Unite.AI

MAY 29, 2024

With nine times the speed of the Nvidia A100, these GPUs excel in handling deep learning workloads. This architecture, leveraging neural networks like RNNs and Transformers, finds applications in diverse domains, including machine translation, image generation, speech synthesis, and data entity extraction.

Data Extraction 273

Data Extraction Neural Network Large Language Models NLP 273

ML Review

MARCH 31, 2019

We start with an image of a panda, which our neural network correctly recognizes as a “panda” with 57.7% Add a little bit of carefully constructed noise and the same neural network now thinks this is an image of a gibbon with 99.3% This is, clearly, an optical illusion — but for the neural network.

Neural Network 52

Neural Network Machine Learning Deep Learning Explainability 52

Unite.AI

NOVEMBER 14, 2024

Founded in 2017, DeepL today has over 1,000 passionate employees and is supported by world-renowned investors including Benchmark, IVP, and Index Ventures. When I started the company back in 2017, we were at a turning point with deep learning. It had really started to gain traction, which inspired the name of our company.

Neural Network 130

Neural Network LLM Large Language Models AI Modeling 130

John Snow Labs

JUNE 2, 2023

Spark NLP’s deep learning models have achieved state-of-the-art results on sentiment analysis tasks, thanks to their ability to automatically learn features and representations from raw text data. There are separate blog posts for the rule-based systems and for statistical methods.

Deep Learning 98

Deep Learning NLP Convolutional Neural Networks Neural Network 98

PyImageSearch

JANUARY 2, 2023

This blog will cover the benefits, applications, challenges, and tradeoffs of using deep learning in healthcare. Computer Vision and Deep Learning for Healthcare Benefits Unlocking Data for Health Research The volume of healthcare-related data is increasing at an exponential rate.

Computer Vision 52

Computer Vision Deep Learning Neural Network Machine Learning 52

Unite.AI

JULY 29, 2024

Neural Machine Translation (NMT) In 2016, Google made the switch to Neural Machine Translation. It uses deep learning models to translate entire sentences as a whole and at once, giving more fluent and accurate translations. NMT operates similarly to having a sophisticated multilingual assistant within your computer.

Neural Network 264

Neural Network Deep Learning Machine Learning Automation 264

Flipboard

MARCH 27, 2023

Project Structure Accelerating Convolutional Neural Networks Parsing Command Line Arguments and Running a Model Evaluating Convolutional Neural Networks Accelerating Vision Transformers Evaluating Vision Transformers Accelerating BERT Evaluating BERT Miscellaneous Summary Citation Information What’s New in PyTorch 2.0?

Convolutional Neural Networks 158

Convolutional Neural Networks Neural Network BERT Deep Learning 158

Flipboard

MARCH 13, 2023

OpenAI has pioneered a technique to shape its models’ behaviors using something called reinforcement learning with human feedback (RLHF). Having a human periodically check on the reinforcement learning system’s output and give feedback allows reinforcement learning systems to learn even when the reward function is hidden.

ChatGPT 172

ChatGPT Large Language Models Neural Network Deep Learning 172

Towards AI

JUNE 6, 2023

Now it’s possible to have deep learning models with no limitation for the input size. unsplash Attention-based transformers have revolutionized the AI industry since 2017.

Neural Network 90

Neural Network Computer Vision Deep Learning NLP 90

Viso.ai

DECEMBER 3, 2023

The recent deep learning algorithms provide robust person detection results. However, deep learning models such as YOLO that are trained for person detection on a frontal view data set still provide good results when applied for overhead view person counting ( TPR of 95%, FPR up to 0.2% ).

Convolutional Neural Networks 98

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 98

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?

Convolutional Neural Networks 98

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 98

Marktechpost

MARCH 25, 2024

These models use deep learning techniques, particularly neural networks, to process and produce text that mimics human-like understanding and responses. LLMs Core: Transformer Architecture The transformer architecture, introduced in 2017, is at the core of LLMs. What are Large Language Models?

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ChatGPT Neural Network Large Language Models BERT 133

Explosion

JANUARY 12, 2018

Declined 36 opportunities to “touch base” with investors and other professional networkers, who were confused by our radical we-spend-our-time-working approach. spaCy In 2017 spaCy grew into one of the most popular open-source libraries for Artificial Intelligence. spaCy’s Machine Learning library for NLP in Python.

NLP 52

NLP Neural Network Machine Learning Python 52

Viso.ai

DECEMBER 10, 2023

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. I n past years, machine learning, in particular deep learning technology , has achieved big successes in many computer vision and image understanding tasks.

Convolutional Neural Networks 98

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 98

Mlearning.ai

APRIL 8, 2023

Over the years, we evolved that to solving NLP use cases by adopting Neural Network-based algorithms loosely based on the structure and function of a human brain. 2003) “ Support-vector networks ” by Cortes and Vapnik (1995) Significant people : David Blei Corinna Cortes Vladimir Vapnik 4.

