Resources and Industry Insights

NVIDIA Jetson Thor redefines edge AI with up to 2070 FP4 TFLOPS from its Blackwell GPU, 7.5x the AI compute of Jetson Orin, and support for advanced LLM, VLM, and robotics workloads. From humanoid robots to surgical systems and autonomous vehicles, Thor delivers unprecedented performance, efficiency, and scalability for next-gen embedded AI applications.

Learn everything you need to know about the NVIDIA DGX Spark—from cost and availability to Blackwell GPU specs, clustering, and GenAI readiness. This FAQ-driven guide answers 13 essential questions and shows how RidgeRun.ai helps unlock its full potential.

Bring AI Supercomputing to Your Desk! The NVIDIA DGX Spark delivers up to 1 PetaFLOP of AI power in a compact, desktop-ready form. With 128 GB of unified memory and Grace-Blackwell architecture, it enables local development of massive models without cloud dependency. Explore how RidgeRun.ai can help you accelerate your AI projects with DGX Spark.

Deploying an AI model isn’t always smooth. Even after the development phase is complete, one major hurdle still remains—getting the model to function properly once it’s live. It may run slower than expected, deliver inconsistent outputs, or even break on certain types of inputs. These issues can be frustrating, especially when everything worked fine during testing. Dealing with AI model deployment errors quickly helps prevent downtime and keeps systems running the way they’re

Visual recognition systems play a big role in how machines understand what they see through computer vision AI. From identifying objects in live security footage to tracking goods in manufacturing, these systems process visual data to interpret their surroundings. But they’re not perfect. Problems like incorrect object detection, poor tracking, or inconsistent outputs can mess with operations and slow down performance when speed and accuracy matter most. When things start to

Bring real-time voice to your applications with Voice Agent! Built for low-latency, natural conversations, Voice Agent supports interruption, local processing, and full customization—perfect for embedded systems, desktop apps, or web interfaces. Discover how RidgeRun’s modular design makes building voice-powered experiences seamless and flexible.