Using the existing Snowflake Python Connector you bring the Snowflake data to the system that is executing the Python program, limiting you to the compute and memory of that system. With Snowpark for Python, you are bringing your Python code to Snowflake to leverage the compute and memory of the cloud platform.
Have a few questions regarding SnowPark with Python.

Why do we need Snowpark when we already have Snowflake python connector(freely) that can use to connect to Python jupyter with Snowflake DW?

If we use snowpark and connect with Local jupyter file to run ML model. Is it use our local machine computing power or Snowflake computing power?If its our local machine computing power how can we use Snowflake computing power to run the ml model?
Snowflake SnowPark Python -Clarifications