Introduction
The field of AI and robotics is rapidly evolving, with new advancements and predictions emerging regularly. In this blog post, we’ll explore some of the latest developments and insights from industry experts, including Rodney Brooks and OpenAI.
Academic Rumblings About the Limits of Deep Learning
In recent years, there has been increasing discussion about the limitations of deep learning, a popular AI technique. According to Rodney Brooks, academic rumblings about these limits began in 2017, with the technical press reporting on the limitations of deep learning and reinforcement learning for game play. By 2020, the popular press had started to declare the end of the deep learning era.
The Emergence of LLMs and ChatGPT
In 2023, the “next big thing” in AI beyond deep learning emerged: large language models (LLMs), such as ChatGPT and its cousins. These models, which were already being worked on as early as 2017, have shown significant promise in various applications, revolutionizing natural language processing and generation.
The Decline of the Turing Test and Asimov’s Laws
As AI and robotics advance, traditional measures of progress, such as the Turing Test and Asimov’s three laws, are becoming less relevant. The Turing Test, which evaluates a machine’s ability to mimic human-like conversation, was largely missing from press coverage in 2023 and 2024, indicating a shift in how progress is measured. Instead, the focus has turned to more practical applications and the development of AI systems that can assist and augment human capabilities.
Robotics Developments
In robotics, there have been several notable developments. For instance, dexterous robot hands are expected to become generally available by 2030, with lab demonstrations already underway. Additionally, there are predictions of robots capable of providing physical assistance to the elderly for multiple tasks by 2028, and those that can carry out the last 10 yards of delivery from a vehicle. These advancements highlight the potential for robotics to improve quality of life and streamline various processes.
Google DeepMind’s RT-2 Model
Google DeepMind has introduced RT-2, a vision-language-action (VLA) model that translates vision and language into robotic actions. This model, which is trained on text and images from the web, can directly output robotic actions, bringing us closer to a future of helpful robots. RT-2 represents a significant step forward in the integration of AI and robotics, enabling machines to better understand and interact with their environment.
Conclusion
The field of AI and robotics is undergoing rapid change, with new advancements and predictions emerging regularly. As we look to the future, it’s essential to stay informed about these developments and consider their implications for various industries and society as a whole. From the limitations of deep learning to the emergence of large language models and the integration of AI and robotics, the landscape is shifting, and the possibilities are endless.
