Join us on Dec. 10 in San Francisco as we discuss new ways of improving chip performance, power and area-cost beyond traditional Moore’s Law scaling.

This year’s Tech for Global Good Celebration honored four innovative organizations who are using technology to address critical problems facing our future, and recognized ocean conservationist and women in STEM advocate Julie Packard with the James C. Morgan Global Humanitarian Award.

Where can the industry test codesigned chip innovations for the AI Era—to accelerate the future of computing, from materials to systems? The answer is: our new Materials Engineering Technology Accelerator (META Center), which—I’m delighted to announce—is now open for collaboration.

The serial interaction between siloed parts of the industry that produced the computing eras of the past—mainframe/minicomputer, PC/Internet, mobile/social media—will not be sufficient to fuel the next era of computing. Instead, we need codesign from materials to systems to enable the AI Era.

The AI Era is fueling an explosion of data, while Moore’s Law is no longer the predictable engine of progress that it once was. With opportunities and challenges of this magnitude, we need to open the strategic planning lens and decide where we want to be in 2029.

In honor of UN International Day of the Girl on Oct. 11, Applied Materials employees share what they are doing to support gender equity and female empowerment.

Our recent Open Innovation Workshop brought together quantum technology leaders from across the ecosystem to identify key challenges in quantum information systems and explore opportunities for collaboration. The central theme that emerged from the day is that quantum is about so much more than computing; there are many applications in areas like sensing, metrology and communications encryption on the near-term horizon.

Metrology allows process engineers to see the results of process steps. Today, driving improvements in chip performance, power and area/cost (PPAC) requires novel architectures and exotic material stacks. This is introducing new sources of atomic-scale variation that can negatively impact chip performance and yield. It is becoming imperative to “watch” the deposition process as it occurs to control variability and deliver repeatable performance.

Strategic investments from corporate venture capital into AI companies have been increasing. Read my latest blog to find out what’s driving this trend and where the funding is being directed.