Google Research AI blog

FEBRUARY 10, 2023

We also had a number of interesting results on graph neural networks (GNN) in 2022. Relative performance results of three GNN variants ( GCN , APPNP , FiLM ) across 50,000 distinct node classification datasets in GraphWorld. We provided a model-based taxonomy that unified many graph learning methods.

Algorithm 110

Algorithm Neural Network Auto-classification ML 110

Marktechpost

SEPTEMBER 13, 2024

Also, the application of SoftmaxAttn necessitates a row-wise reduction along the input sequence length, which can significantly slow down computations, particularly when using efficient attention kernels. Recent research in machine learning has explored alternatives to the traditional softmax function in various domains.

Auto-classification 104

Auto-classification Neural Network Machine Learning Computer Vision 104

Google Research AI blog

JANUARY 18, 2023

I will begin with a discussion of language, computer vision, multi-modal models, and generative machine learning models. Over the next several weeks, we will discuss novel developments in research topics ranging from responsible AI to algorithms and computer systems to science, health and robotics. Let’s get started!

Computer Vision 132

Computer Vision Auto-classification Large Language Models Neural Network 132

AWS Machine Learning Blog

JUNE 12, 2023

It can support a wide variety of use cases, including text classification, token classification, text generation, question and answering, entity extraction, summarization, sentiment analysis, and many more. Deep learning (DL) models with more layers and parameters perform better in complex tasks like computer vision and NLP.

Deep Learning 95

Deep Learning Auto-classification Computer Vision Machine Learning 95

AWS Machine Learning Blog

MAY 31, 2023

PyTorch is a machine learning (ML) framework based on the Torch library, used for applications such as computer vision and natural language processing. PyTorch supports dynamic computational graphs, enabling network behavior to be changed at runtime.

ML 119

ML Auto-classification Auto-complete Natural Language Processing 119

The MLOps Blog

JANUARY 23, 2025

A typical multimodal LLM has three primary modules: The input module comprises specialized neural networks for each specific data type that output intermediate embeddings. An output could be, e.g., a text, a classification (like “dog” for an image), or an image. Examples of different Kosmos-1 tasks.

Large Language Models 59

Large Language Models Auto-classification LLM Robotics 59

AWS Machine Learning Blog

MARCH 28, 2024

You can deploy this solution with just a few clicks using Amazon SageMaker JumpStart , a fully managed platform that offers state-of-the-art foundation models for various use cases such as content writing, code generation, question answering, copywriting, summarization, classification, and information retrieval.

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LLM Auto-complete Auto-classification Generative AI 136

Pickl AI

JANUARY 23, 2023

This framework can perform classification, regression, etc., but performs very well with neural networks. Keras supports a high-level neural network API written in Python. Deep Python integration makes it possible to easily create neural network layers in Python using well-known modules and packages.

Machine Learning 52

Machine Learning ML Neural Network Auto-classification 52

DataRobot Blog

MAY 18, 2022

For this example, we only use binary classification—does this bag contain a firearm or not? Another obstacle to creating high performing computer vision models is that training datasets may not contain sufficient images of the target object with different backgrounds and from different directions. Image Augmentation Examples.

Visual AI 52

Visual AI Auto-classification Neural Network Computer Vision 52

Viso.ai

DECEMBER 22, 2023

The Segment Anything Model (SAM), a recent innovation by Meta’s FAIR (Fundamental AI Research) lab, represents a pivotal shift in computer vision. SAM performs segmentation, a computer vision task , to meticulously dissect visual data into meaningful segments, enabling precise analysis and innovations across industries.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Auto-classification 52

The MLOps Blog

JUNE 27, 2023

Some of its features include a data labeling workforce, annotation workflows, active learning and auto-labeling, scalability and infrastructure, and so on. The platform provides a comprehensive set of annotation tools, including object detection, segmentation, and classification. Robust security functionality.

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Machine Learning Metadata Data Scientist Data Quality 134

Mlearning.ai

MAY 23, 2023

Classification is very important in machine learning. Hence, we have various classification algorithms in machine learning like logistic regression, support vector machine, decision trees, Naive Bayes classifier, etc. One such classification technique that is near the top of the classification hierarchy is the random forest classifier.

Data Science 52

Data Science Neural Network Deep Learning Machine Learning 52

Dlabs.ai

JANUARY 16, 2023

The Mayo Clinic sponsored the Mayo Clinic – STRIP AI competition focused on image classification of stroke blood clot origin. Typical Neural Network architectures take relatively small images (for example, EfficientNetB0 224x224 pixels) as input. Tile embedding Computer vision is a complex problem.

Neural Network 52

Neural Network ML Auto-classification Convolutional Neural Networks 52

Jay Alammar

DECEMBER 16, 2020

This article focuses on auto-regressive models, but these methods are applicable to other architectures and tasks as well. The literature is most often concerned with this application for classification tasks, rather than natural language generation. to perform well across various datasets for text classification in transformer models.

Explainability 52

Explainability Auto-classification Auto-complete Neural Network 52

AWS Machine Learning Blog

JANUARY 31, 2024

In this post, we present an approach to develop a deep learning-based computer vision model to detect and highlight forged images in mortgage underwriting. We provide guidance on building, training, and deploying deep learning networks on Amazon SageMaker. The model outputs the classification as 1, representing a forged image.

Computer Vision 121

Computer Vision Auto-complete Deep Learning Auto-classification 121

Flipboard

APRIL 13, 2023

Prime Air (our drones) and the computer vision technology in Amazon Go (our physical retail experience that lets consumers select items off a shelf and leave the store without having to formally check out) use deep learning. To give a sense for the change in scale, the largest pre-trained model in 2019 was 330M parameters.

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Generative AI ML AI AI 182

AWS Machine Learning Blog

AUGUST 8, 2023

These complex models often require hardware acceleration because it enables not only faster training but also faster inference when using deep neural networks in real-time applications. GPUs’ large number of parallel processing cores makes them well-suited for these DL tasks.

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BERT Deep Learning Auto-classification Python 98