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

The robotics industry is on the cusp of a significant shift, with humanoid robots poised to become a reality much sooner than anticipated. This video discusses the potential for growth in the sector, with a focus on the underlying technology that powers these robots, rather than the physical robots themselves. It highlights the importance of the computing platforms, such as Nvidia's Blackwell GPUs and Jetson Thor, which enable robots to process vast amounts of data in real time. The video also touches on the 'chat GPT moment' for robots, where large action models are being developed to allow robots to learn from human-like data inputs. The future of robotics is being shaped by advancements in AI training, with companies like Nvidia leading the way in creating digital environments for training and testing AI models. The potential market for humanoid robots is vast, with an expected growth rate of over 60% per year for the next six years, making it an exciting field for investors to watch.

Takeaways

• 📈 The robotics industry is experiencing significant growth, with humanoid robots potentially becoming a reality sooner than expected.
• 🤖 The global industrial robotics market is expected to triple in size over the next 9 years, with a CAGR of over 11%, while the humanoid robot market could grow over 30 times by 2030.
• 🧠 The key to investing in robotics might lie in the technology platforms and the computers powering the robots, rather than the physical robots themselves.
• 🚀 NVIDIA's new Blackwell GPUs are a game-changer, offering significant advancements in AI inference performance, which is crucial for autonomous vehicles and humanoid robots.
• 🏆 Tesla's vehicles are often referred to as 'robots on wheels', highlighting the importance of their self-driving capabilities, but they are not the only player in the market.
• 🔒 Online fraud and identity theft are rampant, emphasizing the need for services like Delete Me, which helps protect personal information from data brokers.
• 💻 NVIDIA's Jetson platform, particularly the new Jetson Thor, is designed to provide the necessary computing power for a wide range of robots, including humanoid models.
• 📚 The 'Chat GPT moment' for robots involves the development of large action models that enable robots to learn from video or text prompts, much like humans learn by imitation.
• 🌐 NVIDIA's Project Groot is a foundational model for humanoid robots, indicating a shift towards more generalized and human-like robotics that can learn from a vast array of data sources.
• 🤖 Companies like Google, Meta Platforms, Microsoft, and Amazon are building foundational models, training services, and AI data centers to support the burgeoning field of robotics.
• ⚙️ The future of robotics lies in generative AI and imitation learning, which will allow robots to be trained on-the-fly and adapt to the physical world through reinforcement learning.

Q & A

What is the significance of the robotics industry's 'chat, GPT moment'?

The 'chat, GPT moment' signifies a pivotal shift in the robotics industry towards more advanced AI capabilities, particularly with humanoid robots that can perform a wide range of tasks in various environments, much like humans.

What is the expected growth rate for the global industrial robotics market?

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

How does the potential growth rate of the global humanoid robot market compare to that of industrial robotics?

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

What are the key advantages of humanoid robots over specialized industrial robots?

Humanoid robots offer a universal solution to many challenges, as they can perform a wide range of tasks in nearly any environment, unlike specialized industrial robots that are limited to specific tasks and environments.

Why is the computing power inside robots important for their functionality?

The computing power is crucial as it enables 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.

What is the role of Nvidia's Blackwell GPUs in the context of autonomous vehicles and humanoid robots?

Nvidia's Blackwell GPUs provide high-performance computing capabilities for autonomous vehicles and humanoid robots. They are designed to be small, lightweight, and low power, capable of processing large amounts of data and running AI models efficiently.

How does Nvidia's Drive Thor platform contribute to the advancement of autonomous vehicles?

Nvidia's Drive Thor platform consolidates various functions like automated driving, parking assistance, driver monitoring, navigation, and infotainment systems into a single powerful computing platform, enabling advanced levels of autonomous driving.

What is the significance of the 'chat GPT moment' for robots in terms of AI training?

The 'chat GPT moment' for robots refers to the development of large action models that allow robots to learn by imitation, similar to how humans learn. This shift towards imitation learning facilitated by generative AI is a significant step towards more advanced and versatile robotics.

