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gpt-3
AI & Machine Learning2020–2024
openai / gpt-3 · Archived

gpt-3

GPT-3: Language Models are Few-Shot Learners

19Distinct people
22Mentions
0Explicit recommenders
15.7KGitHub stars
REPOSITORY AT A GLANCE

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What it is

GPT-3: Language Models are Few-Shot Learners

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

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Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 9:01:12 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year22 dated mentions

Observed mentions: 2020-05-29 01:47:27 UTC to 2024-05-13 11:32:35 UTC.

0369122020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 11 mentions; 3 submissions, 8 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 7 mentions; 1 submissions, 6 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC1138
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC202
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC716
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC202

What Hacker News says

7 sources
OpenAI publishes a huge amount of research and makes huge amounts of data available for research. They do collaborate with other institutions and researchers. eg: GPT-2: paper https://d4mucfpksywv.cloudfront.net/better-language-models/l... with code: https://github.com/openai/gpt-2, output dataset https://github.com/openai/gpt-2-output-dataset and a bunch of blog posts with all manner of details GPT-3: paper https://arxiv.org/abs/2005.14165 dataset https://github.com/openai/gpt-3 etc etc.
In OpenAI temporarily disables the Browse with Bing beta feature
>Certainly it is pleasing that they are not just doing Hindi, but some of these languages must be represented online by a very small corpus of text indeed. I wonder how effectively an LLM can be trained on such a small training set for any given language? as long as it's not the main language it doesn't really matter. Besides English(92.6%), the biggest language by representation (word count) is taken up by french at 1.8%. Most of the languages GPT-3 knows are sitting at <0.2% representation. https://github.com/openai/gpt-3/blob/master/dataset_statisti... Competence in the main language will bleed into the rest.
In BharatGPT: India's Own ChatGPT
Doesn't really matter. There's lots of positive transfer in individual language learning. Competence in one language bleeds into competence in others. https://arxiv.org/abs/2108.13349 GPT-3 is fluent in many languages despite English taking up 93% of the corpus by word count. French is next with 1.8% https://github.com/openai/gpt-3/blob/master/dataset_statisti... Dunno the statistics of language presence with GPT-4 but it takes it up another level in terms of its multilingual capabilities.
In Why is GPT-3 15.77x more expensive for certain languages?

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