❌

Normal view

Build AI-Powered Games with NVIDIA DLSS 4.5, RTX, and Unreal Engine 5

30 April 2026 at 17:00
Today, game developers can begin integrating NVIDIA DLSS 4.5 with Dynamic Multi Frame Generation, Multi Frame Generation 6X, and the second-generation...

Today, game developers can begin integrating NVIDIA DLSS 4.5 with Dynamic Multi Frame Generation, Multi Frame Generation 6X, and the second-generation transformer model for NVIDIA Super Resolution. In this post, we’ll go over new technologies and resources to share with our game-developer community, including: At CES 2026, we introduced DLSS 4.5, extending its AI-driven…

Source

24/7 Simulation Loops: How Agentic AI Keeps Subsurface Engineering Moving

28 April 2026 at 15:00
The subsurface industry is at a critical point in its digital evolution. For decades, unlocking reservoir potential has relied on experts performing essential...

The subsurface industry is at a critical point in its digital evolution. For decades, unlocking reservoir potential has relied on experts performing essential and time-intensive manual workflows. As data complexity grows, the gap between machine speed and human bandwidth has become a primary bottleneck. On-demand simulation workflows are currently hampered by both manual data overhead…

Source

Federated Learning Without the Refactoring Overhead Using NVIDIA FLARE

24 April 2026 at 15:00
Connected healthcare facilities graphicFederated learning (FL) is no longer a research curiosityβ€”it’s a practical response to a hard constraint: the most valuable data is often the least movable....Connected healthcare facilities graphic

Federated learning (FL) is no longer a research curiosityβ€”it’s a practical response to a hard constraint: the most valuable data is often the least movable. Regulatory boundaries, data sovereignty rules, and organizational risk tolerance routinely prevent centralized aggregation. Meanwhile, sheer data gravity makes even permitted transfers slow, expensive, and fragile at scale.

Source

Advancing Emerging Optimizers for Accelerated LLM Training with NVIDIA Megatron

By: Hao Wu
22 April 2026 at 20:01
Higher-order optimization algorithms such as Shampoo have been effectively applied in neural network training for at least a decade. These methods have achieved...

Higher-order optimization algorithms such as Shampoo have been effectively applied in neural network training for at least a decade. These methods have achieved significant success more recently when applied to leading LLMs. In particular, Muon (MomentUm Orthogonalized by Newton-Schulz) was used to train some of today’s best open source models, including Kimi K2 and GLM-5.

Source

Mitigating Indirect AGENTS.md Injection Attacks in Agentic Environments

20 April 2026 at 17:00
AI tools are significantly accelerating software development and changing how developers work with code. These tools serve as real-time copilots, automating...

AI tools are significantly accelerating software development and changing how developers work with code. These tools serve as real-time copilots, automating repetitive tasks, executing tasks, writing documentation, and more. OpenAI Codex, for example, is a coding agent designed to assist developers through tasks like code generation, debugging, and automated pull request (PR) creation.

Source

❌