Intelligent conversational assistants, such as Apple's Siri, Microsoft's
Cortana, and Amazon's Echo, have quickly become a part of our digital life.
However, these assistants have major limitations, which prevents users from
conversing with them as they would with human dialog partners. This limits our
ability to observe how users really want to interact with the underlying
system. To address this problem, we developed a crowd-powered conversational
assistant, Chorus, and deployed it to see how users and workers would interact
together when mediated by the system. Chorus sophisticatedly converses with end
users over time by recruiting workers on demand, which in turn decide what
might be the best response for each user sentence. Up to the first month of our
deployment, 59 users have held conversations with Chorus during 320
conversational sessions. In this paper, we present an account of Chorus'
deployment, with a focus on four challenges: (i) identifying when conversations
are over, (ii) malicious users and workers, (iii) on-demand recruiting, and
(iv) settings in which consensus is not enough. Our observations could assist
the deployment of crowd-powered conversation systems and crowd-powered systems
in general.

该研究开发了一种基于众包的对话助手 Chorus，它可以与终端用户进行复杂的对话，并以专业的方式招募工作者来帮助决定最佳响应。研究通过对 Chorus 的应用部署，提出了四个挑战：确定对话结束时间、恶意用户和工作者、按需招募，以及在没有共识的情况下的设置。这些观察结果对基于众包的对话系统和众包系统的部署有启示作用。

部署即时众包对话代理的挑战：“我还能帮您做什么？

"Is there anything else I can help you with?": Challenges in Deploying  an On-Demand Crowd-Powered Conversational Agent

Wireless engineers and business planners commonly raise the question on
where, when, and how millimeter-wave (mmWave) will be used in 5G and beyond.
Since the next generation network is not just a new radio access standard, but
instead an integration of networks for vertical markets with diverse
applications, answers to the question depend on scenarios and use cases to be
deployed. This paper gives four 5G mmWave deployment examples and describes in
chronological order the scenarios and use cases of their probable deployment,
including expected system architectures and hardware prototypes. The paper
starts with 28 GHz outdoor backhauling for fixed wireless access and moving
hotspots, which will be demonstrated at the PyeongChang winter Olympic games in
2018. The second deployment example is a 60 GHz unlicensed indoor access system
at the Tokyo-Narita airport, which is combined with Mobile Edge Computing (MEC)
to enable ultra-high speed content download with low latency. The third example
is mmWave mesh network to be used as a micro Radio Access Network ({\mu}-RAN),
for cost-effective backhauling of small-cell Base Stations (BSs) in dense urban
scenarios. The last example is mmWave based Vehicular-to-Vehicular (V2V) and
Vehicular-to-Everything (V2X) communications system, which enables automated
driving by exchanging High Definition (HD) dynamic map information between cars
and Roadside Units (RSUs). For 5G and beyond, mmWave and MEC will play
important roles for a diverse set of applications that require both ultra-high
data rate and low latency communications.

本文介绍了四种 5G 毫米波部署示例，并按时间顺序描述了它们的潜在部署方案和用例，包括预期的系统架构和硬件原型。在 5G 及更高版本中，毫米波和 MEC 将在需要超高数据率和低延迟通信的各种应用程序中发挥重要作用。