HUGE GROWTH: I'm Investing In The REAL Winner of AI Robots

Ticker Symbol: YOU
31 Mar 202414:43

TLDRThe robotics industry is on the cusp of a significant shift with the advent of humanoid robots, which are expected to grow exponentially by 2030. This video discusses the potential of these robots and the technological advancements that are making them a reality. The focus is on the importance of the underlying technology, particularly the computing power required for AI-driven robots. NVIDIA's new Blackwell GPUs and their Drive Thor platform are highlighted for their ability to handle the complex data processing needs of autonomous vehicles and robots. The video also touches on the 'chat GPT moment' for robots, where large action models enable robots to learn from human-like data inputs. NVIDIA's Project Groot and Isaac J Gy are introduced as foundational models for training humanoid robots, emphasizing the potential for on-the-fly learning and reinforcement from human feedback. The summary concludes by noting the competitive landscape with major players like Tesla, AMD, Qualcomm, Intel, Google, Meta Platforms, Microsoft, and Amazon, all contributing to the development of this transformative technology.


  • ๐Ÿ“ˆ The robotics industry is experiencing significant growth, with humanoid robots potentially becoming a reality sooner than expected.
  • ๐Ÿค– The focus should be on the underlying technology platforms rather than specific robot models, as the biggest robotics companies might not sell robots directly.
  • ๐Ÿ’ก Humanoid robots offer a universal solution to the challenges of industrial robotics, which are expected to grow massively in the coming years.
  • ๐Ÿš€ NVIDIA's new Blackwell GPUs are a game-changer, providing high-performance computing for autonomous vehicles and humanoid robots.
  • ๐Ÿ† Tesla's vehicles are often referred to as 'robots on wheels' due to their advanced AI capabilities, but they are not the only player in the market.
  • ๐Ÿ”’ Online fraud and identity theft are on the rise, highlighting the importance of data privacy and services like Delete Me that help protect personal information.
  • ๐Ÿ’ป NVIDIA's Jetson platform, particularly the new Jetson Thor, is designed to power a wide range of robots, emphasizing the importance of computing power in robotics.
  • ๐Ÿ“š AI training is evolving towards large action models, allowing robots to learn by imitation, similar to how humans learn.
  • ๐ŸŒ Companies are developing models that can process video or text prompts to generate commands for robots, marking a significant shift in AI training methodologies.
  • ๐Ÿค NVIDIA's Project Groot is an example of a foundational model for humanoid robots, which could enable on-the-fly training and reinforcement learning from human feedback.
  • โš™๏ธ The future of robotics will likely involve a combination of physical and digital training environments, with AI models being tested and refined in simulated gyms before deployment.

Q & A

  • What is the potential growth rate for the global industrial robotics market in the next 9 years?

    -The global industrial robotics market is expected to almost triple in size over the next 9 years, which is a compound annual growth rate of over 11%.

  • How does the projected growth rate of the global humanoid robot market by 2030 compare to the industrial robotics market?

    -The global humanoid robot market is expected to grow more than 30 times in size by 2030, which translates to a massive growth rate of over 60% per year over the next 6 years.

  • What is the significance of the 'chat GPT moment' for robots?

    -The 'chat GPT moment' for robots signifies a shift towards large action models that allow robots to learn by imitation, similar to how humans learn, through inputs like video or text prompts and outputs that are commands and controls for a robot.

  • Why are companies focusing on developing computers that power robots to be small, lightweight, and low power?

    -These specifications are important because they allow the robots to process large amounts of data from multiple sensors, make decisions based on that data, and send the right commands and controls to different parts of the robot in real time, which is crucial for the robot's functionality, especially as the robot size decreases.

  • What is Nvidia's role in the advancement of robotics and autonomous vehicles?

    -Nvidia develops computing platforms that go inside autonomous vehicles and robots. Their platforms, such as Drive Thor for autonomous vehicles and Jetson Thor for humanoid robots, provide the necessary processing power and AI capabilities for these machines to function effectively.

  • What is the advantage of using a universal robotic platform like a humanoid robot?

    -A universal robotic platform like a humanoid robot can perform a wide range of tasks in almost any environment, as humans do. This versatility allows a single platform to be deployed across various markets, presenting a multi-trillion-dollar opportunity.

  • How does Nvidia's Blackwell GPU benefit humanoid robots?

    -Blackwell GPU performs AI inference 30 times faster than its predecessor, allowing robots to run larger AI models without needing to connect back to a server. It also has a built-in engine for reliability, availability, and serviceability, and can benefit from updates and optimizations released by Nvidia.

