Neural Networks
Why Artificial Neural Networks Have A Long Way To Go Before They Can ‘See’ Like Us
Artificial neural networks were created to imitate processes in our brains, and in many respects – such as performing the quick, complex calculations necessary to win strategic games such as chess and Go – they’ve already surpassed us. But if you’ve ever clicked through a CAPTCHA test online to prove you’re human, you know …
Internet Data Produce A Racist, Sexist Robot
A robot operating with a popular internet-based artificial intelligence system consistently gravitates to men over women, white people over people of color, and jumps to conclusions about peoples’ jobs after a glance at their face. The work is believed to be the first to show that robots loaded with an accepted and widely used model …
How Machine Learning Can Support Historians Decipher Ancient Inscriptions
The origins of ancient inscriptions are often shrouded in mystery. Writing carved into stone millennia ago can be hard to read and is often missing entire sections of the text. Now a neural network, trained on thousands of existing inscriptions, could help historians figure out when and where a piece of writing comes from – …
Developing Countries Are Being Left Behind In The AI Race – And That’s A Problem For All Of Us
Artificial Intelligence (AI) is much more than just a buzzword nowadays. It powers facial recognition in smartphones and computers, translation between foreign languages, systems which filter spam emails and identify toxic content on social media, and can even detect cancerous tumours. These examples, along with countless other existing and emerging applications of AI, help make …
Can Machine-Learning Models Overcome Biased Datasets?
Artificial intelligence systems may be able to complete tasks quickly, but that doesn’t mean they always do so fairly. If the datasets used to train machine-learning models contain biased data, it is likely the system could exhibit that same bias when it makes decisions in practice. For instance, if a dataset contains mostly images of …
Artificial Networks Learn To Smell Like The Brain
Using machine learning, a computer model can teach itself to smell in just a few minutes. When it does, researchers have found, it builds a neural network that closely mimics the olfactory circuits that animal brains use to process odors. Animals from fruit flies to humans all use essentially the same strategy to process olfactory information in …
What are Adversarial AI Attacks and How Do We Combat Them?
Deep learning is the main force behind the recent advances in the field of artificial intelligence (AI). Deep learning models are capable of performing on par with, if not exceeding, human levels, at a variety of different tasks and objectives. However, deep neural networks are vulnerable to subtle adversarial perturbations applied to their inputs – …
Success With Machine Learning Projects In Python
What does it mean for a machine to learn? In a way, machines learn just like humans. They infer patterns from data through a combination of experience and instruction. In this article, we will give you a sense of the applications for machine learning and explain why Python is a perfect choice for getting started. …
The Pain Points Of Scaling Data Science
While building a machine learning model, data scaling in machine learning is the most significant element through data pre-processing. Scaling may recognize the difference between a model of poor machine learning and a stronger one. Machine learning algorithm only recognizes numerical if there is a significant difference in the dimension, say few varying in tens …
Tweaking AI Software To Function Like A Human Brain Improves Computer’s Learning Ability
Computer-based artificial intelligence can function more like human intelligence when programmed to use a much faster technique for learning new objects, say two neuroscientists who designed such a model that was designed to mirror human visual learning. In the journal Frontiers in Computational Neuroscience, Maximilian Riesenhuber, PhD, professor of neuroscience, at Georgetown University Medical Center, and …