Semiconductors

AI is being implemented at the edge, near-edge and cloud—and each application demands a unique set of memory requirements.

Back-scattered electron imaging technologies reveal buried defects to speed process development and improve chip performance and yield.

Solving the manufacturing challenges of next-generation memory technologies—where a few atoms can make a very big difference—will require expertise in materials engineering and manufacturing.

Selective removal technologies capable of removing materials at the atomic-scale are needed to enable new ways to shrink transistors as 2D scaling reaches physical limits.

Applied Materials is honored to be recognized among Intel’s 2018 Preferred Quality Supplier (PQS) award winners.

Moving systems to the neuromorphic computing paradigm with ‘in-memory compute.’

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.