Unite.AI

NOVEMBER 5, 2024

The Artificial Intelligence (AI) chip market has been growing rapidly, driven by increased demand for processors that can handle complex AI tasks. The need for specialized AI accelerators has increased as AI applications like machine learning, deep learning , and neural networks evolve.

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NVIDIA

DECEMBER 19, 2024

GLAMlab Hair Try On is a digital experience that lets users take a photo, upload a headshot or use a models picture to experiment with different hair colors and styles. Used by thousands of web and mobile app users daily, the experience is powered by the NVIDIA StyleGAN2 generative AI model.

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Analytics Vidhya

JUNE 4, 2023

In a groundbreaking development, NVIDIA Research has unveiled its latest AI model, Neuralangelo. The innovative model utilizes neural networks to reconstruct 3D scenes and objects from 2D video clips.

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Unite.AI

MARCH 2, 2025

Artificial Intelligence (AI) is evolving at an unprecedented pace, with large-scale models reaching new levels of intelligence and capability. From early neural networks to todays advanced architectures like GPT-4 , LLaMA , and other Large Language Models (LLMs) , AI is transforming our interaction with technology.

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Towards AI

DECEMBER 16, 2024

The Top 10 AI Research Papers of 2024: Key Takeaways and How You Can Apply Them Photo by Maxim Tolchinskiy on Unsplash As the curtains draw on 2024, its time to reflect on the innovations that have defined the year in AI. Key Contributions: Frameworks for fairness in multi-modal AI. And lets be real what a year it has been!

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Unite.AI

DECEMBER 26, 2024

These algorithms are called Convolutional Neural Networks (CNN), and they contain a database of the gyroscopic movements associated with a variety of daily living activities. Telehealth data is further informed by wearable devices integrated with AI, which enhance monitoring by continuously gathering and analyzing health data.

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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. One of the central challenges in this field is the extended time needed to train complex neural networks.

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Viso.ai

DECEMBER 20, 2023

The computer vision annotation tool CVAT provides a powerful solution for image annotation in computer vision. Computational vision is the research field that uses machines to collect and analyze images and videos to extract information from processed visual data. Get a demo or the whitepaper.

Computer Vision 98

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NVIDIA

MARCH 3, 2025

Among Ai2s efforts with EarthRanger is the planned development of a machine learning model trained using NVIDIA Hopper GPUs in the cloud that predicts the movement of elephants in areas close to human-wildlife boundaries where elephants could raid crops and potentially prompt humans to retaliate. A lion detected with WPS technologies.

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Viso.ai

FEBRUARY 25, 2024

Image reconstruction is an AI-powered process central to computer vision. In this article, we’ll provide a deep dive into using computer vision for image reconstruction. About Us: Viso Suite is the end-to-end computer vision platform helping enterprises solve challenges across industry lines.

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NVIDIA

OCTOBER 25, 2023

10-16 in New Orleans, NeurIPS brings together experts in generative AI, machine learning, computer vision and more. Picture This: Improving Text-to-Image Diffusion Models Diffusion models have become the most popular type of generative AI models to turn text into realistic imagery. Set for Dec.

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Unite.AI

JANUARY 22, 2025

The system's intelligence stems from its neural network-based Concept Processor, which observes and learns from every interaction. As physicians document patient encounters, the AI identifies patterns in their clinical reasoning and documentation style.

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Unite.AI

NOVEMBER 6, 2023

In recent years, Generative AI has shown promising results in solving complex AI tasks. Modern AI models like ChatGPT , Bard , LLaMA , DALL-E.3 Moreover, Multimodal AI techniques have emerged, capable of processing multiple data modalities, i.e., text, images, audio, and videos simultaneously.

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Viso.ai

DECEMBER 20, 2023

In the field of computer vision, supervised learning and unsupervised learning are two of the most important concepts. In this guide, we will explore the differences and when to use supervised or unsupervised learning for computer vision tasks. We will also discuss which approach is best for specific applications.

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AI Weekly

SEPTEMBER 21, 2023

pitneybowes.com In The News How Google taught AI to doubt itself Today let’s talk about an advance in Bard, Google’s answer to ChatGPT, and how it addresses one of the most pressing problems with today’s chatbots: their tendency to make things up. [Get your FREE eBook.] Get your FREE eBook.]

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Unite.AI

MAY 29, 2024

This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction. Typically, the generative AI model provides a prompt describing the desired data, and the ensuing response contains the extracted data.

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PyImageSearch

JANUARY 13, 2025

To learn how to master YOLO11 and harness its capabilities for various computer vision tasks , just keep reading. YOLO11 is the newest version of the popular Ultralytics YOLO (You Only Look Once) series of real-time object detection models. Validation: Evaluate model performance on a validation dataset.

