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ɫ����Ƶ recently announced the availability of ɫ����Ƶ AI v4.2, which has the potential to increase a business’ AI time to impact by 4X. These new capabilities can significantly fast-track successful implementations by empowering industrial engineers with AI, helping choose the right use case and quickly deriving deeper and relevant insights from data. 

 In the below video, Jeff Wood, ɫ����Ƶ AI's Director of Product Management, elaborates on the new cutting-edge features of the release and how they can help customers achieve their AI dreams sooner.

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Below are some of the Frequently Asked Questions, Jeff is asked about the v4.2 release.

‍What is the key theme of the 4.2 release?

The key theme of our v4.2 release is helping industrial companies realize real business value from AI as quickly as possible. Many companies struggle with adopting AI, with project failure rates as high as 80%. We are looking to reverse that statistic.

The ɫ����Ƶ AI platform is designed and built for industrial engineers. It aims to make AI available to users who don’t necessarily have data science or coding expertise. Enhancements in this release make AI accessible to industrial operators so that they can quickly extract value from their data, define and develop real-world use cases, and drive impact across their operations. 

  What are the key highlights of the v4.2 release?

There are four key highlights of the v4.2 release. Let’s take a look at what they are and how they can help companies fast-track their AI goals.

1. AI Navigator: This is a new module in the v4.2 release that serves as the starting point for a company’s AI journey by guiding them through a structured review of their potential use cases. The ɫ����Ƶ AI Navigator helps the company collect critical information on a use case and then assess how well suited that use case is to be solved with AI. This is done along dimensions such as data readiness, business value, scope, complexity and success criteria. As the company builds a group of use cases, it can rank and prioritize which ones to pursue.

2. Notebook: A new feature, Notebook provides users visibility into all of the actions that have been taken for a project. This allows them to see previous steps, better plan future iterations and sets them on the path to building the best possible AI model. In addition, Notebook also provides a common reference when multiple users are collaborating on a project.

3. 3D Charting: 3D charting gives users greater visibility into their data. For example, a user can see three separate features plotted together on a scatterplot. This helps them quickly extract data insights and relationships, ultimately leading to the development of AI models.

4. Error Code Cleaning: Lastly, there is Error Code Cleaning. This is another feature focused on saving the user’s time. In particular, it helps the user quickly identify and remove the bad data in their dataset. 

What benefits are current users experiencing from the latest release?

We have had encouraging feedback on the latest release. With the AI Navigator, we have seen very positive results, with customers using it to help them plan which use cases to work on and achieve success with those use cases.

  In addition, we have received excellent user feedback for the Notebook and 3D Charting features. Users have commented that these are precisely the type of features that can help them gain momentum with their projects.

  Why is it important that process engineers/operators are empowered to use AI?

At ɫ����Ƶ AI, our mission is to empower industrial companies to build a profitable and sustainable future by transforming how they use data. A key part of this is recognizing that the best people to get value from industrial data are the process engineers and operators since they have a deep understanding of the company’s operations. In addition, these individuals have contextual knowledge and experience that is critical to making an AI project successful. As a result, the best way to make a company successful with AI is to empower process engineers and operators to use AI directly.

  This new release can help engineers to quickly identify and select the right AI use case, as well as define AI models faster. It has the potential to transform industrial operations from one dimensional, model predictive control-based black boxes to three-dimensional visual systems. Moreover, it can enable them to build, validate and scale AI models swiftly and efficiently across the organization.

  What is next for the ɫ����Ƶ roadmap?

ɫ����Ƶ AI's no-code platform enables industrial engineers to leverage the power of AI across their operations. In the next 12 months, we will advance the ease and speed for users to apply, explain and scale AI with the following key roadmap features:   

• Apply AI to more complex use cases and challenges 
• Deliver advanced data visualization for deeper data discovery, trend analysis and relationship insights 
• Provide advanced model evaluation capabilities
• New capabilities to fast-track scaling AI use cases 

 If you would like more information on ɫ����Ƶ AI v4.2,  with one of our experts today.