AWS Machine Learning Blog

MARCH 21, 2025

In this post, we explore how you can use these multi-modal generative AI models to streamline the management of technical documents. Multi-modal generative AI models work well with text extraction from image files, so we start by converting the PDF to a collection of images, one for each page. samples/2003.10304/page_2.png"

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Marktechpost

SEPTEMBER 12, 2023

It leverages the capabilities of deep learning models, such as Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNNs). This AI Model Uses Image-to-Image Translation to Bring Ancient Fossils to Life appeared first on MarkTechPost.

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NVIDIA

OCTOBER 26, 2023

Researchers are taking deep learning for a deep dive, literally. The paper describes a model, called DeepSeeColor, that uses a sequence of two convolutional neural networks to reduce backscatter and correct colors in real time on the NVIDIA Jetson Orin NX while undersea.

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Unite.AI

OCTOBER 22, 2024

From recommending products online to diagnosing medical conditions, AI is everywhere. As AI models become more complex, they demand more computational power, putting a strain on hardware and driving up costs. For example, as model parameters increase, computational demands can increase by a factor of 100 or more.

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Viso.ai

DECEMBER 3, 2023

This article will explore the latest advances in pose analytics algorithms and AI vision techniques, their applications and use cases, and their limitations. With the latest advances in hardware and model efficiency, new applications with real-time requirements are becoming possible and economically feasible.

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Viso.ai

DECEMBER 19, 2023

Today, the use of convolutional neural networks (CNN) is the state-of-the-art method for image classification. Image Classification Using Machine Learning CNN Image Classification (Deep Learning) Example applications of Image Classification Let’s dive deep into it! How Does Image Classification Work?

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Viso.ai

OCTOBER 9, 2024

With the rapid development of Convolutional Neural Networks (CNNs) , deep learning became the new method of choice for emotion analysis tasks. Emotion Classification AI Model After pre-processing, the relevant features are retrieved from the pre-processed data containing the detected faces.

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Marktechpost

JULY 31, 2024

This article lists the top TensorFlow courses that can help you gain the expertise needed to excel in the field of AI and machine learning. It also delves into NLP with tokenization, embeddings, and RNNs and concludes with deploying models using TensorFlow Lite.

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Viso.ai

DECEMBER 1, 2023

As Artificial Intelligence (AI) models become more important and widespread in almost every sector, it is increasingly important for businesses to understand how these models work and the potential implications of using them. This guide will provide an overview of AI models and their various applications.

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NYU Center for Data Science

NOVEMBER 23, 2022

The model’s datasets are currently the largest publicly available for studying dementia CDS PhD student, Sheng Liu Alzheimer’s is the most prevalent form of dementia, and early diagnosis of the disease is essential to clinical trials and necessary treatments.

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Viso.ai

DECEMBER 10, 2023

This article will cover image recognition, an application of Artificial Intelligence (AI), and computer vision. Image recognition with deep learning is a key application of AI vision and is used to power a wide range of real-world use cases today. Therefore, we will cover the following topics: What is image recognition?

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Marktechpost

JUNE 22, 2023

One of the most groundbreaking and revolutionary works in this domain refers to state-of-the-art generative models called diffusion models. These models have completely transformed how textual descriptions can be used to generate high-quality images by harnessing the power of deep learning algorithms.

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Pickl AI

SEPTEMBER 25, 2024

Summary: This blog delves into 20 Deep Learning applications that are revolutionising various industries in 2024. From healthcare to finance, retail to autonomous vehicles, Deep Learning is driving efficiency, personalization, and innovation across sectors.

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NVIDIA

OCTOBER 4, 2023

The ALERTCalifornia initiative, a collaboration between California’s wildfire fighting agency CAL FIRE and the University of California, San Diego, uses advanced AI developed by DigitalPath. So Ethan Higgins, the company’s system architect, turned to AI.

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Marktechpost

DECEMBER 10, 2024

Artificial Neural Networks (ANNs) have become one of the most transformative technologies in the field of artificial intelligence (AI). Modeled after the human brain, ANNs enable machines to learn from data, recognize patterns, and make decisions with remarkable accuracy. How Do Artificial Neural Networks Work?

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Pickl AI

FEBRUARY 1, 2023

Transfer Learning in Deep Learning: A Brief Overview Collecting large volumes of data, filtering it and then interpreting is a challenging task. What if we say that you have the option of using a pre-trained model that works as a framework for data training? Yes, Transfer Learning is the answer to it.

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Marktechpost

SEPTEMBER 17, 2024

In deep learning, neural network optimization has long been a crucial area of focus. Training large models like transformers and convolutional networks requires significant computational resources and time. reduction in training time. Check out the Paper and GitHub Page.

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Viso.ai

FEBRUARY 25, 2024

In turn, this evolved into more sophisticated methods using machine learning and deep learning. Following that, the development of Convolutional Neural Networks (CNNs) was a watershed moment in the field. This involves estimating missing pixels by averaging the values of surrounding pixels. CT scans ).

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Marktechpost

JUNE 27, 2023

Artificial intelligence (AI) has made considerable advances over the past few years, becoming more proficient at activities previously only performed by humans. Yet, hallucination is a problem that has become a big obstacle for AI. They rely on massive visual training data in convolutional neural networks.

