A while ago I wrote briefly on why the Singularity might not be near and my estimates badly off. I saw it linked the other day, and realized that pessimism seemed to be trendy lately, which meant I ought to work on why one might be optimistic instead: http://www.gwern.net/Mistakes#counter-point
(Summary: long-sought AI goals have been recently achieved, global economic growth & political stability continues, and some resource crunches have turned into surpluses - all contrary to long-standing pessimistic forecasts.)
Kurzweil has an example of a task with 43,000x speedup over some period, more than Moore's Law, that is often mentioned in these discussions, and might be what you're thinking of. It was for one very narrow task, cherrypicked from a paper as the one with by far the greatest improvement. It's an extremely unrepresentative sample selected for rhetorical effect. Just as Kurzweil resolves ambiguity overwhelmingly in his favor in evaluating his predictions, he selects the most extreme anecdotes he can find. On the other hand, in computer chess and go software progress seems to have been on the same order as Moore's law too.
ETA: there were still improvements of many thousandfold over the period considering the rest of the paper.
I agree this 43k improvement is not representative of algorithms research in general (sorting is not 43k faster than in the 1960s, for example), but let's not call it 'very narrow': linear programming optimization (and operations research in general) is important and used all over the place in numerous applications in every industry. We owe a good deal of our present wealth to operations research and linear programming.