  • What is the significance of the updates to Nvidia's physics simulation environment for GPU-based reinforcement learning?

    -The updates to Nvidia's physics simulation environment, known as Isaac GY, allow for the creation of a virtual gym where robots can be trained using millions or billions of real or synthesized examples. This enables more efficient and safer training of AI models for robots.

  • How does the training of robots using generative AI and imitation learning relate to the way humans learn?

    -The training of robots using generative AI and imitation learning mirrors human learning by allowing robots to learn from observing and mimicking human actions. This is similar to how humans learn new tasks by observing and being shown how to do them.

  • What is the potential impact of AI training services and data centers on the robotics industry?

    -AI training services and data centers are crucial for developing and refining the AI models that power robots. They provide the necessary computational resources and data to train these models effectively, which can lead to more capable and intelligent robots.

  • Why is it important for investors to understand the science behind the stocks in the robotics and AI industry?

    -Understanding the science behind the stocks is important for investors to make informed decisions about where the industry is heading and which companies are likely to be leaders in the field. It helps investors to identify potential opportunities and to evaluate the long-term prospects of different companies.



๐Ÿค– The Rise of Humanoid Robots and AI Innovations

This paragraph discusses the recent advancements in the robotics industry, particularly focusing on humanoid robots. It emphasizes the potential for these robots to be more versatile than current industrial robots, which are often limited to specific tasks in certain environments. The global industrial robotics market is expected to grow significantly, but the humanoid robot market is anticipated to grow even faster, by over 30 times by 2030. This growth is due to the adaptability of humanoid robots, which can perform a wide range of tasks in various settings. The paragraph also suggests that the focus should not be solely on the physical design of robots, but also on the underlying technology, such as the computing power required for AI processing. Nvidia's new Blackwell GPUs and their application in autonomous vehicles and humanoid robots are highlighted as a key innovation in this space.


๐Ÿš— Autonomous Vehicles and Nvidia's Impact on Robotics

The second paragraph explores the concept of autonomous cars as a type of robot on wheels, and how Nvidia's computing platforms are integral to their operation. It discusses the shift from Tesla's rules-based code to AI models similar to others in the industry, suggesting a potential levelling of the playing field regarding full self-driving capabilities. The importance of data in training AI models is highlighted, with a mention of the staggering amount of online fraud and identity theft cases as an example of data vulnerability. The paragraph then transitions into a promotion for a service called Delete Me, which helps protect personal information from online data brokers. Nvidia's Jetson platform, specifically the new Jetson Thor designed for humanoid robots, is also discussed. The capabilities of the Blackwell GPU in terms of AI inference performance, self-checking for faults, and automatic updates are emphasized as key features for robotics applications.


๐Ÿ“š AI Training and the 'Chat GPT Moment' for Robotics

The third paragraph delves into the AI training aspect of robotics, likening it to the 'Chat GPT moment' where large language models are being developed for robots. These models allow robots to learn from video or text prompts, essentially enabling them to learn by imitation. The paragraph mentions that companies are creating general-purpose foundation models, with Nvidia's Project Groot being highlighted as an example. It discusses the importance of training robots using both real and synthesized data, as well as the use of digital environments for training and testing AI models. The paragraph also touches on the concept of reinforcement learning from human feedback and the potential for on-the-fly training of robots. It concludes by acknowledging the contributions of various companies, including Google, Meta Platforms, Microsoft, and Amazon, in building foundational models and AI data centers to support the burgeoning field of generative AI in robotics.



๐Ÿ’กHumanoid Robots

Humanoid robots are designed to mimic the form and often the functions of the human body. They are significant in the video's narrative as they represent the next generation of robotics with the potential to perform a wide array of tasks in various environments. The script discusses the growth potential of the humanoid robot market and how these robots could become a universal solution to many challenges currently faced by industry-specific robots.

๐Ÿ’กChat GPT Moment

The term 'Chat GPT moment' is used in the context of a pivotal shift in technology, similar to how GPT (Generative Pre-trained Transformer) has revolutionized natural language processing. In the video, it refers to a transformative period for robots where they can learn from large datasets and human demonstrations, much like how GPT models have enabled machines to understand and generate human-like text.

๐Ÿ’กIndustrial Robotics Market

The industrial robotics market is a sector focused on the manufacturing and application of robots in industries such as automotive, pharmaceutical, and microchip production. The video emphasizes the expected growth of this market, highlighting its potential as an investment area due to the increasing demand for automation and advanced manufacturing solutions.

