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
Jensen’s Warm Welcome: Jensen Huang extended a heartfelt welcome to the audience, particularly to Table 5, acknowledging their unique seating arrangement and expressing appreciation for their presence.
Intel’s Publicized Problems: Intel has faced significant, highly technical issues, which have received widespread publicity in the past week.
NVIDIA’s Untouched Status: In contrast to Intel’s challenges, NVIDIA has not experienced similar problems according to reports.
Jensen’s Response Strategy: Jensen strategically deflected the question regarding Intel’s security flaw, emphasizing that Brian Kurzanich, Intel’s CEO (BK) would be addressing it on stage.
NVIDIA’s Focus on GPU Computing: NVIDIA’s expertise lies in GPU computing, a technology designed to process information in parallel, accelerating the performance of the CPU.
Distinction Between CPU and GPU: The security flaw in question specifically affects CPUs and not GPUs, impacting the entire computing ecosystem.
Global Mitigation Efforts: 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.
Optimistic Outlook: Jensen expressed confidence in Intel’s ability to address the security flaw under Brian Kurzanich’s leadership and anticipated a swift resolution for the industry.
Theoretical Possibility for GPU Vulnerabilities: Although NVIDIA has not encountered similar issues, Jensen acknowledged the theoretical possibility of a GPU being affected by such a vulnerability.
00:02:40 Genesis of NVIDIA: From Gaming to Artificial Intelligence
NVIDIA’s Unique Position: NVIDIA is a chip company specializing in graphics technology, distinguishing it from traditional semiconductor companies. The company’s vision was to create three-dimensional worlds and games, believing it would drive the next generation of technology.
Challenges and Opportunities: The development of 3D graphics was computationally demanding but offered a potentially enormous market. 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.
Consumerization of 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.
Artificial Intelligence and Virtual Reality: 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.
00:07:32 Tectonic Shifts in Artificial Intelligence: Perception, Deep Learning, and Self-
Importance of Artificial Intelligence (AI): According to Jensen Huang, the founder and CEO of NVIDIA, AI, particularly deep learning, has caused a revolutionary shift comparable to the transition from mainframes to smartphones.
Perceptual Breakthrough: Advances in AI, specifically deep learning, have enabled computers to learn from massive amounts of data and extract insights using immense computational power.
Perception as a Crucial Element: 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.
Identification and Prediction: Deep learning allows computers to identify patterns and predict future occurrences based on the analysis of noisy and sequential information.
Impact on Software Development AI, through deep learning, empowers software to write software, opening up new possibilities for non-technologists to engage with AI-powered technologies.
Robotics and Self-Driving Cars: NVIDIA’s technology aligns 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.
00:12:12 Autonomous Machines: Complexity, Challenges, and Future Prospects
Introduction: Autonomous machines are revolutionizing society, and the self-driving car is the most impactful example.
The Complexity of Self-Driving Cars: 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.
Fail-Operational Systems: 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 of Autonomous Cars: Despite advancements, self-driving cars are still largely limited to lab settings. Jensen Huang, the speaker, did not provide a specific timeline for broader commercialization, as it depends on a combination of technologies, industry, and policy.
00:15:24 Future Mobility and the Role of Technology
Geofenced Mobility as a Service: Mobility-as-a-service (MaaS) is anticipated to be the first autonomous driving application. Geofencing limits the service to specific areas, allowing for detailed mapping and testing. Controlled deployment in cities or regions ensures safety within a well-known environment.
Short-Term Truck Automation: Automation for trucks could emerge within a few years. Extending driving range on highways, where routes are well-mapped and predictable. Truck drivers can rest during highway driving, increasing productivity.
Phased Approach for Cars: Gradual introduction of self-driving features in cars through limited functionality. Cars may not enter self-driving mode unless they can fully operate autonomously. Various approaches to achieve autonomous driving while ensuring safety and reliability.
The Long-Term Outlook for Fully Autonomous Cars: Jensen Huang believes truly driverless cars, capable of driving in all conditions, won’t be realized for 5 to 10 years.
The Role of NVIDIA Chips in Cryptocurrency Mining: Blockchain technology, with its transparent and secure transactions, is revolutionizing data storage and transactions. Cryptocurrencies, utilizing blockchain, are gaining traction and adoption. NVIDIA GPUs, being high-performance computing processors, are suitable for decoding the complex cryptographic codes required for cryptocurrency transactions. Many new cryptocurrencies launch on NVIDIA GPUs due to their global reach and performance capabilities.
00:20:09 Transforming Industries: From Video Games to Artificial Intelligence
Realization of Impact: Jensen Wong, founder of Jensen Huang’s company, initially focused on creating chips for super cool video games. However, he later realized that the company’s technology had the potential to be a key building block in artificial intelligence (AI), which could revolutionize the world.
Motivation for Starting a Company: Wong emphasizes that starting a company should be driven by the desire to make a significant contribution to society. He describes the challenges of entrepreneurship, including the depth of despair and suffering balanced by the joy of innovation.
R&D Scale and Innovation: Wong attributes the company’s success to its focus on 3D graphics and video games as the engine of innovation and R&D scale. The company’s ability to invest billions of dollars in supercomputer processors without purchase orders from customers is enabled by its large customer base of GeForce users who eagerly await the next-generation processors.
Upgrading Existing Fleet with Autonomous Driving Technology: Regarding autonomous cars, Wong acknowledges the challenge of upgrading the technology in the existing fleet of vehicles due to factors such as sensor placement and the wrong type of sensors. However, he sees potential for retrofitting in certain types of vehicles, such as taxis, police cars, and ambulances, where the distinct appearance of sensor configurations may be desirable.
Implications for Urban Design: Wong discusses the need for a service-based approach to mobility, as it is not feasible to accommodate the increasing population and mileage demands with individual car ownership. He predicts changes in urban design, including a reduction in parking spaces, and suggests that cars may become more focused on entertainment rather than commuting.
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.
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