Cover Image
Read Now

The working limitations of large language models

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 wo...

Full description

Bibliographic Details
Main Authors: Burtsev, Mikhail, Reeves, Martin (Author), Job, Adam (Author)
Format: eBook
Language:English
Published: [Cambridge, Massachusetts] MIT Sloan Management Review 2023
Edition:[First edition]
Subjects:
Artificial Intelligence / Computer Programs / Fast / (ocolc)fst00817252
Natural Language Processing (computer Science) / Fast / (ocolc)fst01034365
Artificial Intelligence / Computer Programs / Http://id.loc.gov/authorities/subjects/sh85008181
Natural Language Generation (computer Science) / Fast / (ocolc)fst01986384
Natural Language Generation (computer Science) / Http://id.loc.gov/authorities/subjects/sh2017004703
Natural Language Processing (computer Science) / Http://id.loc.gov/authorities/subjects/sh88002425
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Description
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
Item Description:Reprint #65233
Physical Description:7 pages

Similar Items