๐Ÿ’กAI Inference

AI inference refers to the process where an AI system uses its trained model to deduce outcomes or make decisions without undergoing further training. In the context of the video, efficient AI inference is crucial for robots to make real-time decisions based on sensory data, which is exemplified by Nvidia's development of powerful, low-power GPUs for this purpose.

๐Ÿ’กNvidia's Jetson Thor

Nvidia's Jetson Thor is a computing platform specifically designed for powering humanoid robots. As highlighted in the video, it includes a high-performance CPU cluster and a dedicated Blackwell GPU, which is capable of performing AI inferences much faster than its predecessors. This platform is pivotal as it enables robots to operate autonomously with greater intelligence and efficiency.

๐Ÿ’กAutonomous Vehicles

Autonomous vehicles, also known as self-driving cars, are a key point of discussion in the video. They are likened to robots on wheels and are powered by advanced computing platforms like Nvidia's Drive Thor. The video notes the significance of these vehicles in the broader robotics industry, especially concerning the development of AI models that can handle complex tasks and edge cases.

๐Ÿ’กData Centers

Data centers are facilities used to house, power, and cool the computer systems that store, process, and manage large amounts of data. In the video, they are mentioned in the context of AI training, where they play a critical role in processing and storing the vast datasets used to train the AI models that eventually power robots and autonomous vehicles.

๐Ÿ’กGenerative AI

Generative AI refers to the branch of artificial intelligence that can create new content, such as text, images, or actions, based on existing data. The video discusses how generative AI is enabling the 'Chat GPT moment' for robots, allowing them to learn new tasks through imitation and training on large datasets, which is a significant shift from rule-based programming.

๐Ÿ’กAI Training

AI training involves teaching AI models to perform tasks by exposing them to large datasets and allowing them to learn from patterns and examples. In the video, AI training is discussed in the context of developing large action models for robots, which is a significant part of the 'Chat GPT moment' for robotics. The training enables robots to learn from human demonstrations and digital environments, leading to more versatile and adaptable machines.

๐Ÿ’กOnline Fraud and Identity Theft

The video mentions the prevalence of online fraud and identity theft as a societal issue, highlighting statistics related to cases in the US. While not directly related to robotics, this serves as a reminder of the importance of data security and privacy, which are also relevant considerations in the development and deployment of AI and robotics technologies.

๐Ÿ’กInvestment Opportunities

The video discusses various investment opportunities in the field of robotics, particularly focusing on the potential growth of humanoid robots and the companies that support their development, such as Nvidia. It emphasizes the importance of understanding the underlying technology and market trends to make informed investment decisions in this rapidly evolving sector.


The robotics industry is experiencing a significant shift, with humanoid robots potentially arriving sooner than expected.

Investors may be overlooking the true potential of robotics companies that do not directly sell robots.

Humanoid robots offer a universal solution to the challenges of industrial robotics, with a market expected to grow over 30X by 2030.

Industrial robotics market is predicted to almost triple in size over the next 9 years, with a CAGR of over 11%.

Humanoid robots can perform a multitude of tasks in various environments due to their human-like design.

Nvidia's new Blackwell GPUs are a game-changer, offering significant advancements for autonomous vehicles and humanoid robots.

Nvidia's Drive Thor platform consolidates various car functions and provides 1000 teraflops of compute power.

Mercedes-Benz's Drive Pilot, powered by Nvidia, has achieved level three autonomy, a significant milestone.

Tesla's full self-driving software is currently at level two, indicating there's competition for the lead in autonomous technology.

Data security is a growing concern, with over 2.5 million cases of online fraud and a million cases of identity theft in the US in the past year.

Nvidia's Jetson platform powers robots of various sizes, with a new version, Jetson Thor, specifically designed for humanoid robots.

Blackwell GPUs perform AI inference 30 times faster than their predecessors, enabling robots to run larger models more efficiently.

Nvidia's Project Groot is a general-purpose foundation model for humanoid robots, signifying the start of the 'Chat GPT moment' for robotics.

Isaac reinforcement learning gym allows robots to learn through imitation and digital training, similar to human learning processes.

Nvidia's digital gym for robots uses physics simulation environments to train AI models with vast amounts of data.

The transition to generative AI and imitation learning could revolutionize how robots are trained and deployed.

While Nvidia is a significant player, other companies like Tesla, AMD, Qualcomm, Intel, Google, Meta Platforms, Microsoft, and Amazon are also contributing to the robotics tech stack.

The generative AI era for robotics is in its infancy, presenting vast opportunities for innovation and investment.