It doesn’t necessarily contradict but adds nuance to the conversation. LLMs shine in areas like logistics, data analysis, and workflow automation, despite their role in direct robotic control or real-time precision tasks is limited.
Where the confusion might arise is that while LLMs can contribute to robotics—like interpreting natural language commands or generating code—they aren’t a substitute for core movement algorithms like inverse kinematics. In other words, LLMs enhance certain aspects around robotics and automation but don’t replace the specialized systems already in place for critical tasks.
The focus is more on integration and augmentation, not replacement.
It doesn’t necessarily contradict but adds nuance to the conversation. LLMs shine in areas like logistics, data analysis, and workflow automation, despite their role in direct robotic control or real-time precision tasks is limited.
Where the confusion might arise is that while LLMs can contribute to robotics—like interpreting natural language commands or generating code—they aren’t a substitute for core movement algorithms like inverse kinematics. In other words, LLMs enhance certain aspects around robotics and automation but don’t replace the specialized systems already in place for critical tasks.
The focus is more on integration and augmentation, not replacement.
Proof. I am asking for anything for you to back up what you are claiming.
All of those things require context. Something LLMs cannot ever understand; it is a hard limit of the statistical analysis that LLMs use.
Edit: also, here is proof of cognitive decline brought about as a result of feeding LLM outputs back into LLM models: https://bmjgroup.com/almost-all-leading-ai-chatbots-show-signs-of-cognitive-decline/