Baidu Releases ERNIE-4.5-21B-A3B-Thinking: A Compact MoE Model for Deep Reasoning

Baidu AI Research team has just released ERNIE-4.5-21B-A3B-Thinking, a new reasoning-focused large language model designed around efficiency, long-context reasoning, and tool integration. Being part of the ERNIE-4.5 family, this model…

MCP Team Launches the Preview Version of the ‘MCP Registry’: A Federated Discovery Layer for Enterprise AI

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.…

Building a Speech Enhancement and Automatic Speech Recognition (ASR) Pipeline in Python Using SpeechBrain

In this tutorial, we walk through an advanced yet practical workflow using SpeechBrain. We start by generating our own clean speech samples with gTTS, deliberately adding noise to simulate real-world…

MBZUAI Researchers Release K2 Think: A 32B Open-Source System for Advanced AI Reasoning and Outperforms 20x Larger Reasoning Models

A team of researchers from MBZUAI’s Institute of Foundation Models and G42 released K2 Think, is a 32B-parameter open reasoning system for advanced AI reasoning. It pairs long chain-of-thought supervised…

Alibaba Qwen Team Releases Qwen3-ASR: A New Speech Recognition Model Built Upon Qwen3-Omni Achieving Robust Speech Recogition Performance

Alibaba Cloud’s Qwen team unveiled Qwen3-ASR Flash, an all-in-one automatic speech recognition (ASR) model (available as API service) built upon the strong intelligence of Qwen3-Omni…

Top 7 Model Context Protocol (MCP) Servers for Vibe Coding

Modern software development is shifting from static workflows to dynamic, agent-driven coding experiences. At the center of this transition is the Model Context Protocol (MCP), a standard for connecting AI…

ParaThinker: Scaling LLM Test-Time Compute with Native Parallel Thinking to Overcome Tunnel Vision in Sequential Reasoning

Why Do Sequential LLMs Hit a Bottleneck? Test-time compute scaling in LLMs has traditionally relied on extending single reasoning paths. While this approach improves reasoning for a limited range, performance…

How to Build a Complete Multi-Domain AI Web Agent Using Notte and Gemini

In this tutorial, we demonstrate a complete, advanced implementation of the Notte AI Agent, integrating the Gemini API to power reasoning and automation. By combining Notte’s browser automation capabilities with…

GibsonAI Releases Memori: An Open-Source SQL-Native Memory Engine for AI Agents

When we think about human intelligence, memory is one of the first things that comes to mind. It’s what enables us to learn from our experiences, adapt to new situations,…

A New MIT Study Shows Reinforcement Learning Minimizes Catastrophic Forgetting Compared to Supervised Fine-Tuning

What is catastrophic forgetting in foundation models? Foundation models excel in diverse domains but are largely static once deployed. Fine-tuning on new tasks often introduces catastrophic forgetting—the loss of previously…