Microsoft Commits $40M to Exploration of “AI for Human Good” Use Cases – AI Trends

Microsoft is embarking on a five-year, $40m programme to explore how artificial intelligence (AI) can be used to bolster the response of non-governmental organisations (NGOs) to humanitarian disasters. The AI for Humanitarian Action programme will focus on using AI technologies to assist select NGOs throughout the world…

CNN Tensor Shape Explained – Convolutional Neural Networks and Feature Maps

Convolutional neural networks are artificial neural nets used for image recognition in deep learning. Let’s look at the typical tensor input shape for a CNN. We’ll also introduce input channels, output channels, and feature maps. Check out the corresponding blog and other resources for this…

Artificial intelligence helps track down mysterious cosmic radio bursts

Breakthrough Listen researchers used artificial intelligence to search through radio signals … civilizations. Credit: Breakthrough Listen image Artificial intelligence is invading many fields, most … VISIT THE SOURCE ARTICLE Author:

New Research: Artificial Intelligence Non-Invasively Detects…

… Fertility and Life Whisperer used artificial intelligence to accurately detect aneuploidy of … abnormalities using morphological assessment through artificial intelligence A recent, international collaborative study … Australia-based Life Whisperer suggests that artificial intelligence (AI) models, applied to 2D … VISIT THE SOURCE ARTICLE Author:

How to Predict Room Occupancy Based on Environmental Factors

Small computers, such as Arduino devices, can be used within buildings to record environmental variables from which simple and useful properties can be predicted. One example is predicting whether a room or rooms are occupied based on environmental measures such as temperature, humidity, and related…

A Gentle Introduction to SARIMA for Time Series Forecasting in Python

Autoregressive Integrated Moving Average, or ARIMA, is one of the most widely used forecasting methods for univariate time series data forecasting. Although the method can handle data with a trend, it does not support time series with a seasonal component. An extension to ARIMA that…

How to Reduce Variance in a Final Machine Learning Model

A final machine learning model is one trained on all available data and is then used to make predictions on new data. A problem with most final models is that they suffer variance in their predictions. This means that each time you fit a model,…