The PC industry is currently obsessed with power efficiency, long battery life, and AI. But who's going to stand up for the people who want raw performance and don't care about anything else? That performance advocate could be you, AMD. You've got what it takes. So dig out that bomber jacket, put on those aviator shades, and lean in.

All the sessions from Transform 2021 are available on-demand now. As the world becomes increasingly reliant on technology, organizations have to consider the growing threats to their supply chain. Goldman Sachs principal engineer Michael Mattioli and AMD CTO Mark Papermaster spoke about this issue at VentureBeat's virtual Transform 2021 conference last week. They stressed that this is not a problem any single company can solve alone -- changing the ecosystem will require industrywide collaboration. The supply chain is "remarkably complex," Mattioli said, as it goes all the way back to the design of the chip or board, which is then sent to the foundry to be manufactured.

One thing is certain: The explosion of data creation in our society will continue as far as pundits and anyone else can forecast. In response, there is an insatiable demand for more advanced high performance computing to make this data useful. The IT industry has been pushing to new levels of high-end computing performance; this is the dawn of the exascale era of computing. Recent announcements from the US Department of Energy for exascale computers represent the starting point for a new generation of computing advances. This is critical for the advancement of any number of use cases such as understanding the interactions underlying the science of weather, sub-atomic structures, genomics, physics, rapidly emerging artificial intelligence applications, and other important scientific fields.

In 2016, the chip industry's clock ran out. For 50 years, the number of transistors that could be squeezed onto a piece of silicon had increased on a predictable schedule known as Moore's law. The doctrine drove the digital evolution from minicomputers to PCs to smartphones and the cloud by cramming more transistors onto each generation of microchip, making them more powerful. But as the smallest features of transistors reached about 14 nanometers, smaller than the tiniest viruses, the industry fell off its self-imposed pace. The 2016 edition of a biennial report that usually renewed an industry pledge to sustain Moore's law abandoned that focus to consider alternative paths forward.

Advanced Micro Devices is gearing up to join a race to accelerate deep-learning jobs in client and embedded systems. However, AMD is not yet ready to provide any specifics on the 7-nm x86 and GPU chips that it aims to deliver over the next year -- or its roadmap beyond 7 nm. "There is a need for high performance with what we call the edge [of the network] … closer to the source where data is coming in and [needing] to be analyzed -- often in real time," said Mark Papermaster, AMD's chief technology officer, in an interview. "AMD's machine-learning strategy is holistic and provides engines of AI for both the data center and the edge." In late 2016, AMD released its first GPU accelerators for deep learning in the data center.