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.
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.
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 work. We received many good questions during the event, and wanted to make our detailed responses available to the wider community. If you have any follow up questions, please reach out to us. Enthought is here to help your business navigate the challenges in R&D digital transformation and affect real change and business value generation.
The digital skills mix varies widely across companies, from those just starting to invest in digital transformation initiatives, to ones well into their journey. Building a community of people who think digitally and are able to innovate and quickly prototype ideas is key to delivering results.
The ultimate project goal of EnergizAIR Infrastructure was to raise individual awareness of the contribution of renewable energy sources, and ultimately change behaviors. Now ten years later, with orders of magnitude more data, AI/machine learning, cloud, and smartphones in the hands of individuals, this is an idea whose time has come.
The process of materials discovery is complex and iterative, requiring a level of expertise to be done effectively. Materials workflows that require human judgement present a specific challenge to the discovery process, which can be leveraged as an opportunity to introduce digital technologies.
As industries rapidly advance in AI/machine learning, a key to unlocking the power of these approaches for companies is an enabling environment. Domain experts need to be able to use artificial intelligence on data relevant to their work, but they should not have to know computer or data science techniques to solve their problems. An environment which enables the domain expert to easily and intuitively label data and train models will allow AI to become truly ‘applied.’ The above image shows a series of fault planes predicted by our approach in the SubsurfaceAI Seismic application, created with ‘applied machine learning’ in mind. Learn More.
In this blog article Enthought Energy Solutions Vice President Mason Dykstra looks at the recently published book titled “Real World AI: A Practical Guide for Responsible Machine Learning” in the context of both the technical challenges faced by geoscientists and how to scale.
A microseismic event loaded from the Frontier Observatory for Research in Geothermal Energy (FORGE) distributed acoustic sensing (DAS) data into a Jupyter notebook showing energy from a microseismic event arriving at about 7.5 seconds. These microseisms bring information about the process of stimulation. However, in the data set there are relatively few and they are hard to find without specialized processing. Connecting hard-to-get SEG-Y data to easy-to-develop Jupyter notebooks promises to drive innovation in new AI/ML methods for detecting more microseisms and therefore, increasing the value of the existing data.