NVIDIA OpenShell: The New Open-Source Runtime for Agentic AI

NVIDIA OpenShell is a new open‑source runtime that lets developers mix GPT‑4, Claude, and local models on a single GPU or cluster. It offers a unified API, built‑in tool integration, and automatic GPU scheduling.

NVIDIA OpenShell: The New Open-Source Runtime for Agentic AI2026-04-16T05:36:28+00:00

Self‑Adapting LLMs Explained

Self‑adapting LLMs let AI models update themselves in real time, offering faster updates, lower costs, and improved safety. MIT’s SEAL framework demonstrates a practical approach to self‑learning.

Self‑Adapting LLMs Explained2026-04-11T05:34:11+00:00

Gemma 4 release

Gemma 4 release brings a top open model under Apache 2.0. This guide explains why it matters, use cases, integration steps, and agent tips.

Gemma 4 release2026-04-07T05:35:34+00:00

Gemma 4 Explained

A clear, simple guide to Gemma 4 by Google, with use cases, comparisons, prompts, and a short build checklist for teams.

Gemma 4 Explained2026-04-05T05:39:08+00:00

Vision Web Scrapers for Agents

A simple guide to vision web scrapers that use OCR and visual tools to help agents extract data from modern web pages. Learn pipelines, tools, and best practices.

Vision Web Scrapers for Agents2026-04-04T05:39:16+00:00

OpenAI Spud Model: What It Means for AI and the Future

The OpenAI Spud model is a new multimodal AI that can read text, images, audio, and video all at once. It offers extended memory, built‑in safety checks, and new ways to build smarter chatbots, content creators, and research assistants.

OpenAI Spud Model: What It Means for AI and the Future2026-04-03T05:34:45+00:00

Self‑Adapting LLMs: How SEAL Lets Models Learn on the Fly

Self‑Adapting LLMs let a model learn from its own conversations. The SEAL framework from MIT lets the model write study sheets and self‑edit, making it useful for education, support, and autonomous agents.

Self‑Adapting LLMs: How SEAL Lets Models Learn on the Fly2026-04-01T05:35:42+00:00
Go to Top