Results 21 to 30 of about 98,573 (298)
AutoML-GPT: Automatic Machine Learning with GPT
CoRR, 2023 AI tasks encompass a wide range of domains and fields. While numerous AI models have been designed for specific tasks and applications, they often require considerable human efforts in finding the right model architecture, optimization algorithm, and hyperparameters.
Shujian Zhang +4 more
openaire +3 more sources
GPT-3.5 vs. GPT-4, Unveiling OpenAI’s Latest Breakthrough in Language Models
, 2023 OpenAI’s continuous efforts to push our knowledge and build on it for natural language processing have led to the development of GPT-4, the highly acclaimed successor of GPT-3.
Shehul Singh (17324920) +1 more
core +1 more source
DroidBot-GPT: GPT-powered UI Automation for Android
CoRR, 2023 8 pages, 5 ...
Hao Wen 0004 +3 more
openaire +3 more sources
monarch-initiative/gpt-ontology-completion-analysis: v0.1.0
, 2023 <h2>What's Changed</h2> <ul> <li>Update README.md by @oneilsh in https://github.com/monarch-initiative/gpt-ontology-completion-analysis/pull/2</li> <li>Update README.md by @sabrinatoro in https://github.com/monarch ...
Chris Mungall +3 more
core +1 more source
CoRR, 2022 This paper provides an introductory survey to GPT-3. We cover some of the historical development behind this technology, some of the key features of GPT-3, and discuss the machine learning model and the datasets used. We survey both academic and commercial efforts applying GPT-3 in diverse domains such as developing conversational AI chatbots, software
Mingyu Zong, Bhaskar Krishnamachari
openaire +2 more sources
, 2023 In recent years, deep learning has seen remarkable progress in many fields, especially with many excellent pre-training models emerged in Natural Language Processing(NLP).
Liang Xu (102656) +4 more
core +1 more source
Judgements of research co-created by Generative AI: Experimental evidence
Economics and Business Review, 2023 The introduction of ChatGPT has fuelled a public debate on the appropriateness of using Generative AI (large language models; LLMs) in work, including a debate on how they might be used (and abused) by researchers.
Niszczota Paweł, Conway Paul
doaj +1 more source
, 2023 In recent years, deep learning has seen remarkable progress in many fields, especially with many excellent pre-training models emerged in Natural Language Processing(NLP).
Liang Xu (102656) +4 more
core +1 more source
Frontiers in Chemistry, 2018 The major challenge for the pyrolytic conversion of lignocellulosic materials into crude bio-oil is the poor quality of the final product. Several strategies (addition of solvents, production of emulsions, and extraction with biodiesel) have been studied
Lucía Botella +9 more
doaj +1 more source
GPT-Neo: Large Scale Autoregressive Language Modeling with Mesh-Tensorflow
, 2021 GPT-Neo is an implementation of model & data-parallel GPT-2 and GPT-3-like models, utilizing Mesh Tensorflow for distributed support. This codebase is designed for TPUs.
Black, Sid +4 more
core +1 more source