Discover how Jeena & Company transformed its logistics operations by developing tailored in-house solutions that enhance efficiency and elevate service excellence.
Traditional risk management approaches are no longer sufficient to manage risks in an increasing dynamic and complex business landscape. Implementing a dynamic risk management approach and associated systems presents opportunities, but also poses significant organisational challenges.
Understanding the ethical landscape of artificial intelligence (AI) models is key for responsible deployment.
Understanding the impact of AI ethics through real-world examples is essential for building responsible AI systems. Let’s prioritise ethical considerations in AI development.
The company streamlined key applications and transitioned to virtual machines, overcoming technical debt and infrastructure challenges to improve efficiency by 60 per cent and optimise licensing by 90 per cent.
Uncover the secrets to successful machine learning (ML) projects in enterprises, from avoiding common pitfalls to driving significant business value.
ICT policies often leave even seasoned executives uneasy, perceived as lengthy, endless compliance exercises yielding little reward beyond periodic reviews.
Generative artificial intelligence (AI) has delivered significant return on investment (ROI) for software development teams and is recognised as more of an opportunity than a threat. With big tech and venture capital firms continuing to invest in AI-assisted software development tools, this trend is going to accelerate. However, concerns around IP and security are not yet fully resolved.
Generative (gen) artificial intelligence (AI) risks span data, model, deployment, and governance dimensions, with different concerns coming to the forefront at each adoption stage.
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