Europe’s Landmark Regulation: What You Should Know
This comprehensive session breaks down the EU AI Act: Europe’s landmark regulation for governing AI systems. The webinar explains the legislation’s structure, timelines, and practical
Ethics & Regulations
Global AI Regulations: Navigating the Next Frontier
In November 2022, the launch of ChatGPT marked a groundbreaking milestone in AI, highlighting the need for the evolution of global AI regulations. In fact,
The EU AI Act and its Potential Impact on Enterprises Harnessing the Power of AI
Artificial intelligence (AI) is everywhere and is becoming increasingly present in our daily lives. From personalized recommendations on Netflix to virtual assistants on our smartphones,
The Gender Data Gap in AI: Confronting Bias in Machine Learning
AI and gender bias is a prevalent issue that impacts several aspects of our lives: from the design of products to the type of services
The Environmental Impact of ML Inference
The ever-growing presence of technology in our daily lives has sparked discussions among many about how it affects the environment. Being able to measure, control,
7 Women Leaders in AI/ML to Follow
Only 22% of AI professionals are women. Artificial intelligence (AI) and machine learning (ML) are fields that have traditionally been male-dominated, but that’s starting to
Four principles for deploying AI responsibly
Four principles for deploying AI responsibly Telecoms.com periodically invites expert third parties to share their views on the industry’s most pressing issues. In this piece Alejandro
Six Types of AI Bias Everyone Should Know
AI Bias appears in machine learning in lots of different forms and in a world that is increasingly becoming more reliant on this type of
Machine Learning Bias and Fairness
Machine learning is becoming integral to how the modern world functions, with more and more sectors harnessing the power of algorithms to automate tasks and
Bias vs Fairness vs Explainability in AI
Over the last few years, there has been a distinct focus on building machine learning systems that are, in some way, responsible and ethical. The