In the context of machine learning, what is the purpose of the "kernel trick" in support vector machines (SVMs)?

In the context of machine learning, what is the purpose of the "kernel trick" in support vector machines (SVMs)? Correct Answer To transform data into a higher-dimensional space for better separability

Related Questions

In SVMs (Support vector machines) Data points are log-transformed and normalized as in method A, where for N observations of a gene i, the log transform Xi of the expression level Ei and reference level Ri is?
Consider a system described by ẋ = Ax + Bu y = Cx + Du The system is completely output controllable if and only if Where: x = State vector (n-vector) u = Control vector (r-vector) y = Output vector (m-vector) A = n × n matrix B = n × r matrix C = m × n matrix D = m × r matrix