4 ms·
According to scientists, we only use 0.3% of our neural networks. Imagine if we could use 100%.
by qntty 3y ago
According to scientists, we only use 0.3% of our neural networks. Imagine if we could use 100%.
- deleted 3y ago[deleted]
- kleiba 3y agoNice. I know HN can sometimes be the place where humor goes to die, but I found this comment hilarious.
- zzzcsgo 3y ago[dead]
- madprofessor 3y agoWonderful.
- jredwards 3y agoThank you for taking one of my most hated memes and turning it into hilarity.
- 29athrowaway 3y agoThen you would have to eat a full refrigerator worth of food every day to survive.
- simne 3y agoReally good humor :) But in reality, sparse NN is just loose it's performance, mean loose precision and recall. Precision, means, larger probability of errors; recall - if you work with piece of information, which could consist of few, ie predicates, it will see not all predicates. To be concrete, for good trained full-scale NN, usually considered 70-90% for precision and for recall; but if use small fraction of weights, usually will got drop of performance to about 40-70%, which is good enough for many cases, considering saves on size and computations.