Optimization Quotes

“Leaders are raised through training and experience. Nobody was born naturally with hand-gloves of leadership. We come to life to search for it, discover it and optimize it.”

“Dare to rise, when all voices behind you say you can’t get there, ignore them and move on… it’s not about the talents and gifts you have; it’s about how wise you optimize them!”

“Good website practice and optimizing for conversion usually makes for good search engine optimization. These work together to ensure you drive quality traffic and can persuade that traffic to help you meet your business goals.”

“Constrained optimization is the art of compromise between conflicting objectives. This is what design is all about. To find fault with biological design - as Stephen Jay Gould regularly does - because it misses some idealized optimum is therefore gratuitous. Not knowing the objectives of the designer, Gould is in no position to say whether the designer has proposed a faulty compromise among those objectives.”

“The Enlightenment, finally, invented progressive 'history' as an inner-worldly purgatory in order to develop the conditions of possibility of a perfected 'society'. This provided the required setting for the aggressive social theology of the Modern Age to drive out the political theology of the imperial eras. What was the Enlightenment in its deep structure if not an attempt to translate the ancient rhyme on learning and suffering - mathein pathein - into a collective and species-wide phenomenon? Was its aim not to persuade the many to expose themselves to transitional ordeals that would precede the great optimization of all things?”

“Due to the various pragmatic obstacles, it is rare for a mission-critical analysis to be done in the “fully Bayesian” manner, i.e., without the use of tried-and-true frequentist tools at the various stages. Philosophy and beauty aside, the reliability and efficiency of the underlying computations required by the Bayesian framework are the main practical issues. A central technical issue at the heart of this is that it is much easier to do optimization (reliably and efficiently) in high dimensions than it is to do integration in high dimensions. Thus the workhorse machine learning methods, while there are ongoing efforts to adapt them to Bayesian framework, are almost all rooted in frequentist methods. A work-around is to perform MAP inference, which is optimization based.Most users of Bayesian estimation methods, in practice, are likely to use a mix of Bayesian and frequentist tools. The reverse is also true—frequentist data analysts, even if they stay formally within the frequentist framework, are often influenced by “Bayesian thinking,” referring to “priors” and “posteriors.” The most advisable position is probably to know both paradigms well, in order to make informed judgments about which tools to apply in which situations.”

“Premature optimization is the root of all evil.”

“We must develop knowledge optimization initiatives to leverage our key learnings.”

“Users are a double-edged sword. They can help you improve your language, but they can also deter you from improving. So choose your users carefully, and be slow to grow their number. Having users is like optimization: the wise course is to delay it.”