AI in Manufacturing – Impacts and Benefits

Artificial Intelligence in Learning & Performance is a reality, chatbots being a prime example. IBM Business Partner Assima, has developed new cognitive solutions combining its very own technology With Watson services to accelerate user performance.

A recent Forrester Research report showed that over 40% of business and tech professionals surveyed are interested in AI for Customer Support. And, according to the Service Council, 50% of service organizations are facing significant talent shortages that are negatively affecting their business, with another 38% expecting issues soon. The need to always improve the customer support experience coupled with the loss of skilled employees to retirement is creating a “Know-How” gap that is difficult to replace.

Making quality data available in a reliable manner is a major determinant of success for data analytics initiatives be they regular dashboards or reports, or advanced analytics projects drawing on state of the art machine learning techniques. Data engineers tasked with this responsibility need to take account of a broad set of dependencies and requirements as they design and build their data pipelines.Join Suraj Acharya, Director, Engineering at Databricks, and Singh Garewal, Director of Product Marketing, as they discuss the modern IT/ data architecture that a data engineer must operate within, data engineering best practices they can adopt and desirable characteristics of tools to deploy.

In order to solve the challenges created by issues like PPE shortages, insufficient testing capabilities, and an increase in individuals claiming unemployment benefits, public sector IT teams need to unlock data from legacy systems and securely connect newer technologies, faster.