MiniGPT-4: Open-Source Model for Complex Vision-Language Tasks Like GPT-4: GPT-4, with its multimodal capabilities, has been at the forefront of artificial intelligence (AI) developments. Now, a team of researchers has announced the creation of… https://
analyticsvidhya.com/blog/2023/04/m
inigpt-4-open-source-model-for-complex-vision-language-tasks-like-gpt-4/?utm_source=dlvr.it&utm_medium=twitter
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MACHINE LEARNING
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MiniGPT-4 Open-Source Model for Complex Vision-Language Tasks
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Training biological neural networks for prompt optimization
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Train the biological neural network that does the prompting.
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NER and Related Questions Enhance AI Answer Depth
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Two features that help in answer depth and clarity: NER and related questions. In the answer, the system auto-underlines keywords. You can click them to learn more. After you get an answer, there is a related questions section to learn more about that topic (Google has this).
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Extract Insights from Unstructured Text with Deep Learning Models
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Get insights from your text. Over the years, we've built many state-of-art Deep Learning models. Today, you can use them to get insights from unstructured text. And the best part: At @abacusai
, we cover your solution end-to-end. Bring your data, and we will do the rest! -
Machine Learning Predicts Building Energy Use Efficiency
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Predicting Site EUI Using Machine Learning: Introduction According to a report by the International Energy Agency (IEA), the lifecycle of buildings from construction to demolition was responsible for 37% of global energy-related and process-related CO2… https://
analyticsvidhya.com/blog/2023/04/p
redicting-site-eui-using-machine-learning/?utm_source=dlvr.it&utm_medium=twitter
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Self Query Technology Expands to Weaviate Platform
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Self query is really powerful – excited to see it expand to weaviate!
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OpenAI’s Losses Doubled to $540 Million Developing ChatGPT
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OpenAI’s Losses Doubled to $540 Million as It Developed ChatGPT https://
bit.ly/3M0sdF2 #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Stanford releases string2string tool for NLP and bioinformatics research
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(3/3) We hope string2string will be a valuable asset for researchers & practitioners across NLP, bioinformatics, CSS, and the digital humanities. Join us in the world of strings! Code: https://
github.com/stanfordnlp/st
ring2string
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string2string.readthedocs.io/en/latest/ Paper: https://
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Stanford NLP releases string2string open-source library
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(1/3) Introducing string2string, an open-source library from StanfordNLP’s Mirac Suzgun (+me & @pmphlt
) for string-to-string problems, w/traditional & neural algorithms for string alignment, distance measurement, lexical & semantic search, similarity analysis, and more! -
Advanced Algorithms for NLP Evaluation and Text Analysis
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(2/3) Notable features include the Smith-Waterman, Hirschberg, Wagner-Fisher, and Knuth-Morris-Pratt algorithms, neural techniques like BARTScore, BERTScore, and Faiss, sacreBLEU & ROUGE for evaluation, and visualization tools & metrics for interpretation and analysis.