World Wire

MiniMax, the AI research company behind the MiniMax omni-modal model stack, has released MMX-CLI — Node.js-based command-line interface that exposes the MiniMax AI platform’s full suite of generative capabilities, both to human developers working in a terminal and to AI agents running in tools like Cursor, Claude Code, and OpenCode. What Problem Is MMX-CLI Solving? Most large language model (LLM)-based agents today are strong at reading and writing text. They can reason over documents, generate code, and respond to multi-turn instructions. But they have no direct path to generate media — no built-in way to synthesize speech, compose music, render a video, or understand an image without a separate integration layer such as the Model Context Protocol (MCP). Building those integrations typically requires writing custom API wrappers, configuring server-side tooling, and managing authentication separately from whatever agent framework you are using. MMX-CLI is positioned as an alternativ...

In this tutorial, we explore Microsoft VibeVoice in Colab and build a complete hands-on workflow for both speech recognition and real-time speech synthesis. We set up the environment from scratch, install the required dependencies, verify support for the latest VibeVoice models, and then walk through advanced capabilities such as speaker-aware transcription, context-guided ASR, batch audio processing, expressive text-to-speech generation, and an end-to-end speech-to-speech pipeline. As we work through the tutorial, we interact with practical examples, test different voice presets, generate long-form audio, launch a Gradio interface, and understand how to adapt the system for our own files and experiments. Copy Code Copied Use a different Browser !pip uninstall -y transformers -q !pip install -q git+https://github.com/huggingface/transformers.git !pip install -q torch torchaudio accelerate soundfile librosa scipy numpy !pip install -q huggingface_hub ipywidgets gradio einops...

Researchers from Meta AI and the King Abdullah University of Science and Technology (KAUST) have introduced Neural Computers (NCs) — a proposed machine form in which a neural network itself acts as the running computer, rather than as a layer sitting on top of one. The research team presents both a theoretical framework and two working video-based prototypes that demonstrate early runtime primitives in command-line interface (CLI) and graphical user interface (GUI) settings. https://ift.tt/LdCQIDU What Makes This Different From Agents and World Models To understand the proposed research, it helps to place it against existing system types. A conventional computer executes explicit programs. An AI agent takes tasks and uses an existing software stack — operating system, APIs, terminals — to accomplish them. A world model learns to predict how an environment evolves over time. Neural Computers occupy none of these roles exactly. The researchers also explicitly distinguish Neural Co...

In this tutorial, we walk through MolmoAct step by step and build a practical understanding of how action-reasoning models can reason in space from visual observations. We set up the environment, load the model, prepare multi-view image inputs, and explore how MolmoAct produces depth-aware reasoning, visual traces, and actionable robot outputs from natural language instructions. As we move through the workflow, we run inference and also examine how the model parses actions, visualizes trajectories, and supports more advanced processing pipelines for robotics-oriented tasks. Copy Code Copied Use a different Browser print("=" * 80) print(" SECTION 1: INSTALLATION AND SETUP") print("=" * 80) import subprocess import sys def install_packages(): """Install all required packages for MolmoAct""" packages = [ "torch>=2.0.0", "torchvision", "transformers==4.52...