect with...
Discover how LFM2.5-2.6B enables lightweight, privacy-preserving AI agents on edge devices. This compact model delivers strong reasoning a...
In supply chains, the hardest challenges aren't building AI models—it's understanding messy, real-world operations. Forward-deployed engin...
From NumPy to PyTorch, Python's libraries and frameworks have transformed AI from research to production. This exploration reveals how a v...
Hugging Face and OpenAI documented a July 2026 agent-driven intrusion. This article separates confirmed findings from open questions and r...
Analog computing is making a comeback in AI, promising energy efficiency but facing challenges from inherent noise. Can these systems over...
Simulation is transforming physical AI by enabling safe, scalable training for robots and autonomous systems. Local models bring real-time...
AI is transforming analytics, but instead of fearing it, I leverage it as a co-pilot. By focusing on strategic thinking, data storytelling...
This article explores a novel loop engineering experiment where context management occurs entirely outside the LLM, revealing critical ins...
NVIDIA's Nemotron-3-8B-Embedding model achieves the top ranking on the Retrieval Text Embedding Benchmark (RTEB), setting a new standard f...
Learn how to combine Pydantic models with OpenAI's API to reliably extract structured, validated data from LLM responses—eliminating parsi...
Lessons from developing Shippy, an AI agent for logistics, reveal that modular design, human-in-the-loop validation, and handling real-wor...
AI personalities are not magic; they emerge from training data, fine-tuning, and system prompts. This article explores the technical origi...
Frontier AI models continue to generate plausible-sounding but false information, a persistent flaw known as hallucination. This article e...
Most LLM wikis add unnecessary complexity with vector databases and APIs. A pure Python compiler can replace them, parsing structured mark...
The ReAct loop combines reasoning and acting to enable AI agents to solve complex tasks iteratively. By alternating between thought, actio...
Rising costs from AI coding agents can drain your budget. Learn practical strategies to audit usage, optimize prompts, and switch to cost-...
OpenWiki is a new open source AI agent that automatically generates, updates, and maintains documentation for code repositories. It integr...
Learn how to build and deploy a custom AI agent on cloud infrastructure. This guide covers architecture, tooling, and practical steps for...
Hugging Face and Cerebras collaborate to run Gemma 4 models for real-time voice AI on local hardware, enabling low-latency speech processi...
Explore the risks and strategies for executing untrusted AI agent code without sandboxing, including isolation techniques, monitoring, and...
Prompt regression causes AI outputs to degrade over time without warning. Learn why it happens, how to detect it, and practical strategies...
Dynamic subagents enhance AI agent systems by enabling real-time delegation of specialized tasks. This modular approach improves scalabili...
A team built a custom AI routing layer to reduce API costs, but it introduced latency, errors, and unpredictable behavior that degraded th...
Reliable AI agents often fail due to over-engineering the 'head' (reasoning). Tail control flips this: by constraining the agent's actions...
Discover why top-performing AI agents rely on minimalistic design, clear prompts, and smart tool use instead of complex architectures. Sim...
Prompt caching reduces latency and cost in AI agents by storing and reusing processed prompts. This technique enables faster multi-step re...
Learn how to transform a local large language model into a powerful agent by integrating external tools like web search, APIs, and code ex...
Standard vector retrieval fails multi-agent systems. Discover how adding a context graph layer enables agents to share structured memory,...
Learn how to launch a vLLM inference server on Hugging Face Jobs with a single command. This guide covers setup, configuration, and practi...
Explore how to use an LLM as an intelligent arbiter to select the best document from RAG retrieval candidates, enhancing accuracy with con...
Learn how to run three AI agents with separate LLMs simultaneously on a single outdated GPU. This article covers bare-metal parallel infer...
Learn how to equip AI agents with memory using vector databases, conversation history, and structured storage. Practical techniques for pe...
Discover why a single AI agent fell short for complex tasks and how a multi-agent pipeline improved accuracy, reliability, and efficiency...
A technique for efficient RAG that uses lightweight parallel detectors to identify semantic anchors before making a single, targeted LLM c...
No-code AI platforms empower non-programmers to build intelligent solutions. Discover how drag-and-drop tools, prebuilt models, and automa...
Discover how CUGA, a lightweight harness, powers two dozen practical agentic applications. Learn to build autonomous AI agents with code e...
Discover how the huggingface_hub library is released weekly using AI for code review and open tools for automation, while keeping a human...
AI research is advancing rapidly, exploring machine learning, neural networks, and ethics. This article delves into current breakthroughs,...
Discover how AI agents use tool calling to decide their next action. This article breaks down the decision-making process, from function s...
Explore how AI research has evolved from foundational theories to cutting-edge breakthroughs, including deep learning and reinforcement le...
Learn how to get structured data from large language models using JSON mode and function calling. This guide compares both approaches with...
Learn how to evaluate open-source AI agents for autonomy and task completion using custom benchmarks. A practical guide for researchers an...
Many developers rush to adopt complex agent frameworks, but often a simple loop with an LLM suffices. This article explains when to skip t...
AI research is rapidly evolving, focusing on areas like generative models, reinforcement learning, and ethical frameworks. These advances...
Agentic Resource Discovery empowers AI agents to autonomously search, evaluate, and retrieve resources like APIs, datasets, or tools. This...
Fleet combines general-purpose chat with specialized AI agents to balance broad assistance and domain-specific expertise, enhancing user p...
AI research is rapidly pushing boundaries, from generative models to reasoning systems. This article explores key breakthroughs, including...
When LLM calls fail, agent pipelines silently break. This article introduces a recovery layer that catches fallbacks, retries intelligentl...
Discover how we engineered a cost-predictable coding agent by combining token budgets, early stopping, and adaptive context management. Le...