Natural language processing (NLP) is one of the most difficult problems in artificial intelligence (AI). The challenge lies in the fact that language is a complex system with numerous rules and exceptions. In order to create a system that can accurately process natural language, we need to have a deep understanding of how language works….
Tag: deep-learning
Generative models
Deep Learning is a type of artificial intelligence that is based on learning data representations, instead of specific rules. Deep Learning algorithms are able to learn complex patterns in data and can then generate new data that is similar to the data that was used to train the algorithm. Deep Learning is particularly well suited…
Meta-learning
Meta-learning is a subfield of machine learning that focuses on developing algorithms that can learn from data and improve their performance over time. The goal of meta-learning is to design models that can quickly adapt to new tasks and environments. Meta-learning algorithms are typically based on deep learning models that learn from large amounts of…
Deep learning
Deep learning is a subset of machine learning that is concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. Neural networks are trained using a large set of data, known as a training set, in order to learn to recognize patterns. After training, the neural network is able…
Systems that can trade stocks or other assets
In the past decade, artificial intelligence (AI) has made significant inroads into the financial industry, with applications ranging from stock trading to fraud detection. Now, AI is being used to create “systems that can trade stocks or other assets.” These AI-based systems are able to analyze vast amounts of data and make predictions about future…
Systems to accurately identify emotions in people’s faces or voices
A lot of potential exists for using AI to develop systems that can accurately identify emotions in people’s faces or voices. The most promising techniques for doing so involve using machine learning or deep learning algorithms to extract features from faces or voices that are indicative of emotional state. Once these features have been extracted,…
Systems that can accurately identify objects in images or video
When it comes to object recognition, AI systems can be divided into two main categories: machine learning and computer vision. Let’s take a closer look at each of these methods. Machine learning is a powerful AI technique that can be used to solve many different types of problems. In the context of object recognition, machine…
Using AI to pass a Turing test
The Turing test is a test of a machine’s ability to exhibit intelligent behaviour that is equivalent to, or indistinguishable from, that of a human. In the original formulation, Alan Turing proposed that a human evaluator would be asked to judge natural language responses from a machine and a human, the former of which would…
Using AI to accurately predict stock market trends
It is no secret that machine learning (ML) and artificial intelligence (AI) techniques have been used extensively in stock market prediction. Many studies have shown that these techniques can be used to achieve significant prediction accuracy. In this article, we will explore some of the latest and most effective ways to use AI for stock…
Hidden Markov models that are difficult to train
There are a number of different ways to go about using AI to learn the patterns in hidden Markov models. One approach is to use a technique called deep learning. Deep learning is a type of machine learning that is particularly well suited to learning patterns in data. Deep learning is a subset of machine…