Whinge is an interesting word.
Brodie to me has repetitively expressed a consistent opinion,opposite to yours, while giving the solution to that problem.
you define that as a whinge,because you get irritated a tad when you read it a lot.
So really,its the irritation aspect which makes you define some of his comments as a whinge.
thereforethe word whinge is subjective based on the irritation factor.
so really what i'm saying is,the word whinge is used to create a negative perception about the person you have used it against,whereas in reality,if you think about it,its really just you saying,brodie i get irritated sometimes, when i read what you say on this subject.
of course you don't say your irritated because you know that would reflect more on you,than brodie,and you want to reflect on brodie in a negative way.
thats my thoughts on the word whinge.
Would the benefit of AI to horse racing and wagering, being able to use its processing power to for example analyse the many factors of all horses in a race, such as weight, barrier, sectionals in previous races, jockey, track conditions, track, trial form, unlucky runs etc etc etc to determine the most likely winner.
Much the same as many punters do manually.
When a $30 outsider wins, you can quite often review its form and find a reason why it was going to run so well
A 17-horse field has been entered for the Gran Premio Carlos Pellegrini Internacional (G1) at Hipodromo de San Isidro Dec. 13 in Argentina, part of the Breeders' Cup Challenge Series: Win and You're In.View the full article
Means what it says . the accuracy of the information given by the A.I source was getting near 80% in certain situations.
If the algorithms used were suiting the task.
Still means a LOT of inaccuracies are involved, but things are improving as time progresses.
Is/Will be especially useful where you mentioned above for BOOKMAKER activity.
It's a very interesting topic . The A.I use in horse racing.
here's the snippet I got that from . accurate unless A.I wrote the article 😉🤣😂
We tested several popular algorithms that are used for classification in AI and also developed our own. No algorithm was perfect; the best ones − even one we developed specifically for this task − achieved an accuracy rate of about 80%,