His brief summations of other techniques are similarly uninformative or inaccurate. Statisticians sometimes use improper priors as uninformative priors. The usual uninformative priors on continuous, unbounded variables are improper. Other predicates, such as "is an individual", or "has some properties" are uninformative or vacuous. In Bayesian inference, "uninformative priors" or "objective priors" are particular choices of "a priori" probabilities. This invites uninformative answers and discourages unwanted or unpleasant views. More generally, one speaks of uninformative priors. Practical problems associated with uninformative priors include the requirement that the posterior distribution be proper. The text-based tutorial was criticised, as was the slow AI and dull, uninformative combat results. The term "uninformative prior" is somewhat of a misnomer. However, he described Berliner's editing as "inept" and Peikoff's introduction as "uninformative". For this reason, they are viewed by some as redundant or uninformative. The term is used to contrast the case of a weak or uninformative prior probability. However this type of definition has been criticized by contemporary linguists as being uninformative. With this approach, there is a risk that the algorithm is overwhelmed by uninformative examples.