Your question is Explain Word Embeddings. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You're working on an NLP system that needs to represent words in a way a model can learn from. You are comparing simple token based features with dense vector representations.
What are word embeddings, and why are they useful?