Focus is on cutting costs across the board, and it turns out there is still quite a bit to cut.

If neural networking architectures are simpler than a CPU, why is it so difficult to create them?

FPGAs are proving to be versatile for many applications.

Neuromorphic computing and machine learning dominate the leading edge of chip design this year.

Are cheaper LiDAR devices on the way?

Technical issues increase, costs go up, and not all markets will benefit.

Chipmakers wrestle with EOS, ESD and other power-related issues as leading-edge chips are incorporated into industrial and automotive applications.

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.

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.

Next-gen embedded memory technology ramps up in wake of flash scaling issues.

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

Chipmakers exploring nanosheet, nanoslab, nano-ring and hexagonal FETs.