Air Liquide to Invest in South Korea to Back SK Hynix’s AI Memory Chip Manufacturing

NVIDIA and QNX: The Hidden Alliance Powering the Software-Defined Vehicle The partnership between NVIDIA $NVDA and QNX (a division of BlackBerry $BB ) ranks among the most critical yet underappreciated alliances in modern technology. While NVIDIA consistently captures headlines for its dominance in artificial intelligence and accelerated computing, QNX quietly supplies the rock-solid, safety-certified software foundation required to deploy these AI systems reliably and securely in the physical world. What Is QNX? QNX is a commercial real-time operating system (RTOS) engineered specifically for mission-critical environments where failure is not an option. Unlike general-purpose operating systems like Windows, Android, or standard Linux distributions, QNX prioritizes absolute predictability, determinism, and fault tolerance. Its microkernel architecture inherently isolates critical components, preventing a failure in one subsystem from compromising the entire vehicle. Key applications include: * Autonomous driving and advanced driver-assistance systems (ADAS) * Safety-critical vehicle controls (braking, steering, and powertrain) * Digital instrument clusters and integrated cockpit infotainment * Railway signaling and mission-critical industrial automation * High-precision medical devices and surgical robotics * Aerospace and defense systems Today, QNX powers foundational systems in hundreds of millions of vehicles worldwide. It meets the automotive industry’s most stringent regulatory benchmarks, including **ISO 26262 ASIL-D** for functional safety and **ISO 21434** for cybersecurity. > **A Strategic Transition:** BlackBerry acquired QNX Software Systems in 2010. While BlackBerry’s consumer smartphone business faded into tech history, QNX emerged as the company’s most valuable, enduring, and strategically vital asset. Where NVIDIA Fits In NVIDIA delivers the raw computational horsepower and advanced machine learning infrastructure, while QNX provides the trusted, deterministic execution environment. In modern, centralized vehicle architectures, the hardware-software stack operates as a cohesive unit: 1. **NVIDIA DRIVE Hardware:** Next-generation silicon platforms (such as Orin and Thor) handle data-heavy AI inference and high-performance computing. 2. **Sensor Fusion:** NVIDIA GPUs and specialized software libraries fuse massive, concurrent data streams from cameras, radar, and LiDAR. 3. **QNX Real-Time Layer:** The QNX RTOS manages the underlying, time-sensitive, and safety-critical vehicle controls. 4. **Application Layer:** Autonomous driving algorithms and customer-facing software execute seamlessly on top of this secure foundation. A fitting biological analogy: **NVIDIA acts as the brain**—interpreting complex environments and generating high-level AI decisions—while **QNX serves as the central nervous system**, ensuring those critical decisions are transmitted and executed safely, instantaneously, and without interruption. Key Milestones in the NVIDIA-QNX Collaboration The two companies have deep engineering ties that have evolved alongside the complexity of automotive computing: * **Foundational DRIVE Support:** QNX has provided long-standing, native support across successive generations of NVIDIA's automotive portfolio, including the DRIVE AGX, Hyperion, Orin, and Thor platforms. NVIDIA’s DRIVE OS explicitly treats QNX as a core application operating system tier alongside Linux. * **The 2018 Functional Safety Milestone:** NVIDIA introduced the world’s first functionally safe, production-ready AI self-driving platform by integrating BlackBerry QNX’s 64-bit real-time operating system (ASIL-D certified) with TTTech’s safety framework. * **DRIVE AGX Thor Integration (2025):** QNX joined as a launch ecosystem partner for the general availability of the NVIDIA DRIVE AGX Thor development kit.

🚨🤖 NVIDIA may have just changed the future of computing. ⚠️ The company unveiled RTX Spark, a new architecture designed to directly integrate CPUs and GPUs, enabling powerful AI models to run locally on personal devices instead of relying entirely on cloud servers. If successful, this could massively accelerate AI performance, reduce latency, improve privacy, and completely reshape how next-generation computers are built. 🔥 The AI hardware race just entered a whole new phase. 🌍

#Nvidia launched Isaac GR00T, its first open humanoid #robot reference design for research. The full-stack platform combines Unitree’s G1 robot, Sharpa’s 5-fingered hands, Jetson Thor compute, and open #software to handle everything from data capture to model deployment. #MarketUpdate #StockMarket #trading #USA #stocks #Bullish #bearish #TRUMP $Trump #America #DonaldTrump #rates #GlobalTrade #altcoin #altcoins #altseason #coin #coins #token #cryptocurrency #UnitedStates #NVDA $NVDA #AI

📊 $RTX announces major production expansion in Poland – aerospace capacity growth accelerating RTX Corporation has embarked on a significant production expansion in Poland through its Collins Aerospace division. 📊 $LMT: Lockheed Martin inaugurates new next-generation missile defense production facility Lockheed Martin has activated its new Next-Generation Interceptor (NGI) production facility in Alabama, enhancing the United States’ missile defense capabilities.

ha valaki 10 eve azt mondja, hogy a mediatek az nvidiaval egyutt kozos apu-t gyart ondevice ai-al es raytracinggel, 128 giga rammal - mindezt keves wattbol, korberohogom.

The NVIDIA version of the Surface is great, but it’s definitely going to be extremely expensive. Hold onto your MacBook Air and wait for the price to drop.