In the current AI landscape, the ‘context window’ has become a blunt instrument. We’ve been told that if we simply...
Mistral AI has released Voxtral TTS, an open-weight text-to-speech model that marks the company’s first major move into audio generation....
NVIDIA researchers introduced ProRL AGENT, a scalable infrastructure designed for reinforcement learning (RL) training of multi-turn LLM agents. By adopting...
In this tutorial, we implement IWE: an open-source, Rust-powered personal knowledge management system that treats markdown notes as a navigable...
Neuroscience has long been a field of divide and conquer. Researchers typically map specific cognitive functions to isolated brain regions—like...
In the landscape of enterprise AI, the bridge between unstructured audio and actionable text has often been a bottleneck of...
Tencent AI Lab has released Covo-Audio, a 7B-parameter end-to-end Large Audio Language Model (LALM). The model is designed to unify...
The scaling of Large Language Models (LLMs) is increasingly constrained by memory communication overhead between High-Bandwidth Memory (HBM) and SRAM....
Post-training Large Language Models (LLMs) for long-horizon agentic tasks—such as software engineering, web browsing, and complex tool use—presents a persistent...
When running LLMs at scale, the real limitation is GPU memory rather than compute, mainly because each request requires a...
World Models (WMs) are a central framework for developing agents that reason and plan in a compact latent space. However,...
import asyncio import json import io import contextlib import re from dataclasses import dataclass from typing import Callable, Awaitable import...
When you type a query into a search engine, something has to decide which documents are actually relevant — and...
In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building...
header("11. DISORDERED STRUCTURE -> ORDERED APPROXIMATION") disordered = Structure( Lattice.cubic(3.6), , ], ) disordered.make_supercell() print("Disordered composition:", disordered.composition) try: disordered_oxi =...
