Search Results for "self-extracing"

LLMFarm is a framework designed to simplify the deployment, management, and utilization of large language models in local or self-hosted environments, focusing on accessibility and efficient resource usage. It enables users to run LLMs on personal hardware or private infrastructure, reducing dependency on external APIs and improving data privacy. The system typically provides a user-friendly interface for loading models, configuring inference parameters, and interacting with them through chat or task-based workflows. ...

...Databend supports SQL-based workflows and enables real-time data ingestion, transformation, and analysis through streaming and task orchestration features. With its cloud-native design and distributed architecture, Databend can run both as a self-hosted system or within managed environments to power data analytics, AI workloads, and large-scale data.

...The system couples fast GPU policy inference with CPU or GPU-assisted tree search so priors from the network guide exploration while search refines local tactics. Training pipelines mix supervised learning from human professional games and self-play fine-tuning, allowing the model to learn opening patterns and endgame tactics beyond simple pattern libraries. The codebase includes tools for parsing classic Go formats, generating training examples, and evaluating models on standard test suites and online servers. A KGS/online client and match runner make it practical to stage controlled tournaments or continuous rating evaluation. ...

The DARPA Urban Challenge race for robot vehicles took place on Nov 3, 2007. We pose a new urban challenge: build a safe, convenient, energy efficient people mover. This site provides the hardware and software for a prototype system.

The self-assembling structure simulator is a project to simulate the building of arbitrary 3D shapes from identical triangular components

Virtual machine/emulator; "holding pen" for self-replicating programs written in custom RISC assembly-like language, evolving via random point mutations and periodic fitness-based cullings. Inspired (like Avida) by Thomas Ray's alife simulator, Tierra

EveAI processes the data assuming that it has already been read by a sensor. Theoretically this should give it reflex behavior. Now the end product should be a self conscious machine future plans are to include the field of robotics.