9 research outputs found
Evorus: A Crowd-powered Conversational Assistant Built to Automate Itself Over Time
Crowd-powered conversational assistants have been shown to be more robust
than automated systems, but do so at the cost of higher response latency and
monetary costs. A promising direction is to combine the two approaches for high
quality, low latency, and low cost solutions. In this paper, we introduce
Evorus, a crowd-powered conversational assistant built to automate itself over
time by (i) allowing new chatbots to be easily integrated to automate more
scenarios, (ii) reusing prior crowd answers, and (iii) learning to
automatically approve response candidates. Our 5-month-long deployment with 80
participants and 281 conversations shows that Evorus can automate itself
without compromising conversation quality. Crowd-AI architectures have long
been proposed as a way to reduce cost and latency for crowd-powered systems;
Evorus demonstrates how automation can be introduced successfully in a deployed
system. Its architecture allows future researchers to make further innovation
on the underlying automated components in the context of a deployed open domain
dialog system.Comment: 10 pages. To appear in the Proceedings of the Conference on Human
Factors in Computing Systems 2018 (CHI'18
PressClub with Mark Zuckerberg, Daniel Ek, and Tobi Lütke
https://epublications.marquette.edu/zuckerberg_files_videos/1345/thumbnail.jp
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A simulator and compiler framework for agile hardware-software co-design evaluation and exploration
As Moore's Law has slowed and Dennard Scaling has ended, architects are increasingly turning to heterogeneous parallelism and hardware-software co-design. These trends present new challenges for simulation-based performance assessments that are central to early-stage architectural exploration. Simulators must be lightweight to support heterogeneous combinations of general-purpose cores and specialized processing units. They must also support agile exploration of hardware-software co-design, i.e. changes in the programming model, compiler, ISA, and specialized hardware.
To meet these challenges, we describe our compiler and simulator pair: DEC++ and MosaicSim. Together, they provide a lightweight, modular simulator for heterogeneous systems, offering accuracy and agility designed specifically for hardware-software co-design explorations. The simulator and corresponding compiler were developed as part of the DECADES project, a multi-team effort to design and tape out a new heterogeneous architecture. We will present two case-studies in important data-science applications where DEC++ and MosaicSim enable straightforward design space explorations for emerging full-stack systems