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The working limitations of large language models / Mikhail Burtsev, Martin Reeves, Adam Job.

O'Reilly Online Learning: Academic/Public Library Edition Available online

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Format:
Book
Author/Creator:
Burtsev, Mikhail, author.
Reeves, Martin, author.
Job, Adam, author.
Language:
English
Subjects (All):
Natural language generation (Computer science).
Artificial intelligence--Computer programs.
Artificial intelligence.
Natural language processing (Computer science).
Physical Description:
1 online resource (7 pages)
Edition:
[First edition].
Place of Publication:
[Cambridge, Massachusetts] : MIT Sloan Management Review, 2023.
Summary:
Large language models (LLMs) can generate convincingly human-sounding responses to queries. This ability can lead users to mistakenly attribute certain human capabilities to these artificial intelligence algorithms, namely reasoning, knowledge, understanding, and execution. Understanding how LLMs work and what their limitations are can help users identify where generative AI technology is best applied and where its outputs might be unreliable.
Notes:
OCLC-licensed vendor bibliographic record.
Reprint #65233.
OCLC:
1415201815
Publisher Number:
53863MIT65233

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