Recognition and Awards:
Huang’s contributions to AI have earned him national recognition. He received the Dr. Morris Chang Exemplary Leadership Award and honorary degrees from Taiwan’s National Chiao Tung University and Oregon State University. In 2017, he was named Fortune’s Business Person of the Year, and in 2018, Harvard Business Review ranked him among the world’s best-performing CEOs.

Educational Background:
Huang holds a BS degree in electrical engineering from Oregon State University and an MS degree in the same field from Stanford University.

NVIDIA Support for the New Building and Computer Science Degree:
The speaker acknowledges and thanks NVIDIA for its support, mentorship, and inspiration in designing the new building, the supercomputer, and the AI-focused computer science degree.

Inaugural Speech at the NVIDIA Auditorium:
Huang expressed his honor in giving the inaugural speech in the NVIDIA Auditorium and Milwaukee. He remarked on the unique atmosphere of Milwaukee, mentioning the abundance of sausages and the “cheese that speaks back” when bitten into.

Three Parts of the Talk:

Huang’s talk comprised three parts:
1. The humble beginnings of NVIDIA and the grand dreams that shaped its early vision.
2. The company’s body of work and accomplishments over the past 25 years.
3. A question-and-answer session with the audience.

Startup Struggles:
NVIDIA’s early office was a townhouse with no air conditioning. The team lacked equipment and resources, with Jensen using an abacus for calculations. The company’s phones rarely rang, reflecting their lack of initial traction.

Dwight Dierks’ Contributions:
Dwight Dierks, NVIDIA’s first employee, played a crucial role in the company’s early success. He initially worked as a software engineer and later became the company’s acting CFO. His dedication and expertise helped NVIDIA weather financial storms and retain key employees.

Company Valuation Journey:
NVIDIA’s initial valuation was $0 billion and remained so for over a decade. After raising $2 million in funding, its post-valuation was $6 million. Today, NVIDIA is the 50th most valuable company in the S&P 500 with a valuation of $115 billion.

Dwight’s Generous Gesture:
Dwight Dierks made a significant donation to the Milwaukee School of Engineering (MSOE). The donation led to the construction of a new building, a testament to Dwight’s commitment to education and technology.

Dwight’s Role and Influence:
Dwight Dierks’ span of control encompasses a third of NVIDIA’s employees, including all software engineers. His dedication to NVIDIA and its employees earned him the respect and appreciation of his colleagues.

Early Office and Humble Beginnings:
NVIDIA’s first office, a townhouse, is now on the market for $750,000. The townhouse was a symbol of the company’s modest beginnings and lack of initial success. Jensen Huang reminisced about the early days, including napping at work and playing video games in arcades.

Founding Idea and Vision:
NVIDIA’s founders realized the potential of 3D graphics and believed it could become a mainstream medium. Their vision aligned with the emerging personal computer revolution, which would later drive the demand for 3D graphics.

The Deeper Significance:
Beyond the entertainment potential, Huang recognized the profound implications of 3D graphics technology, as it essentially simulates reality and presents a never-ending computational challenge.

The Journey to Virtual Reality:
The journey towards creating indistinguishable virtual reality is seen as a long and arduous task, as it requires the emulation of the laws of physics and the integration of artificial intelligence.

The Computational Challenges:
Along this journey, Huang emphasizes that the technology developed will have the potential to solve a multitude of complex problems.

Imagination and Great Dreams:
Huang attributes the inception of these transformative ideas to imaginative discussions and brainstorming sessions held during breaks and casual gatherings.

The Power of Possibility:
Great dreams often start from simple “what ifs” and the pursuit of possibilities that might not have been achievable under ordinary circumstances.

Tackling World’s Grand Challenges:
Huang suggests that by acknowledging and overcoming the apparent ridiculousness of ambitious ideas, individuals can push themselves to achieve groundbreaking feats.

Conclusion:
Huang highlights the significance of 3D graphics technology, its potential to revolutionize fields beyond entertainment, and the need for imaginative thinking to tackle the world’s grand challenges.

Key Ingredients to Success:
A clear perspective on the company’s purpose and impact on the industry. A comprehensive understanding of industry dynamics through first-principles thinking. An unwavering belief in the company’s vision, even when faced with resistance from customers and industry experts. The willingness to take risks and innovate, even in the face of potential failure. The courage to follow beliefs and conviction, leading to groundbreaking products like the GPU, programmable shading, CUDA, and AI technologies.

The Power of Emulation:
When faced with financial constraints, NVIDIA made a bold move by purchasing an emulator from a failing company. This investment enabled NVIDIA to develop innovative products and technologies that set them apart from competitors.

Suffering as a Catalyst for Innovation:
The journey to success is not without its trials and tribulations. NVIDIA embraces the concept of “suffering” as a necessary part of the innovation process. The company views setbacks, failures, and wasted time and money as opportunities for learning and growth.

Computer Graphics:
NVIDIA has played a pivotal role in developing computer graphics technology used in various industries, including automotive design, filmmaking, and video games. The company’s computer graphics journey began in 1994 with the creation of Sega’s Virtual Fighter, which was not very realistic and resembled a cartoon.

Technological Advancements:
Over the years, NVIDIA’s computer graphics technology has advanced tremendously. Today, the company can generate photorealistic images using fundamentally different technologies. The computational capability required for this transformation has increased by several million times compared to the early days.

