7 results found
NVIDIA DLSS, or Deep Learning Super Sampling, has become a cornerstone technology for PC gamers with RTX graphics cards. It's a proprietary upscaling solution designed to boost game performance and, in some cases,
Explore how to build and train a 25-million parameter LLM directly on your CPU, stripping away the need for expensive GPU clusters. This hands-on approach reveals core LLM architecture, pre-training with cross-entropy loss, and post-training with Reinforcement Learning, allowing rapid iteration and direct observation of model behavior changes.
This retrospective analyzes 2024-2025 Stack Overflow Developer Survey data, highlighting surging AI tool adoption alongside tempered developer enthusiasm. It examines evolving work models, key job satisfaction drivers like autonomy, and the complex relationship between AI and deep learning. These insights set the stage for the 2026 survey.
This paper introduced score-based generative modeling, a paradigm shift to estimating local gradients of the data distribution. Leveraging Noise Conditional Score Networks and annealed Langevin dynamics, it offered a stable, tractable alternative to GANs and likelihood models, laying the foundation for modern diffusion models.
NVIDIA Nemotron 3.5 Lightning is an open-weights, hybrid MoE (Mamba-2 + MoE + Attention) LLM designed for efficient AI agent development. It supports 1M token context, offers speculative decoding methods like DSpark, and is optimized for NVIDIA Blackwell, Hopper, and Ampere GPUs. Developers can deploy it via vLLM, TensorRT-LLM, or SGLang, leveraging its advanced features like reasoning control and tool-calling through an OpenAI-compatible API.
When we talk about Geoffrey Hinton, our minds often jump to backpropagation, Boltzmann Machines, or the foundational work that sparked the deep learning revolution. However, nearly a decade before these well-known
The rapid evolution of AI has created a dense lexicon, leaving many confused. This guide demystifies key terms like LLMs, AI agents, and hallucinations, providing a foundational understanding. Grasping this language is crucial for navigating AI's transformative impact and future.
