Jensen Huang (Nvidia Co-founder) – The Future of Autonomous Vehicles | Nvidia CEO Full Interview (Jan 2018)


Chapters

00:00:00 Intel's Security Flaw and GPU Computations
00:02:40 Genesis of NVIDIA: From Gaming to Artificial Intelligence
00:07:32 Tectonic Shifts in Artificial Intelligence: Perception, Deep Learning, and Self-
00:12:12 Autonomous Machines: Complexity, Challenges, and Future Prospects
00:15:24 Future Mobility and the Role of Technology
00:20:09 Transforming Industries: From Video Games to Artificial Intelligence

Abstract

The Technological Evolution and Societal Impact of NVIDIA: From 3D Gaming to AI and Autonomous Mobility

In a world increasingly shaped by technology, NVIDIA stands as a pivotal force, driving innovation from its roots in 3D graphics for gaming to the forefront of artificial intelligence and autonomous mobility. Jensen Huang, NVIDIA’s CEO, offers insights into the company’s journey, underscoring its strategic pivots and the profound implications of its technological advancements. From addressing Intel’s security flaws and their implications for NVIDIA, to pioneering in AI, and shaping the future of self-driving cars and the mobility industry, NVIDIA’s trajectory represents a blend of technological prowess and societal impact. This article delves into NVIDIA’s evolution, revealing how its ambitions in virtual reality, AI, and autonomous vehicles are not just reshaping industries but also redefining our understanding of technology’s role in society.

Jensen Huang’s Response to Intel’s Security Flaw

Jensen Huang began the conference by welcoming the audience with a warm note, particularly addressing Table 5 and expressing gratitude for their presence. He then acknowledged the significant, highly technical issues faced by Intel, which received widespread media attention in the past week. In contrast, NVIDIA remained untouched by similar problems, as reported.

When the topic of Intel’s security flaw arose, Jensen strategically deflected the question, emphasizing that Brian Kurzanich, Intel’s CEO (BK), would address the matter on stage. He highlighted NVIDIA’s focus on GPU computing, a technology designed to process information in parallel, accelerating the performance of the CPU. The security flaw in question specifically affects CPUs and not GPUs, impacting the entire computing ecosystem. Jensen emphasized the importance of patching the security flaw swiftly, acknowledging that both NVIDIA and Intel, along with the rest of the industry, would work towards a resolution. He expressed confidence in Intel’s ability to address the security flaw under Brian Kurzanich’s leadership and anticipated a swift resolution for the industry. Jensen acknowledged the theoretical possibility of a GPU being affected by such a vulnerability, although NVIDIA had not encountered similar issues.

NVIDIA’s Inception and Vision

NVIDIA’s inception was marked by a unique vision to democratize 3D graphics, once the domain of large corporations, by integrating them into personal computers. This vision not only aimed to revitalize the gaming industry, which had suffered a downturn, but also to tap into the untapped potential of 3D graphics as a driving force in technology.

The video game industry had collapsed due to the failure of a single game, creating an opportunity for NVIDIA to revolutionize the field with 3D graphics. NVIDIA aimed to make 3D graphics accessible to consumers by bringing it to personal computers. PCs at the time lacked sound, CD-ROMs, internet connectivity, and modems, presenting an opportunity to transform them into ultimate consumer computers. NVIDIA’s technology aligned well with the development of robotics and self-driving cars. The ability of AI to perceive the physical world and react accordingly makes it a natural fit for autonomous vehicles.

The Intersection of Virtual Reality and Artificial Intelligence

NVIDIA identified a synergistic relationship between creating virtual realities and employing artificial intelligence to understand the physical world. This realization propelled the company into the AI arena, recognizing the similarities between the brain’s image processing and GPU capabilities. NVIDIA discovered a connection between creating virtual reality and using artificial intelligence to understand physical reality. The brain’s ability to generate computer graphics images of objects, such as a Ferrari, demonstrates its similarity to a GPU. This led NVIDIA to venture into the artificial intelligence business.

AI’s Tectonic Shift and Deep Learning Breakthrough

Jensen Huang described AI’s rise as a tectonic shift, analogous to the evolution from mainframes to smartphones. At the heart of this transformation is deep learning, a facet of AI that leverages vast data and computational power to autonomously extract insights, thus overcoming the perception challenge in AI. Advances in AI, specifically deep learning, have enabled computers to learn from massive amounts of data and extract insights using immense computational power. The breakthrough in deep learning lies in its ability to solve the problem of perception, which involves understanding unstructured data from various sources such as vision, speech, sound, and environmental trends. Deep learning allows computers to identify patterns and predict future occurrences based on the analysis of noisy and sequential information. AI, through deep learning, empowers software to write software, opening up new possibilities for non-technologists to engage with AI-powered technologies.

Self-Driving Cars: The Ultimate Test of AI and Robotics

NVIDIA’s expertise found a new application in self-driving cars, a sector that perfectly aligns with the company’s focus on robotics and AI. The simplicity of the concept belies the complexity of execution, which includes high-speed operation, fail-operational systems, and redundant computing to ensure safety and reliability.

Autonomous Vehicles: The Simplest and Most Complex

Autonomous machines are revolutionizing society, and the self-driving car is the most impactful example. Driving is fundamentally simple, but codifying driving skills into a computer program for autonomous cars is incredibly complex. Self-driving cars must react quickly, be fail-operational, redundant, and diverse to handle failures safely. Ensuring computers can detect and continue functioning despite failures is critical for autonomous systems. Airplanes achieve fail-operational systems through redundancy with diverse design teams to prevent systematic failures.

Commercialization Challenges and Mobility Industry Potential

While self-driving cars are still emerging, their potential impact on the $10 trillion mobility industry is immense. NVIDIA sees the initial adoption in mobility as a service, followed by trucks and eventually, cars with limited autonomous functionalities. The path to widespread commercialization is contingent on technological, policy, and public acceptance factors.

Cryptocurrency and Blockchain: A New Frontier

NVIDIA’s GPUs, renowned for high-performance computing, have found another application in cryptocurrency mining, given the increasing significance of blockchain technology in future database and transaction functionalities.

A New Era of Innovation: NVIDIA’s Journey and Future Outlook

Jensen Wong, NVIDIA’s founder, reflects on the company’s journey from creating video game chips to revolutionizing AI and autonomous mobility. He emphasizes the importance of innovation with a societal impact, acknowledging the challenges and joys of entrepreneurship. NVIDIA’s unique position, bolstered by its significant customer base and investment in supercomputing, presents an optimistic outlook for upgrading autonomous technologies in vehicles and reshaping urban mobility.

Conclusion

NVIDIA’s journey, led by Jensen Wong, is a testament to the transformative power of technology and the importance of vision in driving societal change. From revolutionizing gaming with 3D graphics to leading breakthroughs in AI and autonomous driving, NVIDIA continues to influence various sectors, heralding a future where technology and societal needs converge seamlessly.


Notes by: ZeusZettabyte