What is the potential impact of AI training on the capabilities of humanoid robots?

AI training, particularly through imitation learning and reinforcement learning, can significantly enhance the capabilities of humanoid robots. It allows them to learn new tasks, adapt to different environments, and improve their performance over time.

How does Nvidia's digital gym for robots contribute to the training and development of AI models for robots?

Nvidia's digital gym, Isaac Gym, provides a physics simulation environment for training AI models through reinforcement learning. It allows for the generation of vast amounts of training data, including edge cases, and enables the testing and refinement of AI models in a virtual setting before deployment in physical robots.

What are some of the major players in the development of embedded chips for robots and self-driving cars?

Major players in the development of embedded chips for robots and self-driving cars include Nvidia, Tesla, AMD, Qualcomm, and Intel, among others.

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

Understanding the science behind the stocks is crucial for making informed investment decisions. It allows investors to identify the technological advancements and innovations that drive the value of companies in the robotics and AI industry.

Outlines

00:00

🤖 The Rise of Humanoid Robots and AI Innovations

The robotics industry is experiencing a significant shift with the advent of humanoid robots, potentially becoming more prevalent sooner than expected. The focus is not just on the physical design of robots but also on the underlying technology stack. The market for industrial robots is growing, but the humanoid robot market is projected to grow even faster, offering a versatile solution to various tasks across different environments. Companies like Boston Dynamics and Tesla are in the spotlight, but the real innovation lies in the computing power that drives these robots, requiring small, efficient, and powerful processors. Nvidia's Blackwell GPUs and Drive Thor platform are examples of such innovations, offering significant advancements in compute power and AI capabilities.

05:02

🚗 Autonomous Vehicles and Nvidia's Impact

The script discusses the progress of autonomous vehicles, highlighting the differences between Tesla's approach and that of other companies like Nvidia. While Tesla has made strides with its self-driving software, Nvidia's Drive platform, which powers Mercedes-Benz's Drive Pilot, has reached level three autonomy. The script also emphasizes the importance of data privacy and introduces a service called Delete Me, which helps protect personal information from online threats. Nvidia's Jetson platform is also mentioned for its role in powering robots of various sizes, with a new version called Jetson Thor specifically designed for humanoid robots, featuring advanced AI inference capabilities and built-in diagnostic features.

10:04

📈 AI Training and the Future of Robotics

The script explores the concept of AI training for robots, comparing it to the way humans learn by imitation. It discusses the development of large action models that can interpret video or text prompts to generate commands for robots. Companies are building foundational models that enable robots to learn from vast amounts of data, including video tutorials and manuals. Nvidia's Project Groot is highlighted as a general-purpose foundation model for humanoid robots. The script also covers the importance of reinforcement learning and the use of digital environments for training AI models. Nvidia's Isaac simulation environment and the concept of testing and updating AI models in a virtual gym before deploying them in the real world are explained. The narrative concludes by emphasizing the ongoing competition and innovation in the robotics tech stack, with many companies contributing to the development of embedded chips, training services, and AI data centers.

Keywords

💡Humanoid Robots

Humanoid robots are robots designed to resemble the human form and mimic human movements and tasks. They are significant in the video's theme as they represent the next generation of robotics with the potential to perform a wide variety of tasks in nearly any environment, just like humans. The video discusses the rapid growth expected in the humanoid robot market by 2030, highlighting their versatility and the multi-trillion-dollar opportunity they present.

💡Chat GPT Moment

The 'Chat GPT Moment' is a reference to a transformative point in the development of AI, akin to the impact of the GPT (Generative Pre-trained Transformer) models on natural language processing. In the context of the video, it suggests a significant shift towards more advanced, imitation-based learning for robots, enabled by large action models that allow robots to learn from human demonstrations, much like how humans learn from one another.

💡AI Inference

AI inference refers to the process where an AI model uses learned knowledge to make predictions or decisions based on new, unseen data. It is a core concept in the video as it pertains to the capabilities of the computer systems within robots, which need to process sensory data in real-time to make decisions and control the robot's actions. The efficiency of AI inference is crucial for the practical application of robots in various environments.

