Can Deep Learning Save Us and Itself From the Avalanche of Threats in Cyberspace?

I present a computationally efficient and accurate feedforward neural network for sentiment prediction capable of maintaining high transfer accuracy when coupled with an effective semantics model of the text. Experimental results show the advantages of the new approach. Applications to security validation programs are discussed.