Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Understanding Emails and Drafting Responses -- An Approach Using GPT-3   Providing computer systems with the ability to understand and generate
natural language has long been a challenge of engineers. Recent progress in
natural language processing (NLP), like the GPT-3 language model released by
OpenAI, has made both possible to an extent. In this paper, we explore the
possibility of rationalising email communication using GPT-3. First, we
demonstrate the technical feasibility of understanding incoming emails and
generating responses, drawing on literature from the disciplines of software
engineering as well as data science. Second, we apply knowledge from both
business studies and, again, software engineering to identify ways to tackle
challenges we encountered. Third, we argue for the economic viability of such a
solution by analysing costs and market demand. We conclude that applying GPT-3
to rationalising email communication is feasible both technically and
economically.

23
The categories of this paper are: solv-int
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
18
The categories of this paper are: econ
19
The categories of this paper are: eess
13
The categories of this paper are: quant-ph
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
20
The categories of this paper are: acc-phys
14
The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an