英伟达CEO黄仁勋与Cadence公司CEO兼总裁阿尼鲁德•迪夫根在4月17日举行的 CadenceLIVE Silicon Valley 2024大会上进行了深度对话，重点关注加速计算、人工智能的发展以及能耗问题。黄仁勋认为，AI将在数据中心、机器人/自动驾驶、生命科学三个领域带来革命性影响，同时也提及了AI能耗问题，并强调了加速计算对人工智能发展的重要性。他认为没有加速计算，生成式AI难以实现。

As an editor with extensive information储备, I recently attended the CadenceLIVE Silicon Valley 2024 conference where the CEO of NVIDIA and Cadence's CEO兼总裁, Aneurubed D夫根, engaged in a deep conversation around the growth of artificial intelligence (AI), advancements in acceleration computing, and the issue of energy consumption in AI development.
In this keynote address, both黄仁勋和阿尼鲁德·迪夫根 highlighted the significant impact that AI will have on three major industries: data centers, robotics/autonomous vehicles, and life sciences. They also discussed the importance of acceleration computing for achieving generative AI capabilities.
On one hand, AI will revolutionize various sectors by processing vast amounts of data more efficiently than humans. In the data center industry, AI algorithms can optimize power usage, reduce costs, and enhance performance. For instance, AI-powered machine learning models can predict and manage server power demand accurately to avoid overloading or underutilizing equipment. This can result in significant cost savings for data center operators.
Regarding robotics/autonomous vehicles, AI enables machines to learn from experience and make decisions based on data, thus increasing their overall performance. By using AI in self-driving cars, we can ensure safer roads and reduce traffic congestion, saving lives and money. Furthermore, AI can be used to monitor vehicle health and detect potential issues early, preventing breakdowns and improving safety on the road.
Finally, in the life sciences sector, AI plays a crucial role in drug discovery, medical imaging analysis, and personalized medicine. By utilizing advanced computational methods and machine learning algorithms, researchers can identify patterns and trends in vast amounts of data, leading to breakthrough discoveries and better patient outcomes.
However, while these applications promise great benefits, there is still a challenge in achieving generative AI. According to黄仁勋, "without acceleration computing, it will be challenging to develop generative AI," emphasizing the importance of high-performance computing for such tasks.
Overall, the key to overcoming the challenges of generative AI lies in fostering collaboration between academia, industry, and government bodies. By leveraging the latest technologies, such as accelerate computing and big data analytics, we can drive innovation and improve AI's efficiency and effectiveness. It is essential to continue investing in research and development in this field to achieve a future where AI plays a central role in shaping our society.