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Viso.ai

DECEMBER 18, 2023

As an Edge AI implementation, TensorFlow Lite greatly reduces the barriers to introducing large-scale computer vision with on-device machine learning, making it possible to run machine learning everywhere. About us: At viso.ai, we power the most comprehensive computer vision platform Viso Suite. What is TensorFlow?

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IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more.

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Unite.AI

AUGUST 2, 2023

They require a high amount of computational power. These limitations are a major issue why an average human mind is able to learn from a single type of data much more effectively when compared to an AI model that relies on separate models & training data to distinguish between an image, text, and speech.

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Marktechpost

DECEMBER 16, 2023

Researchers from various universities in the UK have developed an open-source artificial intelligence (AI) system, X-Raydar, for comprehensive chest x-ray abnormality detection. The researchers also developed web-based tools, allowing public access to the AI models for real-time chest x-ray interpretation.

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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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AI Weekly

JANUARY 18, 2024

We need a careful balance of policies to tap its potential imf.org AI Ethics in the Spotlight: Examining Public Concerns in 2024 In the early days of January 2024, there were discussions surrounding Midjourney, a prominent player in the AI image-generation field.

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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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Marktechpost

JANUARY 12, 2024

Models tailored for 2D images, such as those based on convolutional neural networks, need to be revised for interpreting complex 3D environments. Models designed for 3D spatial data, like point cloud processors, often fail to effectively leverage the rich detail available in 2D imagery. Check out the Paper and Project.

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Unite.AI

FEBRUARY 21, 2024

Computer vision is a field of artificial intelligence that aims to enable machines to understand and interpret visual information, such as images or videos. Computer vision has many applications in various domains, such as medical imaging, security, autonomous driving, and entertainment.

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Marktechpost

SEPTEMBER 12, 2023

Image-to-image translation (I2I) is an interesting field within computer vision and machine learning that holds the power to transform visual content from one domain into another seamlessly. It leverages the capabilities of deep learning models, such as Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNNs).

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Marktechpost

JULY 31, 2024

TensorFlow is a powerful open-source framework for building and deploying machine learning models. Learning TensorFlow enables you to create sophisticated neural networks for tasks like image recognition, natural language processing, and predictive analytics.

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IBM Journey to AI blog

FEBRUARY 14, 2024

Companies also take advantage of ML in smartphone cameras to analyze and enhance photos using image classifiers, detect objects (or faces) in the images, and even use artificial neural networks to enhance or expand a photo by predicting what lies beyond its borders. Computer vision guides self-driving cars.

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Marktechpost

JULY 4, 2023

The 3D computer vision domain was flooded with NeRFs in recent years. NeRFs capture and model the underlying geometry and appearance information from a collection of multi-view images. By leveraging neural networks, NeRFs offer a data-driven approach that surpasses traditional methods.

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Marktechpost

APRIL 21, 2024

Computer vision has advanced significantly in recent decades, thanks in large part to comprehensive benchmark datasets like COCO. However, nearly a decade after its introduction, COCO’s suitability as a benchmark for modern AI models is being questioned. Check out the Paper and Project.

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Viso.ai

SEPTEMBER 2, 2024

As many areas of artificial intelligence (AI) have experienced exponential growth, computer vision is no exception. According to the data from the recruiting platforms – job listings that look for artificial intelligence or computer vision specialists doubled from 2021 to 2023.

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Unite.AI

JANUARY 8, 2025

Dataset examples from the 2020 paper ‘Asian Female Facial Beauty Prediction Using Deep Neural Networks via Transfer Learning and Multi-Channel Feature Fusion'. It could be argued that a FAP system is inherently predisposed to reinforce and perpetuate partial and biased perspectives on attractiveness.

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Viso.ai

MAY 17, 2024

Neural Networks have changed the way we perform model training. With the increase in the usage of the internet and computer systems, the availability of data has become easy. Neural networks, sometimes referred to as Neural Nets, need large datasets for efficient training. About us : Viso.ai

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Unite.AI

APRIL 9, 2024

The adoption of Artificial Intelligence (AI) has increased rapidly across domains such as healthcare, finance, and legal systems. However, this surge in AI usage has raised concerns about transparency and accountability. Composite AI is a cutting-edge approach to holistically tackling complex business problems.

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Marktechpost

FEBRUARY 22, 2024

The progress and development of artificial intelligence (AI) heavily rely on human evaluation, guidance, and expertise. In Natural Language Processing (NLP), recurrent neural networks and Transformers can learn the intricacies of language from vast amounts of unsupervised text generated by humans.

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IBM Journey to AI blog

NOVEMBER 29, 2023

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

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