Remove AI Research Remove Computer Vision Remove Natural Language Processing
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A Comprehensive Guide on i-Transformer

Analytics Vidhya

Introduction Transformers have revolutionized various domains of machine learning, notably in natural language processing (NLP) and computer vision. Their ability to capture long-range dependencies and handle sequential data effectively has made them a staple in every AI researcher and practitioner’s toolbox.

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20 GitHub Repositories to Master Natural Language Processing (NLP)

Marktechpost

Natural Language Processing (NLP) is a rapidly growing field that deals with the interaction between computers and human language. Transformers is a state-of-the-art library developed by Hugging Face that provides pre-trained models and tools for a wide range of natural language processing (NLP) tasks.

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Rethinking Reproducibility As the New Frontier in AI Research

Unite.AI

In particular, the instances of irreproducible findings, such as in a review of 62 studies diagnosing COVID-19 with AI , emphasize the necessity to reevaluate practices and highlight the significance of transparency. Multiple factors contribute to the reproducibility crisis in AI research.

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Microsoft Research Introduces Florence-2: A Novel Vision Foundation Model with a Unified Prompt-based Representation for a Variety of Computer Vision and Vision-Language Tasks

Marktechpost

Natural language processing (NLP) is a good example of this tendency since sophisticated models demonstrate flexibility with thorough knowledge covering several domains and tasks with straightforward instructions. The popularity of NLP encourages a complementary strategy in computer vision.

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A New AI Research Proposes VanillaNet: A Novel Neural Network Architecture Emphasizing the Elegance and Simplicity of Design while Retaining Remarkable Performance in Computer Vision Tasks

Marktechpost

These networks may carry out a range of human-like activities, including face recognition, speech recognition, object identification, natural language processing, and content synthesis, which include several layers and a lot of neurons or transformer blocks.

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AI trends in 2023: Graph Neural Networks

AssemblyAI

What is the current role of GNNs in the broader AI research landscape? Let’s take a look at some numbers revealing how GNNs have seen a spectacular rise within the research community. We find that the term Graph Neural Network consistently ranked in the top 3 keywords year over year.

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Understanding the different types and kinds of Artificial Intelligence

IBM Journey to AI blog

Theory of Mind AI would also be able to understand and contextualize artwork and essays, which today’s generative AI tools are unable to do. Emotion AI is a theory of mind AI currently in development. This allows intelligent machines to identify and classify objects within images and video footage.