We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Product development has long been an elevated science with frameworks, rules and significant research work conducted to ensure the product in question is fit-for-market and valued for its price. But not every company is using the full suite of tools available to tap into the collective wisdom of the consumer base. Developing a product that can make or break your organization is too important to get wrong or approach without sufficient intelligence. While most organizations adopting a product engineering mindset approach their product development cycles with a structured framework, they may fail to analyze and incorporate deep insights from the billions of online conversations about products, companies, and trends.

One of the biggest challenges that marketers are facing today and struggling with is the massive amount of data that we see in our line of work, day in and day out. Some would like to call it "data overload," which is only getting compounded due to the speed at which we're getting data in ever-increasing ways. I like to say, and I am sure other marketers will agree, whenever we are putting together any strategic plan, we start with the data. We say, "What does the data tell us?" Data dictates everything that we do, from what people say on social media and review sites about our brands and products to our customers' suggestions on things that we should consider implementing, like a new soda flavor or a new travel route. Further, there are times when the data that comes to marketers also gives us a kernel of insight into potential consumer trends that may impact our brands and products.

A new feature to be found in modern CAD software releases is KBE (Knowledge Based Engineering) to support diagnosis, selection, and monitoring of tasks. KBE relies on capturing and storing experiential knowledge which includes proprietary design and manufacturing practices exercised during a product development cycle. KBE helps engineering companies to retain and preserve in-house knowledge and intellectual information. A related technology which could significantly augment problem solving capabilities in CAD software is AI (Artificial Intelligence), which was introduced in the mid-1980s. The purpose of AI is to learn and replicate human problem solving capabilities.

Citrine Informatics, the chemicals and materials artificial intelligence (AI) platform, today announced it has won the World Materials Forum Start-up Challenge Award. The Start-up Challenge recognizes innovative materials solutions from all over the world and Citrine was chosen as the winner from a group of 12 semi-finalists. Citrine combines AI with the world's largest materials database to help bring high performance products to market faster for the Fortune 1000. The AI is specifically optimized to take advantage of known relationships in chemistry and physics. "We are excited for this recognition from one of the most important organizations in the field of materials science," said Greg Mulholland, CEO of Citrine.