AI plays an important role in helping robots see and understand the world better. But there are some big challenges that come with it.
Data Shortages: To train AI models, we need a lot of labeled data (data that is marked to help the AI learn). This data can be hard to find or really expensive.
Changing Environments: Robots need to work in many different places that can be unpredictable. This makes it harder for them to understand what they see.
Need for More Power: Processing visual information in real-time is tough. It takes a lot of computer power, which can slow things down.
Creating Fake Data: Using simulations (fake computer environments) to make training data.
Using Past Knowledge: Taking models that have already been trained on one task and using them for new tasks. This helps reduce the amount of data needed.
Better Algorithms: Making simpler and more efficient AI models can help them work better in different situations.
AI plays an important role in helping robots see and understand the world better. But there are some big challenges that come with it.
Data Shortages: To train AI models, we need a lot of labeled data (data that is marked to help the AI learn). This data can be hard to find or really expensive.
Changing Environments: Robots need to work in many different places that can be unpredictable. This makes it harder for them to understand what they see.
Need for More Power: Processing visual information in real-time is tough. It takes a lot of computer power, which can slow things down.
Creating Fake Data: Using simulations (fake computer environments) to make training data.
Using Past Knowledge: Taking models that have already been trained on one task and using them for new tasks. This helps reduce the amount of data needed.
Better Algorithms: Making simpler and more efficient AI models can help them work better in different situations.