Sea Change in Software Development: Economic and Productivity Analysis of the AI-Powered Developer Lifecycle research paper by GitHub, 2023
GitHub · Foundation models · Jun 26, 2023 · 52 citations
What it shows
Across nearly a million Copilot users, developers accepted about 30% of suggested code, with the highest acceptance among less experienced developers.
By Thomas Dohmke, Marco Iansiti, Greg Richards · arXiv 2306.15033 · PDF
Summarised by hand from the abstract.
More from GitHub
All 3The Impact of AI on Developer Productivity: Evidence from GitHub CopilotIn a controlled experiment, developers with GitHub Copilot finished a programming task 55.8% faster than those without it.
GitHub906 citationsRead →Productivity Assessment of Neural Code CompletionFinds that how often developers accept Copilot's suggestions, more than other usage measures, predicts how productive they feel.
GitHub349 citationsRead →
Other foundation models papers
TopicBERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingPre-training a Transformer to fill in masked words, then fine-tuning it, beat task-specific models across language understanding tests.
Google125k citations33 upvotesRead →Language Models are Few-Shot LearnersGPT-3, a 175B-parameter model, does new tasks from a few examples in the prompt, with no fine-tuning.
OpenAI66.4k citations21 upvotesRead →GPT-4 Technical ReportA multimodal model that passes a simulated bar exam with a score around the top 10% of test takers.
OpenAI28.4k citations7 upvotesRead →LLaMA: Open and Efficient Foundation Language ModelsOpen models from 7B to 65B trained only on public data; the 13B model beats GPT-3 on most benchmarks.
Meta22.6k citations25 upvotesRead →The Llama 3 Herd of ModelsOpen models up to 405B parameters that match leading closed models on many tasks.
Meta20.8k citations119 upvotesRead →Qwen3 Technical ReportQwen3, a unified series of large language models, integrates thinking and non-thinking modes, reduces computational resources, and achieves state-of-the-art performance across various tasks and languages.
Alibaba (Qwen)10.1k citations339 upvotesRead →
About this paper
- Citations
- 52, 8 influential · Semantic Scholar
- Upvotes
- - · Hugging Face
- Lab
- GitHub · on Companies · on Paydays · on Releases
Changes
Influential citations rose from 7 to 8.
Citations rose from 50 to 52.
Citations rose from 47 to 50.
A first count of 7 influential citations.
A first count of 47 citations.
Added to the list.