💡NVIDIA

NVIDIA is a leading technology company known for its GPUs (Graphics Processing Units) and AI computing platforms. In the video, NVIDIA is highlighted for its significant contributions to the field of robotics through its development of powerful computing platforms like Jetson Thor and Drive Thor, which are designed to handle the complex data processing and AI inference tasks necessary for autonomous vehicles and humanoid robots.

💡Autonomous Vehicles

Autonomous vehicles, also known as self-driving cars, are a key topic in the video as they share many technological similarities with robots, particularly in the areas of AI and sensor data processing. The video discusses how companies like NVIDIA and Tesla are advancing the field with new computing platforms and AI models that enable higher levels of vehicle autonomy.

💡Generative AI

Generative AI refers to artificial intelligence systems that can create new content, such as text, images, or actions, based on existing data. In the video, generative AI is central to the 'Chat GPT Moment' for robots, as it enables the development of large action models that allow robots to learn new tasks by observing and imitating human actions or other robots.

💡AI Training

AI training involves teaching AI models to perform tasks by providing them with data and letting them learn from it. The video emphasizes the shift in AI training for robots towards imitation learning, where robots can learn from human demonstrations and digital environments, facilitated by large datasets and advanced simulation engines.

💡Digital Gym

The 'Digital Gym' is a term used in the video to describe a virtual environment where AI models for robots are trained using reinforcement learning. It allows for the simulation of a vast number of scenarios, including edge cases that are rare in the real world, enabling more robust and safe AI model training for robots.

💡Robotic Platforms

Robotic platforms refer to the underlying technology or infrastructure on which robotics applications are built. The video discusses the importance of these platforms, particularly the computing power required for AI processing within robots, and how companies like NVIDIA are developing advanced platforms like Jetson Thor to meet the needs of the evolving robotics industry.

💡Investment Opportunities

The video explores the potential investment opportunities in the robotics industry, suggesting that the biggest gains may not come from companies that sell robots directly, but from those that provide the underlying technology and computing power necessary for robots to function. It highlights the growth potential in sectors like AI inference chips and AI training services.

💡Data Privacy

While not directly related to robotics, the topic of data privacy is mentioned in the context of an advertisement for a service that helps protect personal information from online data brokers. The video briefly touches on the importance of data privacy in the digital age, which is a broader societal issue that affects individuals and companies alike.

Highlights

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

The global industrial robotics market is expected to almost triple in size over the next 9 years, with a CAGR of over 11%.

The global humanoid robot market is expected to grow over 30 times in size by 2030, with a growth rate of over 60% per year for the next 6 years.

Humanoid robots offer a universal solution to challenges in robotics, with the potential to perform a wide range of tasks in nearly any environment.

Investors should focus on the computing power behind robots, which needs to be small, lightweight, and capable of processing large amounts of data in real-time.

Nvidia's new Blackwell GPUs are designed for autonomous vehicles and humanoid robots, offering significant advancements in compute power and efficiency.

Nvidia's Drive Thor platform consolidates multiple car functions, providing 1000 teraflops of compute power for advanced AI models.

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

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

Over 2.5 million cases of online fraud and over a million cases of online identity theft were reported in the US last year, highlighting the need for data protection services.

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

Blackwell GPUs have a built-in engine for reliability, availability, and serviceability, offering self-checking and health status updates for robots.

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

Isaac reinforcement learning gym by Nvidia allows robots to learn and adapt to the physical world through digital training.

AI models for robots can be trained on millions of real or synthesized examples in digital environments, improving their ability to handle edge cases.

Once trained, AI models are tested in digital environments and only updated in physical robots when they demonstrate expert-level performance.

The generative AI era in robotics is still in its early stages, with many opportunities for various companies to lead the market.

Investors are advised to understand the underlying science behind robotics stocks to make informed decisions in this rapidly evolving field.