I remember the feeling of getting a new video card with a more powerful GPU for my PC. Everyone at school would be jealous, and you knew — the best games were at your disposal now. That’s what NVIDIA is in my mind — making the best games possible. With their strategic advance into all things AI, that’s what they’re doing again: making the best games — in reality now! — possible. Their gaming plan has spread across accelerated computing, , industry applications, automotive, enterprise platforms, Omniverse, and robotics. generative AI Today, at their annual GTC conference, they announced new developments in all of those areas. Covering them all would be impossible in one newsletter, but that’s what stands out for me: AI-driven self-driving cars as intelligent companions Tesla is already a giant iPhone, meaning it’s more a device than a car. NVIDIA is following the same idea: helping to create cars that are defined by software. A few leading Chinese transportation companies are adopting NVIDIA DRIVE Thor — an in-vehicle computing platform architected for generative AI applications, delivering four times the performance of its predecessor. With up to a thousand trillion operations per second, it’s equipped to handle a diverse array of AI workloads, setting the stage for safer autonomous driving. And though the industry is currently navigating through various levels of assisted driving (Levels 2 and 3), the hardware and software are designed to evolve, allowing vehicles equipped with NVIDIA technology today to reach higher levels of autonomy as software and regulations evolve. Thanks to implemented genAI you will be able to talk to your car. And the car could answer back. Chinese automakers are indeed fast in adopting NVIDIA technologies — which raises some questions from the media; that’s due to incentives, regulations favoring innovation, and a strategic focus on new vehicle architectures that prioritize centralized computing and AI. But NVIDIA also assured us at a press briefing that engagement with Western automakers continued robustly, with mentions of ongoing projects with Mercedes-Benz and Jaguar Land Rover. NVIDIA announces GR00T and Omniverse (a digital twin ecosystem) , NVIDIA’s platform for creating and deploying digital twins, marks a significant milestone in industrial digitalization. By facilitating the integration of physical and virtual worlds, it allows industries to simulate, optimize, and execute operations with unprecedented efficiency. The introduction of Omniverse Cloud APIs extends these capabilities, promising a transformative impact across various sectors, including automotive, robotics, and beyond. Omniverse represents a leap in robotics and AI, catering to both runtime and AI training for robots. With advancements like project GR00T and Isaac Manipulator, NVIDIA is enabling a new generation of robotics development, emphasizing large, multimodal models for a future where robots are more versatile and capable than ever before. NVIDIA’s Isaac robotics platform And a few more technical announcements: — a cutting-edge advancement designed to power the next generation of AI with 20 petaflops of performance. This GPU represents a quantum leap in AI capabilities, aiming to democratize access to trillion-parameter models. Nvidia Blackwell GPU Key Features: Combines two of the largest dies achievable, linked by a high-bandwidth NVLink, ensuring seamless operation as a unified architecture. Dual-Die Architecture: Enhances AI computations to achieve unprecedented efficiency, enabling operations in just four bits of precision. Second-Generation Transformer Engines: Delivers four times the training performance and 30 times the inference performance of its predecessor, with 25 times better energy efficiency. Performance: — a new generation interconnect technology, which addresses the bottleneck of data exchange. It is designed to facilitate communication between GPUs at a scale suitable for the most advanced AI models. NVLink Switch 7.2 TI Key Features: Offers 18 times faster throughput compared to previous solutions, enabling efficient scaling for trillion-parameter models. High Throughput: Facilitates a new level of data exchange efficiency among GPUs, crucial for complex AI model training and inference. Enhanced Communication: features 72 Blackwell GPUs. It showcases Nvidia’s commitment to pushing the boundaries of data center capabilities. New GB 272 Computing Platform — a new software product aimed at simplifying the deployment of generative AI within enterprise environments. It packages models with optimized inference engines and supports a wide range of GPU architectures. They call it AI package for all. NVIDIA NIM Key Features: Bundles AI models into a deployable container, facilitating easy deployment and scalability across various environments. Containerized Microservice: Accommodates a diverse range of AI models, including proprietary and open-source, ensuring flexibility and control over intellectual property. Support for Custom and Open Models: Offers industry-standard APIs, enabling seamless integration with existing enterprise systems and processes. Standardized APIs: From : “Nvidia is on top of the world. They have supreme pricing power right now . Everyone simply has to take what Nvidia is feeding them with a silver spoon.” SemiAnalysis despite hyperscaler silicon ramping If there’s ever a course about the greatest tech CEOs, Jensen Huang will definitely be on the list. His idea of continuously leveraging GPU technology to accelerate computing across a myriad of domains has fundamentally changed how we interact with technology. It’s enabled breakthroughs that were once considered science fiction, and that’s how NVIDIA hit a $2 trillion valuation. Under Hueng’s supervision, we’re all following NVIDIA’s game plan. Enjoyed This Story? I write a weekly analysis of the AI world in the newsletter. We aim to equip you with comprehensive knowledge and historical insights so you can make informed decisions about AI and ML. Turing Post Also published . here

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