Crowdsourcing Vs. Managed Service Vs. In-House Labeling
Labeled data is required for all supervised machine learning projects. Labels are added to raw data, such as images, text, audio, and video, in order to train algorithms to map inputs to outputs. If training is successful, the model will...
How to Find Training Data for Machine Learning
Supervised machine learning projects require training data. By learning from training data, a supervised algorithm aims to be able to accurately predict outcomes when exposed to real data. Training data is required for all types of supervised machine learning projects:...
Manual Vs. Automated Data Labeling
As demands increase for high-quality, large-scale training datasets, data labeling has become an increasingly important function within AI. Manually labeling training data is labor-intensive and can be difficult and expensive (see our guide to data labeling here), but is automatic...
Is Synthetic Training Data the Future of Machine Learning?
Even as the availability of processing power increases exponentially, and machine learning algorithms are commoditized, there is a problem that persistently slows the development of complex AI: obtaining high-quality, accurate training data. All supervised machine learning algorithms require training data,...
Objectivity and Ground Truth in AI
‘Ground truth’ is somewhat of a confusing machine learning buzzword. Discussions of the ground truth naturally touch on areas such as bias, representation, and objectivity, and it’s a concept worthy of discussion. One of the main pitfalls of AI is...
How Drones and Computer Vision are Used to Enhance Crop Yield
Drones or UAVs (Unmanned Aerial Vehicles) are propelling a revolution in farming and agriculture. In 2019, the FAO published E-Agriculture in Action: Drones for Agriculture, a detailed guide and roadmap of how drones are being used in agriculture, and the best practices for...
Ultimate Guide to LIDAR
Light Detection and Ranging (LIDAR) is a remote sensing and mapping technology designed to measure the dimensions and topography of terrain and 3D spaces. While LIDAR has been in development since the 1960s, recent developments in laser sensing and data...
AI Embodies The Bias Of Internet Content
OpenAI is a significant player in the modern artificial intelligence (AI) and machine learning (ML) space. While the parent company is a non-profit, it also consists of a for-profit company that received a $1 billion investment from Microsoft in 2019....
Using AI and Machine Learning to Decipher Ancient Languages
he Sumerians inhabited Mesopotamia some 6000 years ago, the region between the Tigris and Euphrates rivers, in modern-day Iraq, Kuwait, Turkey, and Syria. Mesopotamia marks humanity’s transition from small agricultural settlements to larger urban societies. The first cities were built...
What is a Human-in-the-Loop?
Machine learning (ML) and artificial intelligence (AI) models still largely require the input of humans to train, tune and test models to ensure their accuracy and performance. When humans are positioned in the ML and AI loop or cycle, they...