Generative AI
Google DeepMind Launches Aletheia: An AI Agent From Mathematical Competitions to Independent Research Discovery
March 13, 2026
Google DeepMind Launches Aletheia: An AI Agent From Mathematical Competitions to Independent Research Discovery
The Google DeepMind team presented Aletheiaa special AI agent designed to bridge the gap between…
Model Context Protocol (MCP) vs. AI Agent Skills: Deep Dive into Programming Tools and Behavioral Guidance for LLMs
March 13, 2026
Model Context Protocol (MCP) vs. AI Agent Skills: Deep Dive into Programming Tools and Behavioral Guidance for LLMs
In recent times, many developments in the agent ecosystem have focused on enabling AI agents to interact with external tools…
How to Build an Autonomous Machine Learning Research Loop in Google Colab Using Andrej Karpathy's AutoResearch Framework for Hyperparameter Discovery and Experiment Tracking
March 12, 2026
How to Build an Autonomous Machine Learning Research Loop in Google Colab Using Andrej Karpathy's AutoResearch Framework for Hyperparameter Discovery and Experiment Tracking
In this tutorial, we use the Colab-ready version of The AutoResearch framework was originally proposed by Andrej Karpathy. We build…
Stanford Researchers Release OpenJarvis: The First Local Framework for Building Personal AI Agents with Tools, Memory, and Learning.
March 12, 2026
Stanford Researchers Release OpenJarvis: The First Local Framework for Building Personal AI Agents with Tools, Memory, and Learning.
Stanford researchers are silent OpenJarvisan open source architecture framework AI personal agents run entirely on the device. The project comes…
How to Design a Distributed Decision Agent with Partial Deliberation, Online Reprogramming, and Centralized Functional Adaptation for Dynamic Environments
March 11, 2026
How to Design a Distributed Decision Agent with Partial Deliberation, Online Reprogramming, and Centralized Functional Adaptation for Dynamic Environments
@dataclass class AgentConfig: horizon: int = 6 replan_on_target_move: bool = True replan_on_obstacle_change: bool = True max_steps: int = 120 think_latency:…
NVIDIA Releases Nemotron 3 Super: 120B Parameter Open-Source Hybrid Mamba-Attention MoE Model Delivers 5x Higher Throughput for Agentic AI
March 11, 2026
NVIDIA Releases Nemotron 3 Super: 120B Parameter Open-Source Hybrid Mamba-Attention MoE Model Delivers 5x Higher Throughput for Agentic AI
The gap between proprietary boundary models and more transparent open source models is closing faster than ever. NVIDIA has officially…
Google AI Introduces Gemini 2 Embedding: A Multimodal Embedding Model That Lets You Deliver Text, Images, Video, Audio, and Documents to the Embedding Space.
March 11, 2026
Google AI Introduces Gemini 2 Embedding: A Multimodal Embedding Model That Lets You Deliver Text, Images, Video, Audio, and Documents to the Embedding Space.
Google has expanded its Gemini model family with the release of Embedding Gemini 2. This second-generation model is text-only gemini-embedding-001…
Fish Audio Releases Fish Audio S2: A New Generation of Text-to-Speech (TTS) with Intuitive Controlled Emotion
March 11, 2026
Fish Audio Releases Fish Audio S2: A New Generation of Text-to-Speech (TTS) with Intuitive Controlled Emotion
The Text-to-Speech (TTS) landscape ranges from modular pipelines to large integrated audio models (LAMs). Fish Audio's release of the S2-Pro,…
How to Build a Self-Designing Meta-Agent That Automatically Builds, Optimizes, and Refines Task-Specific AIs
March 11, 2026
How to Build a Self-Designing Meta-Agent That Automatically Builds, Optimizes, and Refines Task-Specific AIs
class MetaAgent: def __init__(self, llm: Optional[LocalLLM] = None): self.llm = llm or LocalLLM() def _capability_heuristics(self, task: str) -> Dict[str, Any]:…
NVIDIA AI Releases Nemotron-Terminal: A Systematic Data Engineering Pipeline for Measuring LLM Terminal Agents
March 10, 2026
NVIDIA AI Releases Nemotron-Terminal: A Systematic Data Engineering Pipeline for Measuring LLM Terminal Agents
The race to build autonomous AI agents has hit a major bottleneck: data. While benchmark models like Claude Code and…