More than 75% of organizations trying to achieve Digital Transformation – despite collectively spending more than a trillion dollars – have failed to achieve their transformation goals, evidence that they and their strategic partners are still climbing the transformation learning curve.
Organizations are increasingly relying on artificial intelligence (AI) systems to make decisions that can significantly affect individual rights, human safety, and critical business operations. But how do these models derive their conclusions? What data do they use? And can we trust the results?
Even as explainability gains importance, it is becoming significantly harder. Modeling techniques that today power many AI applications, such as deep learning and neural networks, are inherently more difficult for humans to understand. For all the predictive insights AI can deliver, advanced machine learning engines often remain a black box. The solution isn’t simply finding better ways to convey how a system works; rather, it’s about creating tools and processes that can help even the deep expert understand the outcome and then explain it to others.To shed light on these systems and meet the needs of customers, employees, and regulators, organizations need to master the fundamentals of explainability. Gaining that mastery requires establishing a governance framework, putting in place the right practices, and investing in the right set of tools.
Major corporations around the world have trusted Mintmesh to bring our unique expertise on cloud based AI digital platform solution, to guide their Digital Transformation efforts.
Mintmesh has a proven track record in helping clients not only achieve their transformation goals, but to outpace their traditional competitors by saving up to 41% technical bid evaluation time. We’ve worked side-by-side with our customers to tackle some of the most daunting transformation challenges imaginable, resulting in demonstrated, documented ROI.
Mintmesh’s, "Making AI Understandable: Demystifying the black box”, series is about assisting the EPC organizations to decode the use cases of AI and help establish a good fit for explainability technology, in an easy-to-follow educational format.
The Webinars are free, but registration is required.
According to a report by MarketsandMarkets, the global AI in the construction market is expected to grow from $407 million in 2018 to $1.8 billion by 2024, at a compound annual growth rate (CAGR) of 34.0%
According to a report by McKinsey, companies that adopt AI and ML in the construction industry can improve productivity by 50% and reduce project timelines by 20%
According to a study by the World Economic Forum, AI and ML can help the construction industry save $1.6 trillion by 2030