Roadmap on emerging hardware and technology for machine learning.

Recent progress in artificial intelligence is largely attributed to the rapid development of machine learning, especially in the algorithm and neural network models. However, it is the performance of the hardware, in particular the energy efficiency of a computing system that sets the fundamental limit of the capability of machine learning. Data-centric computing requires a revolution in hardware systems, since traditional digital computers based on transistors and the von Neumann architecture were not purposely designed for neuromorphic computing.

Publisher Correction: Integrating photonics with silicon nanoelectronics for the next generation of systems on a chip.

In this Letter, owing to an error during the production process, the author affiliations were listed incorrectly. Affiliation number 5 (Colleges of Nanoscale Science and Engineering, State University of New York (SUNY)) was repeated, and affiliation numbers 6-8 were incorrect. In addition, the phrase "two oxide thickness variants" should have been "two gate oxide thickness variants".

Integrating photonics with silicon nanoelectronics for the next generation of systems on a chip.

Electronic and photonic technologies have transformed our lives-from computing and mobile devices, to information technology and the internet. Our future demands in these fields require innovation in each technology separately, but also depend on our ability to harness their complementary physics through integrated solutions. This goal is hindered by the fact that most silicon nanotechnologies-which enable our processors, computer memory, communications chips and image sensors-rely on bulk silicon substrates, a cost-effective solution with an abundant supply chain, but with substantial limitations for the integration of photonic functions.

Sub-bandgap polysilicon photodetector in zero-change CMOS process for telecommunication wavelength.

We report a defect state based guided-wave photoconductive detector at 1360-1630 nm telecommunication wavelength directly in standard microelectronics CMOS processes, with zero in-foundry process modification. The defect states in the polysilicon used to define a transistor gate assists light absorption. The body crystalline silicon helps form an inverse ridge waveguide to confine optical mode.