Generative AI has been a popular topic within the robotics realm, sparking a plethora of innovative ideas on how to harness the full potential of emerging technologies. From leveraging natural language commands to design applications, the possibilities are virtually limitless. During a recent visit to Nvidia's South Bay headquarters, we posed the question of generative AI to Deepu Talla, Nvidia's Vice President and General Manager of Embedded & Edge Computing.
Talla expressed his enthusiasm for the impact of generative AI, stating, "I think it speaks in the results. You can already see the productivity improvement. It can compose an email for me. It's not right, but I don't have to start from zero. It's giving me 70%. There are obvious things you can already see that are definitely a step function better than how things were before. Summarizing something's not perfect. I'm not going to let it read and summarize for me. So, you can already see some signs of productivity improvements."
As it turns out, Nvidia was on the brink of unveiling its groundbreaking developments in the world of generative AI. The ROSCon announcement coincided with several other pivotal updates on the company's robotics offerings. Notably, this includes the general availability of the Nvidia Isaac ROS 2.0 and Nvidia Isaac Sim 2023 platforms.
These cutting-edge systems are wholeheartedly embracing generative AI, a move that is poised to catalyze its adoption among the robotics community. Nvidia highlights that approximately 1.2 million developers have already interacted with the Nvidia AI and Jetson platforms, drawing prominent clients like Cisco, AWS, and John Deere into the fold.
A standout feature in this new era is the Jetson Generative AI Lab, which grants developers access to open-source large language models. In their own words, Nvidia describes this venture as follows:
"The NVIDIA Jetson Generative AI Lab provides developers access to optimized tools and tutorials for deploying open-source LLMs, diffusion models to generate stunning images interactively, vision language models (VLMs), and vision transformers (ViTs) that combine vision AI and natural language processing to provide comprehensive understanding of the scene."
These models are a game-changer in the world of robotics, enabling systems to make informed decisions in scenarios for which they were not explicitly trained. While environments like warehouses and factory floors are more structured, they still present countless variables to contend with. The goal is to equip these systems with the capability to adapt on the fly and offer a more intuitive, natural language interface.
Deepu Talla emphasized the transformative potential of generative AI, stating, "Generative AI will significantly accelerate deployments of AI at the edge with better generalization, ease of use, and higher accuracy than previously possible. This largest-ever software expansion of our Metropolis and Isaac frameworks on Jetson, combined with the power of transformer models and generative AI, addresses this need."
In addition to the generative AI integration, the latest versions of the platforms deliver notable enhancements in perception and simulation, further solidifying Nvidia's company position as a driving force in the world of robotics and artificial intelligence. With these groundbreaking developments, the future of robotics is looking brighter and more capable than ever.