AI Learns from You – but You Can Learn from AI
The product experts that use our AI don’t see the Citrine Platform as a black box, but as a flashlight. And that flashlight just got stronger.
The product experts that use our AI don’t see the Citrine Platform as a black box, but as a flashlight. And that flashlight just got stronger.
Although many companies are already reaping the rewards of using AI, others are being held back by myths around the need for large datasets. While representative data can propel an AI project forward quickly, you don’t need to wait for large, structured datasets to start your AI journey.
Polymers play a crucial role in a wide range of modern applications, from automotive and aerospace to electronics and packaging. As the demand for high-performance polymer products continues to rise, producers are constantly looking for ways to improve efficiency and responsiveness to customer needs.
Many of our customers are using the Citrine Platform to remove so-called “Forever chemicals”, PFAS, from a variety of products. In each case, the Citrine Platform is able to help because it is chemically-aware and can be trained to deeply understand a domain by our customer’s experts.
Our customers are innovators, pushing the boundaries of science and engineering to create and optimize materials, chemicals, products, and processes. They generate intellectual property, which is an intangible, but no less important, asset on the balance sheet. It is important that this asset is protected.
Learn how consumer companies are leveraging artificial intelligence to accelerate product development and commercialization of cosmetic and personal care products.
Generative AI is disrupting and reshaping many industries globally. In the materials and chemicals space, the effective deployment of AI (or not) is going to separate the winners from losers and it’s going to happen a lot faster than you think.
Dr. Lenore Kubie passes on advice around data strategy.
Companies are thinking through the build versus buy decision on Materials Informatics platforms. This blog outlines what to think about.
Materials innovation is essential to sustainability. Materials Informatics can accelerate that. To speed up adoption of MI we need both education and public research to produce FAIR data.