EUDR Deadline Extended—But Immediate Action is Key
The EU Deforestation Regulation (EUDR) aims to eliminate deforestation-linked products from the European market, impacting commodities like coffee, cocoa, soy, wood,and palm oil. This new regulation requires suppliers to demonstrate that their products are deforestation-free. With the compliance deadline extended...
Building Expert AI With Domain-Specific Data
The internet has been transformative for AI development, providing the vast quantities of data that power today's most advanced systems. From language models to computer vision, many of modern AI's breakthroughs would be impossible without access to this enormous pool...
Generative AI Projections for 2025 and Beyond
Generative AI, once a glint in the eye of researchers pre-2022, has advanced rapidly in a short space of time. While generative AI technology has already dramatically impacted business and society in its short two-year history, questions surround its future. ...
Sustainable Dev’t In Ghana
The latest survey by the Ghana Statistical Service revealed that 42,396 agribusiness firms closed during the lockdown, with 16,091 of those firms still remaining closed. The impact of COVID-19 was more pronounced in the service and industry sectors, particularly for...
The Lack of Diversity in Datasets And Why We Should Care
There has been a noticeable lack of diverse datasets to train machine learning models, resulting in ethical harms against specific communities. AI ethics researchers are pushing for solutions that involve more transparency in model development and dataset training. Regulations on...
Abductive Learning and Artificial Intelligence: Why Can’t Machines learn like Humans?
In an oriental fable, the sons of King Serendippo travel a distant road. They come across a man who has lost a camel. Is it, they ask him, blind on one side, carrying two skins on its back, one of...
The Art of the Dataset
Artists working with AI face multiple decisions during their creative process. Typically, they need to come up with a compelling concept, find a relevant dataset, choose a suitable algorithm and curate the generated images for display. Each stage offers plenty...
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...
