There are multiple layers in which machine learning can help with the creation of semiconductors, but getting there is not as simple as for other application areas.

Transition from planar to 3D NAND is harder and more time-consuming than expected.

Machine learning needs techniques to prevent adversarial use, along with better data protection and management.

Funding is free-flowing for the field, but hurdles persist.

New lithography, equipment required as packaging continues to scale.

Next nodes are expected to be long-lasting, because costs of developing chip after that will skyrocket.

Mark Bohr opens up on the company’s push into multi-chip solutions, and upcoming issues at 7nm and 5nm.

Chip industry repositions as technology begins to take shape; no clear winners yet.

Proponents tout freedom for computing architectures, but is the semiconductor ecosystem ready for open-source hardware?

Advanced packaging shifts to mainstream with complete flows, better tools, market proof points.

High price of moving to finFETs pushes foundries to offer a less expensive alternative.

Foundry unit rolls out ambitious plan down to 4nm, along with 18nm FD-SOI and advanced packaging developments.

Demand is up, capacity is flat. A look at what’s behind this imbalance.