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are notoriously difficult to design and implement. Despite the hype and the flood of recent frameworks, especially within the generative AI space, turning these projects into real, tangible value stays a serious challenge...

People and businesses are obsessive about the potential of AI, but 80% of AI projects will fail—and it is not all the way down to want or enthusiasm. While AI is permeating every industry and...

Within the , constructing Machine Learning models was a skill only data scientists with knowledge of Python could master. Nevertheless, low-code AI platforms have made things much easier now. Anyone can now directly make a...

Apple failed to realize results with its artificial intelligence (AI) and prolonged reality (XR) headset 'Vision Pro', which it invested heavily in last 12 months, resulting in expectations that it's going to face an...

A straightforward guide to know the macro-elements that may negatively impact your workEver found yourself deep in a knowledge project, only to understand it’s going nowhere? It’s a more common feeling than you would...

In an effort to enhance fairness or reduce backlogs, machine-learning models are...

Learning from a use case3. The responsibility of consolidating the collected information was ambiguous:The HAI methods facilitate design participants to generate a considerable amount of information mandatory to design an AI-powered application. The methods...

A Journey To Encourage Young ProgrammersBack in 2005, the Web was not what it looks like today.Before 2005, people had just began using the Web to:Communicate with one another using Gmail.Play basic browser-based games.Share...