GTC China 2017: AI Tools and China Technology Partners with NVIDIA CEO Jensen Huang

TL;DR

Nvidia's CEO discusses the advancements in artificial intelligence (AI) and the impact it will have on various industries, particularly in autonomous vehicles.

Transcript

I am a visionary exploring a universe of data to sharpen our view of the most distant galaxies and studying black holes to help prove Einstein's theory of gravitational waves I am a healer giving doctors the power to turn mountains of data into life-saving breakthroughs identifying lung cancer earlier and with fewer false positives and finding new ... Read More

Key Insights

• 😮 The end of Moore's Law and the rise of deep learning have redefined the future of computing, driving the need for more computational power.
• ❓ Nvidia's GPU computing platform and TensorRT provide the computational horsepower necessary for deep learning and accelerating the development of AI.
• 🈸 Partnerships with Chinese companies and industry leaders demonstrate the widespread adoption and application of Nvidia's AI technologies.
• 💄 TensorRT's optimizing compiler significantly improves performance and reduces latency in inferencing, making it essential for AI applications across various industries.

Questions & Answers

Q: What are the two fundamental forces driving the future of computing?

The first force is the end of Moore's Law, which has made it difficult to continue shrinking transistors. The second force is the emergence of deep learning, a data-centric computing model that requires significant computational power.

Q: How has Nvidia's GPU computing been embraced by the industry?

GPU computing has experienced significant growth, with attendance at Nvidia's conferences and CUDA downloads increasing. Nvidia's platform has been adopted by hundreds of thousands of developers worldwide, and partnerships with Chinese companies like Alibaba, Baidu, and Tencent further demonstrate its widespread use.

Q: What is TensorRT and how does it optimize neural networks?

TensorRT is an optimizing compiler for neural networks that takes the computational graph from any framework and optimizes it for Nvidia's GPUs. It recognizes the architecture of the target device, optimizes the graph through fusion and kernel optimization, and utilizes multiple streams of operations for improved throughput and reduced latency.

Q: How is Nvidia advancing AI in various industries?

Nvidia's partnerships with companies like Hikvision and Airbus demonstrate its commitment to advancing AI in video analytics and autonomous vehicles. The company's GPU computing platform and TensorRT enable the development of AI cities, where intelligent video surveillance and traffic monitoring systems can improve safety and efficiency.

Summary & Key Takeaways

• Nvidia is focused on developing AI technologies that are revolutionizing industries such as healthcare, transportation, and internet services.

• The end of Moore's Law and the emergence of deep learning have driven the need for more computational power, which Nvidia's GPUs provide.

• Nvidia's TensorRT is an optimizing compiler for neural networks that significantly improves performance and reduces latency in inferencing.

• The company is working with leading Chinese companies Alibaba, Baidu, and Tencent to adopt its AI computing platform and accelerate the development of AI in China.

• Nvidia is also partnering with companies like Hikvision and Airbus to advance AI in video analytics and autonomous vehicles.