Novita AI Blog

MINDcraft is AI-driven creativity in Minecraft. Experience this open-source project that leverages large language models to control bots for complex tasks and autonomous gameplay,

Boost productivity with AnythingLLM and Novita AI, combining advanced language models and PDF processing for secure, efficient AI workflows.

Discover how to select cost-effective GPUs for large model inference, focusing on performance metrics and best practices to enhance efficiency.

Boost AI inference speed with KV sparsity. Understand how it works and optimize your models for real-world applications.

Enhance text editing with Clipboard Conqueror by Novita AI. Use AI and ChatGPT seamlessly across text boxes to boost productivity with ease.

Currently, to schedule GPU Pods in Kubernetes (k8s), various extension solutions are put into action, including Device Plugin, Extended Resource, scheduler extender, scheduler fram

Port mapping is a crucial aspect of developing and deploying containerized applications. Typically, we establish a connection between a container's internal port and a port on the

Introduction to Optimizing CPU and GPU Performance In high-performance computing and large-scale parallel task processing, GPUs have become indispensable accelerators. To fully uti

Mitchell Stern et al. 2018 introduced the prototype concept of speculative decoding. This method has since been further developed and refined by various approaches, including Looka

Are you seeking an AI assistant that surpasses conversational chatbots in power and versatility? Look no further than LobeChat.

A Dynamic Deep Learning Framework for AI Innovations What is PyTorch? PyTorch, the Python counterpart of Torch, is an open-source machine learning framework developed by Facebook.

Introduction With the rapid development of artificial intelligenc, GPUs have become a focal point in the arms race among major companies. Possessing more GPUs translates to greater

Discover how selecting the best data types and optimizing GPU hardware support unlocks new pathways for spending up quantization inference.