so variability in reality is the founding cancer evolution theory life itself is variability there is no life without variability as far as we understand life today we all swim in a sea of variability I like the idea of swimming because it gives you the idea of being able to move in any direction with minimal effort and being also and gives the idea of the fact that you should try to move along with the current in a way not to have the variability work against you but work together with variability and trying to use variability for your for the best okay never never put yourself against the current recognize that variability is there and do what what you can do to go forward so just a very tiny introduction to typical I would call it a typical but simplified feed flow so we have ingredients its ingredients has its variation in its nutrients okay then we add to that variation the sampling error we had the analytical error then we have the data we use in our optimization we take decision on this but anyway we get to a point where we have numbers that we use then we proportion the feed and we have the our rounding error in the diet then we proportion the feed and we have dosing errors scale errors imprecisions whatever you can think of then we have our mixing errors because not every mixture is the same and not every mixer is well maintained as it should be then you have after you made the mixer and you palletized and you've made everything you have the segregation of the nutrients due to the different parts of processing transport to farm and feeders and finally the errors of delivery that we mentioned yesterday they are not at all something that does not happen it happens it happens much more than one then we can think of so there's a lot of points where we could say that there is a hot spot they are not just a usual linear programming because they include in the variability data foreign group or ingredients so you need to have the variability data for each nutrient for each ingredient or at least for the ingredients you want to control and for the nutrient in the ingredients you want to control you need to decide what is the probability of success you want ie how many times out of a hundred you want to be within the numbers you you set as a requirement in your LP and you have to know your analytical error data let's say that most of these things are totally unknown or very difficult to obtain and very difficult to manage and very difficult to maintain said this that explains why the software is not being a big success I can show you some idea of how it works