Alexandre Gonfalonieri

About Me

Alexandre Gonfalonieri is a Consultant at CKS Consulting, a Management Consulting firm.

What I have learned after several AI projects

Some of you are probably thinking about integrating an AI-based solution into your organization. Well, the good news is that you do not need to be an expert on AI, but you do need to understand the basics such as the importance of data(many articles are available for non-tech people on Medium). Once this is done, you can proceed to automate key tasks and use data to detect patterns and outcomes. Before jumping into the AI bandwagon, please ask yourself these three questions.

Why is Machine Learning Deployment Hard?

Machine learning is still in its early stages. Indeed, both software and hardware components are constantly evolving to meet the current demands of ML. Deploying Machine Learning is and will continue to be difficult, and that’s just a reality that organizations are going to need to deal with. Thankfully though, a few new architectures and products are helping data scientists. Moreover, as more companies are scaling data science operations, they are also implementing tools that make model deployment easier.

The Harvard Innovation Lab

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