Moore's law states that the number of transistors on an integrated circuit grow exponentially, roughly doubling at a period of 20 months. This affects the amount of memory available and the speed of computation, which roughly double at the same rate.
This also affects the speed of floating-point computation, if the precision is fixed. But I wonder whether one can observe a similar growth in the precision available (for scientific computing).
As a follow-up, what would such growth imply for scientific computing? For example, if we regard a linear systems of equations $Ax = b$, then the condition number of the matrix $A$ describes how strong the solution $x$ is affected if we successively drop decimal places of $b$. The larger the condition number, the more change in $x$, the worse for computing. In the reverse direction, any increase in precision would naturally lead to an improved exactness in the solution, at rate a proportional to the condition number, which were a good thing. How can this be interpreted?
PS: I have found engineering literature that, similarly, warns the reader that, e.g., a high convergence rate in numerical methods, i.e. $O(h^t)$ with large $t$, on the other hand means a strong detoriation if $h$ is increased, where $h$ denotes step-size or mesh-size in the usual contexts. This is similar to my point of view on the condition number (but may be equally wrong).