How do I balance interests within a specialized PhD? Do I simply read a lot outside my field?
You say, "The problem is that I want to know too much." You don't want to know too
much, but maybe you want to know too much all at once.

If you are going to pursue a PhD in molecular biology, you owe it to
yourself, your department, your research adviser, and whomever is
providing financial support to focus you energy on learning that
material and writing a fine thesis roughly within the usual time
expected by your department. Most serious PhD students don't have
much time for 'hobbies' outside of their coursework and research,
but if you do, you could consider AI as your hobby for now.

There seem to be unexploited connections between molecular biology and AI,
so it is worthwhile to look forward to exploring those connections
at an appropriate time.

If you can't bear to let a major connection to AI wait until you
finish a PhD in molecular biology, then maybe you should re-think the
order of your concentrations. Both fields are developing rapidly.
Will it be easier to catch up on recent developments in AI after
your PhD in molecular biology? Or would it be easier to learn about
recent developments in molecular biology after getting a PhD in AI?

I have some idea how much biology an AI a person would have to know in order to
make worthwhile applications to molecular biology. But personally, I
have no idea how much you would have to know about AI
to exploit opportunities in molecular biology. So I have no advice about the best
order of concentration. 

As a starting place for you to make the best decision on your own, do you see how study "of a single new enzyme ..." would make successful exploitation of AI techniques more likely? Or maybe you can find a molecular biology department
that is already deeply committed to using AI.

I have done a lot of work in applications of statistics and probability modeling
to biology with only self-taught biology (not even a high school biology class).
My impression is that it is easier for me to catch the essence of the necessary
biology ad hoc than it is for biologists to catch the the essence of the
required statistics or probability. (Some of my collaborators may disagree
on that.)