While reading the book AI A modern approach, 4th ed, I came across the section of "Agent program" with following text:
It is instructive to consider why the table-driven approach to agent construction is doomed to failure. Let $P$ be the set of possible percepts and let $T$ be the lifetime of the agent (the total number of percepts it will receive).
The lookup table will contain $\sum_{i=1}^T |P|^T$ entries.
Consider the automated taxi: the visual input from a single camera (eight cameras is typical) comes in at the rate of roughly 70 mb per sec. (30 frames per sec, 1080 X 720 pixels, with 24 bits of color information).
This gives a lookup table with over $10^{600,000,000,000}$ for an hour's driving.
Could someone please explain how the lookup table number is derived? (or what the author's point is which I am missing). If I were to multiply all of the numbers $30 × 1080 × 720 × 24 × 8 × 3600$, then I get $1.6124314e+13$ which comes very close I think, but can't get what would be the reason to build a table (even though a theoretic one) in such a way - something which is obviously intractable
edit:
My core question is this:
Assuming $10^{600,000,000,000}$ is derived from $30 × 1080 × 720 × 24 × 8 × 3600$, what is the purpose of storing data in the look up table at pixel precision? Wouldn't storing higher level of details be enough to solve these kind of problems (ie, autonomous driving)? Coming more from standard software database systems, I am missing that point. Thanks