Difference between machine learning and artificial intelligence
The subject areas Artifical Intelligence and Machine Learning (plus Data Science) are loosely defined, such that it is hard to make strict statements about how they relate. In the general case, it seems that there are parts that overlap, but that they are quite far from being "the same subject with two different names" as suggested in the question.

The term Artifical Intelligence has many possible meanings and interpretations - which version to refer varies by time and by the source using it. Textbooks on artificial intelligence will often cover topics such as search algorithms, logical deduction and other things which are clearly not machine learning as it is practised today.

For instance, we could take it to refer to Artificial General Intelligence (or "hard AI"), and it should be clear in this case that at least some form of learning algorithm(s) would be required to meet the goals of AGI. However, it is far less clear how much of AGI can be solved by combining machine learning into complex structures.

The term Machine Learning has a few different working definitions, but this is a popular one:


  A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E.


This is far more tightly defined than Artificial Intelligence, but still has a lot of scope. 

The trend to conflate AI and ML appears to be a media and marketing issue, not a technical one. I suspect this is in part due to advances in the last 5-10 years in neural networks. Neural network models have made strong progress, especially in signal processing of images, video, audio. There is also an analogy with biological brains which can be compelling - especially when the subject matter is simplified for consumption by mainstream media. 

It is worth mentioning Data Science too. Like Artificial Intelligence, the term is somewhat fuzzily defined. Also like AI, Data Science has more to it than just Machine Learning. To Data Science practitioners, ML is part of a toolkit to achieve goals - for some people it is a large part of what they do, for others it is just one part of a wider scope (actually training and refining a ML model might take only a small fraction of a professional data scientist, analyst or statistician's time). I think it is reasonable to state that Artificial Intelligence and Data Science relate to Machine Learning in a similar way.