Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Learning in the Era of Edge Computing: Challenges and Opportunities   The era of edge computing has arrived. Although the Internet is the backbone
of edge computing, its true value lies at the intersection of gathering data
from sensors and extracting meaningful information from the sensor data. We
envision that in the near future, majority of edge devices will be equipped
with machine intelligence powered by deep learning. However, deep
learning-based approaches require a large volume of high-quality data to train
and are very expensive in terms of computation, memory, and power consumption.
In this chapter, we describe eight research challenges and promising
opportunities at the intersection of computer systems, networking, and machine
learning. Solving those challenges will enable resource-limited edge devices to
leverage the amazing capability of deep learning. We hope this chapter could
inspire new research that will eventually lead to the realization of the vision
of intelligent edge.

12
The categories of this paper are: nucl-th
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
0
The categories of this paper are: hep-ph
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
16
The categories of this paper are: stat
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg
14
The categories of this paper are: math-ph
13
The categories of this paper are: quant-ph
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
11
The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg