The Robotic Revolution: The Fusion of Generative AI and Robots Defines the Future

https://www.nvidia.com/gtc/keynote/

LLMs (Large Language Models, such as those used in solutions like ChatGPT), as part of the Generative AI, are revolutionizing how robots perceive and react to their environment by enabling them to process and understand human language. This allows them to interpret more complex instructions and respond more efficiently to interactions with people. Instead of rigidly following specific instructions, these models allow robots to adapt to the context and perform a wider variety of tasks autonomously, making them more versatile and useful in diverse situations.

Nvidia's presentation of the GR00T model and the Jetson Thor platform at GTC 2024 (Notes 1 and 2) marks a significant milestone. GR00T (Generalist Robot 00 Technology) is a general-purpose foundational model (Note 3) for humanoid robots designed to advance robotics and embedded AI. Nvidia's Thor chip is capable of operating at 800 teraflops (Note 4) in floating-point operations with 8-bit precision (FP8).

Robots powered by GR00T will be designed to understand natural language and emulate human movements by observing actions, quickly learning coordination and other skills to navigate, adapt, and interact with the real world. In Nvidia's GTC 2024 keynote, CEO Jen-Hsun Huang demonstrated several of these robots completing various tasks. You can see them starting at the 1:52 mark in the video.

A robot with generalized AI (Note 5) would be able to perform a variety of activities, from simple to complex tasks, without needing constant reprogramming. This means the robot could interact with its environment more naturally, make decisions autonomously, and perform various actions without direct human intervention.

Achieving generalized AI in humanoid robots is an ambitious goal in the fields of robotics and artificial intelligence, as it involves developing algorithms and systems that can understand, learn, and adapt to a wide range of contexts and situations, which is still in the process of development.

Note 1: GTC stands for Nvidia's annual 'GPU Technology Conference.'

Note 2: GPUs (graphics processing units) are devices in which Nvidia is a global leader, specially designed to perform intensive parallel calculations. Therefore, they are used not only for image and video processing but also in computationally demanding applications such as machine learning or cryptography.

Note 3: A "foundation model" is a type of artificial intelligence model that serves as a base or starting point for developing more specific or advanced applications. These models are often trained on large datasets and can perform a variety of general tasks, such as understanding natural language, recognizing images, or making data-based decisions. Then, these models can be adapted or fine-tuned to meet the specific needs of a particular application through a process called "fine-tuning."

Note 4: The term FLOPS refers to "floating-point operations per second," which follows a convention on how numbers are represented based on the available number of bits, sacrificing precision for speed. FP8 would be the representation with 8 bits (bit = binary digit, meaning the most basic representation, either a 1 or a 0).

Note 5: Generalized AI refers to an AI system that has the ability to perform a wide variety of tasks similarly to how a human would, unlike specialized AI, which is designed to perform specific tasks such as voice recognition or data analysis.

Generalized AI in humanoid robots refers to an advanced form of AI that enables a robot to perform a wide range of tasks autonomously, similar to how a human would. This generalized AI would empower the robot to learn and adapt to different situations and environments without the need for specific programming for each task.