ACE positions “context engineering” as a first-class alternative to parameter updates. Instead of compressing instructions into short prompts, ACE accumulates and organizes domain-specific tactics ...
Flow-GRPO (Flow-based Group Refined Policy Optimization) converts long-horizon, sparse-reward optimization into tractable single-turn updates: Benchmarks. The research team evaluates four task types: ...
What if an AI agent could localize a root cause, prove a candidate fix via automated analysis and testing, and proactively rewrite related code to eliminate the entire vulnerability class—then open an ...
SwiReasoning is a decoding-time framework that lets a reasoning LLM decide when to think in latent space and when to write explicit chain-of-thought, using ...
Google AI Proposes ReasoningBank: A Strategy-Level AI Agent Memory Framework that Makes LLM Agents Self-Evolve at Test Time ...
Liquid AI has released LFM2-Audio-1.5B, a compact audio–language foundation model that both understands and generates speech and text through a single end-to-end stack. It positions itself for ...
This hands-on tutorial will walk you through the entire process of working with CSV/Excel files and conducting exploratory data analysis (EDA) in Python. We’ll use a realistic e-commerce sales dataset ...
Kimi K2, launched by Moonshot AI in July 2025, is a purpose-built, open-source Mixture-of-Experts (MoE) model—1 trillion total parameters, with 32 billion active parameters per token. It’s trained ...
The Model Context Protocol (MCP) team has released the preview version of the MCP Registry, a system that could be the final puzzle piece for making enterprise AI truly production-ready. More than ...
At Google I/O 2025, Google introduced MedGemma, an open suite of models designed for multimodal medical text and image comprehension. Built on the Gemma 3 architecture, MedGemma aims to provide ...
Agent Development Kit (ADK) is an open-source Python framework that helps developers build, manage, and deploy multi-agent systems. It’s designed to be modular and flexible, making it easy to use for ...
No single solution universally wins between Large Language Models (LLMs, ≥30B parameters, often via APIs) and Small Language Models (SLMs, ~1–15B, typically open-weights or proprietary specialist ...
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