this is deeplearning article related with AI, artificial intelligence.
Do even the best DNN models understand language? New advances, new excitement Without any doubt, Deep Neural Networks (DNNs) have brought huge improvements to the NLP world recently. News like an AI model using DNN can write articles like a human or can write code to create a website like a real developer comes to …
Do even the best DNN models understand language? Read More »
In NLP, encoding text is the heart of understanding language. There are many implementations like Glove, Word2vec, fastText which are aware of word embedding. However, these embeddings are only useful for word-level and may not perform well in case we would like to expand to encode for sentences or in general, greater than one word. …
EXPLORING UNIVERSAL SENTENCE ENCODER MODEL (USE) Read More »
Introduction Tiny Machine Learning (TinyML) [1] is, unsurprisingly, a machine learning technique but this technique is often utilized in building machine learning applications, which require high performance but have limited hardware. a tiny neural network on a microcontroller with really low power requirements (sometimes <1mW). Figure 1: Tiny ML, the next AI revolution [5] TinyML is …
Introduction Autoencoders provide a powerful framework for learning compressed representations by encoding all of the information needed to reconstruct a data point in a latent code. In some cases, autoencoders can “interpolate”: By decoding the convex combination of the latent codes for two data points, the autoencoder can produce an output that semantically mixes characteristics …
Implementation for Adversarially Constrained Autoencoder Interpolation (ACAI) Read More »
