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Prompt engineering is the process of structuring or crafting an instruction in order to produce the best possible output from a generative artificial intelligence (AI) model. [ 1 ] A prompt is natural language text describing the task that an AI should perform. [ 2 ]
Answers had to be recorded for questions that were off-topic and that were hypothetical. In testing, the software has picked out the best answer for about 90 per cent of the questions that have been asked. The project has won many plaudits including the interactive award and the audience award at the Sheffield documentary festival in 2016. [10]
Tensor Processing Unit (TPU) is an AI accelerator application-specific integrated circuit (ASIC) developed by Google for neural network machine learning, using Google's own TensorFlow software. [2] Google began using TPUs internally in 2015, and in 2018 made them available for third-party use, both as part of its cloud infrastructure and by ...
The high-level architecture of IBM's DeepQA used in Watson [9]. Watson was created as a question answering (QA) computing system that IBM built to apply advanced natural language processing, information retrieval, knowledge representation, automated reasoning, and machine learning technologies to the field of open domain question answering.
SitePal allows users to deploy "virtual employees" on websites that can welcome visitors, guide them around the site, and answer questions. The use of SitePal on commercial websites has been controversial because many visitors report finding them annoying. Some research has shown that they can increase sales in comparison to using static ...
The results would not depend on the machine's ability to answer questions correctly, only on how closely its answers resembled those of a human. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic).