Machine Learning
Humanising Machines Paid Members Public
One of the reasons why Machine Intelligence has taken off in recent years is because we have extraordinarily rich datasets that are collections of experiences about the world that provide a source for machines to learn from.
Innovation Behind Data: Why it’s The New Oil Well in Your Business Paid Members Public
Data is crucial to any organization's efforts to establish digital resiliency – the ability for an organization to rapidly adapt to business disruptions by leveraging digital capabilities to restore business operations and capitalize on the changed conditions.
Future of Neural Network Technology Paid Members Public
Deep neural networks, or more broadly, learning models with deep embeddings, enable a wide range of applications on various levels: from biomedical data to language modeling.
Entrepreneurship, Complexity, and Data Science: Part I Paid Members Public
The success story of Uber is a clear case of economic feedback effect accelerated by a smart use of technology. However, what is why this model is so difficult to reproduce? Is there a relationship between size, information and sustainability?
Diagnosing Alzheimer’s Disease with Disruptive Advances: Artificial Intelligence Knows No Limits Paid Members Public
The early detection of AD based on AI would allow easier management for care providers and the patient’s family, thus decreasing financial expenses and overall healthcare costs to treat this pathology.
A Linear Brain in a Non-linear World: How to Reverse your Thinking with Neuroscience to Challenge, Experiment, and Explore Paid Members Public
I will try to answer this question by exploring major differences between linear and non-linear thinking and why humans are tuned to think linearly from a cognitive and probably neurophysiological perspective.
