Materials Science
Generative models can be used in many more areas than just language generation, with one particularly promising area: molecule generation for chemical product development.
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OpenAI’s ChatGPT, Google’s Bard, and other similar Large Language Models (LLMs) have made dramatic strides in their ability to interact with people using natural language. Users can describe what they want done and have the LLM “understand” and respond appropriately.
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For many traditional innovation-driven organizations, scientific data is generated to answer specific immediate research questions and then archived to protect IP, with little attention paid to the future value of reusing the data to answer other similar or tangential questions.
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In the digital era, robust data tools are crucial for all companies and the science-driven industries like the life sciences, materials science, and chemistry are no exception.
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Dec 19, 2022|Energy, Life Sciences, Materials Science, Transformation As a company that delivers Digital Transformation for Science, part of our job at Enthought is to understand the trends that will affect how our clients do their science. Below are three trends that caught our attention in 2022 that we predict will take center stage in…
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Introduction If you have used TensorFlow before, you know how easy it is to create a simple neural network model using the Keras API. Just create an instance of the Sequential model class, add the number of desired layers and accompanying layer nodes, define the activation functions to be used by each layer, and compile…
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“Digital transformation”, “machine learning”, and “artificial intelligence” are buzzwords heard in every industry, from the boardroom to the lab. We asked Dr. Michael Heiber, lead of Enthought’s Materials Informatics solutions, about what these technology trends mean for the future of materials and chemical labs and product development. Q: What are some of the top challenges…
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SEMICON West 2021 lived up to its status as the signature conference for the extended microelectronics supply chain. Business and technology leaders, researchers, and analysts from across the semiconductor industry connected in-person and virtually for a 360 view of technological and market trends. Enthought Takeaways Authors: Michael Heiber, Application Engineer, Materials Science Solutions Group; Tim…
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At this year’s SEMI Strategic Materials Conference, leaders in the semiconductor industry across the supply chain came together to discuss the big challenges and opportunities that are likely to emerge over the next 5 years. Our Takeaways Authors: Michael Heiber, Application Engineer, Materials Science Solutions Group, Tim Diller, Director of Digital Transformation Services, Materials Science…
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In our recent C&EN Webinar: Accelerating Consumer Products Reformulation with Machine Learning, we demonstrated how to leverage digital tools and technology to bring new products to market faster. The webinar was well attended by scientists, engineers, and business leaders across the product development spectrum eager to learn how these concepts can be applied to their…
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