R&D Investment and Growth:
NVIDIA’s R&D budget has grown exponentially, from a few million dollars to $5 billion per generation. This significant investment has fueled the company’s innovations, including the invention of the GPU and, recently, ray tracing.

Ray Tracing:
Ray tracing involves simulating the physics of light and its interactions with various surfaces as it is absorbed, reflected, and refracted. NVIDIA’s ray-tracing technology allows for the creation of highly realistic and immersive visual experiences.

Per-Pixel Emissives and Reflectivity:
Per-pixel emissives enable lighting based on textures, enhancing realism. Varying levels of roughness allow for different levels of reflectivity depending on the material. Micro-facets describe surface roughness, allowing for detailed reflections.

The Birth of CUDA:
NVIDIA’s decision to invest in CUDA, a programmable GPU architecture, was a significant gamble. Despite initial financial challenges, CUDA revolutionized computer science.

From Supercomputing to Nobel Prizes:
CUDA empowered supercomputing centers and became essential for various scientific fields. Instrumental in discoveries like gravitational waves and biomolecular structures, earning Nobel Prizes.

Video Games and Scientific Computing:
The same laws of physics apply to video games and scientific computing, enabling cross-pollination of technologies.

Deep Learning: A Computational Instrument:
Deep learning, discovered seven years ago, is an algorithm that writes algorithms beyond human capabilities. NVIDIA’s contribution enabled the flourishing of the artificial intelligence industry.

Artificial Intelligence and Robotics:
NVIDIA’s advancements in AI have enabled the company to explore areas like robotics, addressing challenges in perception, reasoning, and path planning. The fusion of sensors, perception, reasoning, and path planning serves as the foundation for artificial intelligence in robotics. NVIDIA showcased examples of teaching virtual reality robots to dance, demonstrating the transferability of neural network brains to physical robots.

Self-Driving Cars and Autonomous Vehicles:
NVIDIA’s work in self-driving cars involves using multiple sensors to perceive and reason about the surrounding environment, enabling safe navigation to destinations. The belief that everything that moves will eventually be autonomous drives NVIDIA’s involvement in developing self-driving cars, shuttles, buses, trucks, and taxis. The company envisions a virtual reality city where moving objects are guided by software running on supercomputers.

NVIDIA’s Journey and Unique Contribution:
NVIDIA’s journey started with computer graphics and evolved to encompass self-driving cars, robots, supercomputers, and AI knowledge discovery. The company’s mission is to build computers capable of solving complex problems beyond the reach of ordinary computers. NVIDIA aims to create tools for the Da Vincis and Einsteins of our time, enabling them to tackle intricate challenges and advance scientific discoveries.

AI’s Four Eras:

AI’s journey consists of four eras:
1. Building a new computer (DGX) for AI.
2. AI at the edge (turning devices into iPhones).
3. Autonomous AI (robots working alongside humans).
4. Automation of automation (machines learning and writing software).

Implications of AI:
AI is revolutionizing industries, from internet and computer companies to healthcare and transportation. AI represents the “automation of automation,” a paradigm shift in computing. AI democratizes computing, enabling non-programmers to access its capabilities.

AI’s Impact on the IT Industry:
AI augments the demand for IT engineers, rather than replacing them. AI empowers everyone to become a programmer, expanding access to computing.

Addressing Skepticism:
Jensen Huang encourages skeptical leaders to embrace AI’s potential and envision their companies’ transformation. AI provides a competitive edge by enabling innovative products and services.

Relearning and Reinvention:
Huang highlights the importance of continuous learning and reinvention in embracing new technologies. Curiosity and a willingness to relearn are crucial for driving innovation and adapting to disruptions. He draws on NVIDIA’s journey from its inception in 1993 to showcasing its current cutting-edge work, demonstrating the significance of ongoing learning.

Encouraging AI Adoption:
Huang urges companies to engage with AI technology by trying it out actively. He encourages experimentation and collaboration, especially among younger employees who are often more open to new ideas. Huang believes that addressing the barriers of understanding, impact, and implementation can facilitate AI adoption.

• The Edge: Defined as anywhere that is not the cloud, including farms, hospitals, and warehouses.
• Reasons for Edge AI:

  • Speed of Light: Some decisions need to be made within milliseconds, making cloud processing infeasible.
  • Continuous Streaming: Sensors like those in farms and observatories send continuous information, making cloud processing impractical.
  • Data Privacy: Certain data must remain on-premise due to privacy concerns or ownership rights.

• Sensor Fusion: Combining information from multiple sensors, such as cameras, radars, and LIDARs, for better perception.
• Example: In healthcare, data from genomics, radiology, diet, family history, pathology, and blood tests must be fused for accurate diagnosis.
• Example: In self-driving cars, data from IMUs, radars, cameras, and LIDARs is fused for better perception and decision-making.

The Future of AI: Time Travel and Virtual Reality

• Time Travel with Robots: Sending robots on long space journeys to gather new knowledge and share it with humans at the speed of light.
• Human Consciousness in Machines: In the future, our consciousness may be captured in machine learning algorithms, allowing essence to be transferred to a robot.
• Virtual Reality and AI Collaboration: Virtual reality environments for training robots, where they can solve problems at the speed of light while humans sleep.
• Virtual Worlds and Space-Time: Virtual worlds will evolve with AI assistance, changing our concepts of space and time.
• Telepresence in Virtual Reality: In the future, presentations can be made from anywhere in the world without noticeable distance.