English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Assuming hardware is the major constraint for enabling real-time mobileintelligence, the industry has mainly dedicated their efforts to developingspecialized hardware accelerators for machine learning and inference. Thisarticle challenges the assumption. By drawing on a recent real-time AIoptimization framework CoCoPIE, it maintains that with effectivecompression-compiler co-design, it is possible to enable real-time artificialintelligence on mainstream end devices without special hardware. CoCoPIE is asoftware framework that holds numerous records on mobile AI: the firstframework that supports all main kinds of DNNs, from CNNs to RNNs, transformer,language models, and so on; the fastest DNN pruning and acceleration framework,up to 180X faster compared with current DNN pruning on other frameworks such asTensorFlow-Lite; making many representative AI applications able to run inreal-time on off-the-shelf mobile devices that have been previously regardedpossible only with special hardware support; making off-the-shelf mobiledevices outperform a number of representative ASIC and FPGA solutions in termsof energy efficiency and/or performance.

CoCoPIE: Making Mobile AI Sweet As PIE --Compression-Compilation Co-Design Goes a Long Way