Unite.AI

AUGUST 1, 2023

OpenAI has been instrumental in developing revolutionary tools like the OpenAI Gym, designed for training reinforcement algorithms, and GPT-n models. The spotlight is also on DALL-E, an AI model that crafts images from textual inputs. Generative models like GPT-4 can produce new data based on existing inputs.

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AssemblyAI

JANUARY 23, 2025

It works by analyzing audio signals, identifying patterns, and matching them to words and phrases using advanced algorithms. The primary drawbacks of cloud-based solutions are their cost and the lack of control over the underlying infrastructure and algorithms, as they are managed by the service provider. Signup Now

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Unite.AI

AUGUST 2, 2023

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. In this article, we will be talking about the data2vec model in-depth.

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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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AWS Machine Learning Blog

NOVEMBER 26, 2024

However, LLMs such as Anthropic’s Claude 3 Sonnet on Amazon Bedrock can also perform these tasks using zero-shot prompting, which refers to a prompting technique to give a task to the model without providing specific examples or training for that specific task. The image was generated using the Stability AI model (SDXL 1.0)

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Unite.AI

SEPTEMBER 9, 2024

Central to this development was a convolutional neural network, trained using Q-learning , which processed raw screen pixels and converted them into game-specific actions based on the current state. The researchers applied this model to seven Atari 2600 games without modifying the architecture or learning algorithm.

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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. It uses AI-based deep learning models to analyze images with results that for specific tasks already surpass human-level accuracy (for example, in face recognition ). How Does Image Classification Work?

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Viso.ai

OCTOBER 9, 2024

AI emotion recognition is a very active current field of computer vision research that involves facial emotion detection and the automatic assessment of sentiment from visual data and text analysis. This solution enables leading companies to build, deploy, and scale their AI vision applications, including AI emotion analysis.

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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. spam detection) and regression (e.g.,

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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. To design it, the developers used the gestures data set, and used the data set to train the ProtoNN model with a classification algorithm.

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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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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

JUNE 12, 2024

AI can provide precise diagnostics, optimize treatment strategies, and predict disease progression by processing and interpreting large, diverse datasets. Synergies Between AI and Digital Pathology: Advances in DL and image processing are revolutionizing digital pathology.

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Topbots

OCTOBER 4, 2023

Generated with Bing and edited with Photoshop Predictive AI has been driving companies’ ROI for decades through advanced recommendation algorithms, risk assessment models, and fraud detection tools. However, the recent surge in generative AI has made it the new hot topic. virtual models for advertising campaigns).

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Marktechpost

JANUARY 15, 2025

Technical Details and Benefits Deep learning relies on artificial neural networks composed of layers of interconnected nodes. Notable architectures include: Convolutional Neural Networks (CNNs): Designed for image and video data, CNNs detect spatial patterns through convolutional operations.

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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. As a result, an AI might be unable to distinguish between potato chips and changing leaves.

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Unite.AI

FEBRUARY 21, 2024

This article focuses on a specific type of computer vision model, called Large Vision Models (LVMs), and how they can be leveraged for domain-specific tasks through transfer learning. What are Large Vision Models (LVMs)? LVMs are advanced AI models that process and interpret visual data, typically images or videos.

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Viso.ai

FEBRUARY 25, 2024

Following that, the development of Convolutional Neural Networks (CNNs) was a watershed moment in the field. The introduction of the Super-Resolution Convolutional Neural Network (SRCNN) later demonstrated that deep learning models could outperform traditional image resolution methods.

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Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. Evolution of NLP Models To understand the full impact of the above evolutionary process.

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NVIDIA

OCTOBER 26, 2023

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. candidate at MIT and AI developer at WARPLab. candidate in the MIT-WHOI joint program.

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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.

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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

DECEMBER 20, 2023

Supervised learning is a type of machine learning algorithm that learns from a set of training data that has been labeled training data. Typical computer vision tasks of supervised learning algorithms include object detection, visual recognition, and classification. from a set of images. to an image.

Computer Vision 98

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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). CV models need labeled data to process the satellite imagery. Caron et al.,

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Marktechpost

SEPTEMBER 23, 2024

Life and other CA algorithms are computationally simple, yet they generate complex and unpredictable dynamics highly sensitive to initial conditions. This unpredictability complicates the development of AI models that can generalize across varying grid configurations and boundary conditions.

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TransOrg Analytics

FEBRUARY 11, 2025

A key subset of AI is Machine Learning (ML), which powers many of these experiences by identifying patterns and making predictions based on large volumes of datawithout explicit programming. However, complex ML algorithms can often function as black boxes , producing outcomes without clear insights into how decisions were made.

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Viso.ai

DECEMBER 21, 2023

Over the past decade, the field of computer vision has experienced monumental artificial intelligence (AI) breakthroughs. This research significantly bridged the gap between academic exploration and practical applications of AI. Here, he leveraged convolutional neural networks for pattern recognition and object detection.

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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. ? Three criteria for evaluating innovative potential in AI: real-world implications, prolonged market impact, and sustainable implementation. ?

Convolutional Neural Networks 52

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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. Therefore, a model trained on such a biased dataset may use the erroneous data to generate erroneous predictions.

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Pickl AI

OCTOBER 2, 2024

AI Techniques Used in Genomic Analysis AI encompasses a range of techniques that can be applied to genomic Data Analysis. Some of the most prominent AI techniques used in this field include: Machine Learning Machine Learning algorithms are designed to learn from data and make predictions or decisions based on that data.

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Pickl AI

APRIL 9, 2025

A simple example could be an early chess-playing program that evaluated moves based on predefined rules and search algorithms. It’s a specific approach to achieving AI. Instead of hard-coding rules, ML algorithms are designed to learn patterns and make predictions or decisions based on data they are “trained” on.

Deep Learning 52

Deep Learning Artificial Intelligence Artificial Intelligence Explainability 52

NVIDIA

FEBRUARY 7, 2024

With advances in computing, sophisticated AI models and machine learning are having a profound impact on business and society. Industries can use AI to quickly analyze vast bodies of data, allowing them to derive meaningful insights, make predictions and automate processes for greater efficiency.

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Pickl AI

FEBRUARY 1, 2023

Transfer Learning is a technique in Machine Learning where a model is pre-trained on a large and general task. Since this technology operates in transferring weights from AI models, it eventually makes the training process for newer models faster and easier.

Deep Learning 52

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Pickl AI

JULY 12, 2024

Jupyter notebooks are widely used in AI for prototyping, data visualisation, and collaborative work. Their interactive nature makes them suitable for experimenting with AI algorithms and analysing data. Importance of Data in AI Quality data is the lifeblood of AI models, directly influencing their performance and reliability.

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Viso.ai

DECEMBER 6, 2023

Computer vision (CV) is a rapidly evolving area in artificial intelligence (AI), allowing machines to process complex real-world visual data in different domains like healthcare, transportation, agriculture, and manufacturing. Edge AI involves processing data near the source. Get a demo here.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Categorization 52

Mlearning.ai

MARCH 26, 2023

The advent of generative AI models like ChatGPT has made this an even more exciting time to delve into data science. Split the dataset and apply simple machine learning models (like logistic regression or decision trees) to predict survival rates. Evaluate your model and tweak it.

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Viso.ai

DECEMBER 3, 2023

Pose estimation is a fundamental task in computer vision and artificial intelligence (AI) that involves detecting and tracking the position and orientation of human body parts in images or videos. Today, the most powerful image processing models are based on convolutional neural networks (CNNs).

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