Our blog is dedicated to a global discussion about the ideas, actions and technologies changing the world as we know it.
Upgrade your browser for full experience
You are using a web browser version that is no longer supported. Please make sure you are using the most updated version of your browser, or try using our supported browser Google Chrome to get the full Applied Materials experience.
In 2020, the Applied Materials Community Affairs team embarked on a year-long journey to evaluate our U.S.-based work in communities of color. This included conducting an Equity Audit examining our personal beliefs as well as our work’s programs and practices. In this blog, I discuss key learnings from the audit and the initial steps we are taking to evolve our program.
To enable a more sustainable semiconductor industry, new fabs must be designed to maximize output while reducing energy consumption and emissions. In this blog post, I examine Applied Materials’ efforts to drive fab sustainability through the process equipment we develop for chipmakers. It all starts with an evolution in the mindset of how these systems are designed.
For many centuries, optical technologies have utilized the same principles and components to bend and manipulate light. Now, another strategy to control light—metasurface optics or flat optics—is moving out of academic labs and heading toward commercial viability.
Join Applied Materials at the 2019 SPIE Advanced Lithography Symposium as we present our latest R&D advancements on layer-to-layer alignment, defect detection and 3D pattern characterization, and highlight new e-beam technology.
Applied Materials is a member of the new IBM Research AI Hardware Center—a new ecosystem of research and commercial partners collaborating with IBM to further accelerate the development of AI-optimized hardware innovations.
Applied Materials convened a panel of industry experts to explore trends and challenges for memory technology over the next decade—from continued scaling of mainstream technologies to developing new memory and computing architectures for Big Data and Artificial Intelligence.