clarifying

Author: karpathy

Readme.md

@@ -5,12 +5,13 @@ ConvNetJS is a Javascript implementation of Neural networks, together with nice
 
 - Common **Neural Network modules** (fully connected layers, non-linearities)
 - Classification (SVM/Softmax) and Regression (L2) **cost functions**
-- A **MagicNet class** for fully automatic neural network learning (automatic hyperparameter search and cross-validatations)
 - Ability to specify and train **Convolutional Networks** that process images
 - An experimental **Reinforcement Learning** module, based on Deep Q Learning
 
 For much more information, see the main page at [convnetjs.com](http://convnetjs.com)
 
+**Note**: I am not actively maintaining ConvNetJS anymore because I simply don't have time. I think the npm repo might not work at this point.
+
 ## Online Demos
 - [Convolutional Neural Network on MNIST digits](http://cs.stanford.edu/~karpathy/convnetjs/demo/mnist.html)
 - [Convolutional Neural Network on CIFAR-10](http://cs.stanford.edu/~karpathy/convnetjs/demo/cifar10.html)
@@ -20,7 +21,6 @@ For much more information, see the main page at [convnetjs.com](http://convnetjs
 - [Deep Q Learning Reinforcement Learning demo](http://cs.stanford.edu/people/karpathy/convnetjs/demo/rldemo.html)
 - [Image Regression ("Painting")](http://cs.stanford.edu/~karpathy/convnetjs/demo/image_regression.html)
 - [Comparison of SGD/Adagrad/Adadelta on MNIST](http://cs.stanford.edu/people/karpathy/convnetjs/demo/trainers.html)
-- [MagicNet classifying arbitary CSV data demo](http://cs.stanford.edu/people/karpathy/convnetjs/demo/automatic.html)
 
 ## Example Code