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Viso.ai

MARCH 26, 2024

Attention mechanisms allow artificial intelligence (AI) models to dynamically focus on individual elements within visual data. This enhances the interpretability of AI systems for applications in computer vision and natural language processing (NLP). without conventional neural networks. Vaswani et al.

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AssemblyAI

SEPTEMBER 22, 2023

In August – Meta released a tool for AI-generated audio named AudioCraft and open-sourced all of its underlying models, including MusicGen. Last week – StabilityAI launched StableAudio , a subscription-based platform for creating music with AI models.

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Unite.AI

JULY 31, 2023

This approach is known as self-supervised learning , and it’s one of the most efficient methods to build ML and AI models that have the “ common sense ” or background knowledge to solve problems that are beyond the capabilities of AI models today. It’s precisely the question that the SEER model aims to answer.

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NVIDIA

DECEMBER 21, 2023

Burning for solutions, developers are embracing AI for early detection. DigitalPath, based in Chico, California, has refined a convolutional neural network to spot wildfires. The startup has developed machine learning and AI models using data on fresh produce to help grocers make informed inventory-purchasing decisions.

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Unite.AI

AUGUST 29, 2023

In the past few years, Artificial Intelligence (AI) and Machine Learning (ML) have witnessed a meteoric rise in popularity and applications, not only in the industry but also in academia. Furthermore, developers have also proposed a model capable of running deep learning computations on edge devices, a TinyML model named TinyDL.

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Mlearning.ai

APRIL 8, 2023

2003) “ Support-vector networks ” by Cortes and Vapnik (1995) Significant people : David Blei Corinna Cortes Vladimir Vapnik 4. Deep Learning (Late 2000s — early 2010s) With the evolution of needing to solve more complex and non-linear tasks, The human understanding of how to model for machine learning evolved.

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Topbots

OCTOBER 4, 2023

Predictive AI is used to predict future events or outcomes based on historical data. For example, a predictive AI model can be trained on a dataset of customer purchase history data and then used to predict which customers are most likely to churn in the next month. virtual models for advertising campaigns).

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Viso.ai

OCTOBER 10, 2024

Trusted across industries, Viso Suite streamlines data processing, AI model training, and edge-based video analytics. We will elaborate on computer vision techniques like Convolutional Neural Networks (CNNs). 2019 , utilized unsupervised deep learning with large amounts of unlabeled images to learn robust features.

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Marktechpost

NOVEMBER 21, 2024

Foundational AI models, characterized by their extensive training data and remarkable adaptability, are proving to be exceptionally effective in utilizing accelerated computing for quantum computing applications. The emergence of generative artificial intelligence paradigms is now further expanding the computational landscape.

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Viso.ai

JANUARY 24, 2025

Architecture of LeNet5 – Convolutional Neural Network – Source The capacity of AGI to generalize and adapt across a broad range of tasks and domains is one of its primary features. Complex Training Process Deep Learning Large-scale datasets must be available for AGI system training.

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Chatbots Life

OCTOBER 9, 2023

Researchers are using microwave imaging and convolutional neural networks for breast cancer screening with high accuracy in classifying profiles as healthy or diseased. ? AI Startups: Transforming Business Potential ? Over $15 billion has been invested in generative AI companies in the first half of 2023. ?

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Viso.ai

DECEMBER 20, 2023

For example, if you want to build a supervised machine learning model to detect specific machine parts, you need to create an image dataset where all the images containing those parts are accurately labeled. Train a model: The AI model learns to associate certain features with certain labels.

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Pickl AI

OCTOBER 2, 2024

Summary: Artificial Intelligence (AI) is revolutionising Genomic Analysis by enhancing accuracy, efficiency, and data integration. Techniques such as Machine Learning and Deep Learning enable better variant interpretation, disease prediction, and personalised medicine.

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Viso.ai

DECEMBER 27, 2023

What is contrast learning? Contrastive learning is a technique used in machine learning, particularly in the field of unsupervised learning. Contrastive learning is a method where we teach an AI model to recognize similarities and differences of a large number of data points.

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Viso.ai

DECEMBER 18, 2023

ONNX (Open Neural Network Exchange) is an open-source format that facilitates interoperability between different deep learning algorithms for simple model sharing and deployment. ONNX (Open Neural Network Exchange) is an open-source format. A deep learning framework from Microsoft.

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Pickl AI

JULY 12, 2024

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. Introduction Artificial Intelligence (AI) transforms industries by enabling machines to mimic human intelligence.

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Pickl AI

SEPTEMBER 18, 2023

These AI systems can generate new data or content rather than simply analyzing or processing existing data. Natural language processing, computer vision, music composition, art generation, and other applications frequently employ generative AI models. How to get started with generative models in deep learning?

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Viso.ai

APRIL 25, 2024

Computer vision models enable the machine to extract, analyze, and recognize useful information from a set of images. Lightweight computer vision models allow the users to deploy them on mobile and edge devices. Today’s boom in CV started with the implementation of deep learning models and convolutional neural networks (CNN).

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