Pith. sign in

REVIEW 1 cited by

Unleashing GPT on the Metaverse: Savior or Destroyer?

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2303.13856 v3 pith:RNZFYDJ5 submitted 2023-03-24 cs.HC cs.AI

classification cs.HCcs.AI
keywords metaversearticleexperiencesimmersivepossibletechnologyaccordingadvantages
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

Incorporating artificial intelligence (AI) technology, particularly large language models (LLMs), is becoming increasingly vital for developing immersive and interactive metaverse experiences. GPT, a representative LLM developed by OpenAI, is leading LLM development and gaining attention for its potential in building the metaverse. The article delves into the pros and cons of utilizing GPT for metaverse-based education, entertainment, personalization, and support. Dynamic and personalized experiences are possible with this technology, but there are also legitimate privacy, bias, and ethical issues to consider. This article aims to help readers understand the possible influence of GPT, according to its unique technological advantages, on the metaverse and how it may be used to effectively create a more immersive and engaging virtual environment by evaluating these opportunities and obstacles.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Codifying Character Logic in Role-Playing

    cs.CL 2025-05 conditional novelty 6.0 of 10

    Representing role-play personas as executable if-then-else logic with semantic condition checks improves consistency and lets 1B-parameter models approach the role-play quality of 8B text-prompted models.

Pith tools