However, the author warns that there are potential problems and troubles with LBMs. For instance, if the AI observed a human making a mistake while performing a task, it might learn to mimic that mistake. The author emphasizes the need for programming and data training guardrails to ensure safety. The author concludes by stating that the advent of LBMs is still going strong and gaining daily traction, but there are still many challenges to be resolved. The author encourages AI researchers to give LBMs a good strong look and to ensure that the AI suitably identifies the right behavior and prevents mistakes in behavioral copycatting.
Key takeaways:
- Large Behavior Models (LBMs) are a new advancement in AI that combines Large Language Models (LLMs) and generative AI with behavioral aspects, allowing AI robots to learn and perform tasks by observing and mimicking human behaviors.
- LBMs are trained using multi-modal data and are capable of interacting with humans using natural language, making them more user-friendly compared to traditional robots that require specialized programming skills.
- While LBMs hold great promise, they also present potential challenges and risks, such as the possibility of the AI mimicking incorrect behaviors or making mistakes due to a lack of common sense.
- The field of LBMs is still in its infancy and presents numerous opportunities for AI researchers, but also necessitates careful consideration of ethical, legal, and safety implications.