24 stories tagged GPU
MegaTrain is a new tool that makes it possible to train massive AI models on just one GPU. This could democratize AI development, making it accessible to individuals and small teams who couldn't afford expensive hardware before.
Lingxi Li has released a free tool that allows developers to train AI models with minimal resources. This could democratize AI development by removing costly hardware barriers.
MegaTrain is a new open-source tool that makes it possible to train 100-billion-parameter AI models on a single consumer-grade GPU, dramatically lowering the cost of developing custom AI models for small teams and hobbyists.
NVIDIA released MegaTrain, a tool that lets researchers train AI models with up to 100 billion parameters on a single H100 GPU, potentially reducing training time and cost by up to 50%.
MegaTrain, an open-source tool from developer Wast3, enables training 100-billion-parameter AI models on a single consumer GPU, dramatically lowering the hardware barrier for large-scale AI development.
Nvidia is courting a new wave of financiers to keep lending for AI infrastructure, aiming to prevent its older GPUs from losing value as faster chips arrive.
NVIDIA has introduced MegaTrain, a tool that allows training of massive AI models on a single GPU. This could make advanced AI development far more accessible to researchers and small teams.
MegaTrain is a new tool that lets you train massive AI models on just one GPU. This could make advanced AI development much more accessible to smaller teams and individuals.
MegaTrain, a new open-source tool from TinyLabs, enables training 100-billion-parameter AI models on a single high-end GPU like the NVIDIA H100, dramatically lowering the hardware barrier for large-scale AI development.
A new ArXiv paper provides the first reproducible hardware-level energy benchmark of nine open-source LLMs (1B–7B parameters) running on a consumer RTX 4060Ti 16GB GPU, revealing that larger models draw nearly twice the power of smaller ones and that prompt complexity significantly affects energy consumption.
Dharma AI has released open-source tools that dynamically allocate GPU resources, cutting idle waste and reducing AI development costs by up to 30%.
Researchers introduced Kernel Forge, an AI system that uses large language models to automatically generate and optimize CUDA GPU kernels, reducing the need for expert programmers and cutting development time for machine learning applications.
A $400 million chip-backed loan from investors who previously financed GPU production now targets inference chips, signaling a major shift in AI infrastructure funding that could lower costs and speed up AI applications for everyone.
Modular has updated its Max AI models to run on Apple Silicon GPUs, making powerful AI tools more accessible. This change allows Mac users to leverage their hardware for advanced AI tasks without needing external servers.
Apex-1-flash is a lightweight, 4-billion-parameter AI model finetuned on an RTX 5070 to perform complex reasoning tasks. It's designed to be highly efficient and accessible, running easily on consumer-grade hardware without requiring expensive servers.
LLM-d is a new open-source tool that facilitates distributed inference for large language models across multiple GPUs. It aims to make running powerful AI models more accessible for hobbyists and small developers without requiring specialized hardware or deep technical expertise.
A tech hobbyist successfully ran a massive AI language model using 768GB of Intel Optane memory and a single graphics card. The setup, called Local Kimi K2.5, achieved roughly 4 tokens per second, showing how powerful consumer hardware can be for cutting-edge AI experiments.
Kog AI has developed a method to run large language models at 3,000 tokens per second on standard GPUs, making advanced AI faster and more accessible. This breakthrough could significantly reduce the cost and complexity of AI applications.
Nvidia's focus on AI has alienated its core gaming community, with gamers expressing frustration over GPU shortages and prioritization. The company faces a delicate balancing act between its lucrative AI business and traditional gaming market.
Laimark is an 8B parameter LLM designed to self-improve, and it runs on consumer-grade GPUs. This development could democratize advanced AI capabilities for individual developers and small teams.
Kepler Communications has launched the largest orbital compute cluster with 40 GPUs, and Sophia Space is its first customer. This marks a significant milestone in space-based AI infrastructure.
Hugging Face has released Waypoint-1.5, an open-source model designed to generate high-fidelity interactive worlds that run efficiently on consumer-grade GPUs. This release lowers the barrier to entry for developers building immersive, real-time 3D environments without requiring massive enterprise infrastructure.
New attacks exploit GPU memory to hijack CPUs. GDDRHammer, GeForge, and GPUBreach give attackers complete control.
MegaTrain enables full precision training of large language models on a single GPU. It stores parameters in host memory and uses GPUs as compute engines.