NLP 98

NLP Neural Network Natural Language Processing Convolutional Neural Networks 98

Towards AI

AUGUST 25, 2023

Machine learning (ML) is a subset of AI that provides computer systems the ability to automatically learn and improve from experience without being explicitly programmed. Deep learning (DL) is a subset of machine learning that uses neural networks which have a structure similar to the human neural system.

Software Engineer 95

Software Engineer Machine Learning Neural Network Artificial Intelligence 95

Viso.ai

OCTOBER 10, 2024

We will elaborate on computer vision techniques like Convolutional Neural Networks (CNNs). Data Preprocessing Although the satellite data is already prepared and ready for analysis, there are a few more processing steps – before using the data in a deep learning model. Model Training Miller et al. Caron et al.,

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Deep Learning 52

Unite.AI

MAY 8, 2024

He began his career at Yandex in 2017, concurrently studying at the Yandex School of Data Analysis. There, I learned a lot about more advanced machine learning algorithms and built my intuition. The most crucial point during this process was when I learned about neural networks and deep learning.

Machine Learning 298

Machine Learning Software Engineer Large Language Models Data Analysis 298

Heartbeat

OCTOBER 24, 2023

Open Neural Network Exchange, or ONNX, is a free and open-source ecosystem for deep learning model representation. Facebook and Microsoft created this tool in 2017 to make it simpler for academics and engineers to migrate models between various deep-learning frameworks and hardware platforms.

Neural Network 52

Neural Network Deep Learning Data Scientist Machine Learning 52

Viso.ai

MAY 7, 2024

GoogLeNet’s deep learning model was deeper than all the previous models released, with 22 layers in total. Increasing the depth of the Machine Learning model is intuitive, as deeper models tend to have more learning capacity and as a result, this increases the performance of a model.

Explainability 52

Explainability Convolutional Neural Networks Neural Network Deep Learning 52

Viso.ai

FEBRUARY 11, 2024

Image classification employs AI-based deep learning models to analyze images and perform object recognition, as well as a human operator. It is one of the largest resources available for training deep learning models in object recognition tasks. They applied deep CNN over pre-trained ImageNet-1K, with 24.2M

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 52

Viso.ai

MARCH 12, 2024

Today’s boom in computer vision (CV) started at the beginning of the 21 st century with the breakthrough of deep learning models and convolutional neural networks (CNN). We split them into two categories – classical CV approaches, and papers based on deep-learning. Find the SURF paper here.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Deep Learning 52

AssemblyAI

MAY 3, 2023

This process of adapting pre-trained models to new tasks or domains is an example of Transfer Learning , a fundamental concept in modern deep learning. Transfer learning allows a model to leverage the knowledge gained from one task and apply it to another, often with minimal additional training.

Large Language Models 363

Large Language Models Neural Network LLM ChatGPT 363

Viso.ai

JULY 17, 2024

Image analogies patch-based texture in-filling for artistic rendering – source The field of Neural style transfer took a completely new turn with Deep Learning. With deep learning, the results were impressively good. Here is the journey of NST. Gatys et al. 2015) The research paper by Leon A.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

Viso.ai

JULY 9, 2024

Neural Networks For now, most attempts to develop ASI are still grounded in well-known models, such as neural networks , machine learning/deep learning , and computational neuroscience. Estimates for when we would achieve AGI range from the next 5 to 30 years.

Neural Network 52

Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

Heartbeat

FEBRUARY 6, 2023

In the second step, these potential fields are classified and corrected by the neural network model. R-CNN (Regions with Convolutional Neural Networks) and similar two-stage object detection algorithms are the most widely used in this regard. In the first step, potential object areas in the image are determined.

Algorithm 90

Algorithm Convolutional Neural Networks Neural Network Computer Vision 90

Viso.ai

JUNE 26, 2024

The Concept of Neuromorphic Engineering [ Source ] Core Principles of Neuromorphic Engineering The core principle of neuromorphic engineering is to develop models that replicate the working mechanism of biological neural networks and process information just like a human brain does.

Neural Network 40

Neural Network Algorithm Robotics Computer Vision 40

Heartbeat

MARCH 14, 2023

Some of the methods used for scene interpretation include Convolutional Neural Networks (CNNs) , a deep learning-based methodology, and more conventional computer vision-based techniques like SIFT and SURF. It lets robots see and understand their surroundings, so they can do tasks and make choices on their own.

Computer Vision 97

Computer Vision Robotics Deep Learning Convolutional Neural Networks 97

Mlearning.ai

FEBRUARY 10, 2023

Addressing bias and Variance Here is the solution to address bias and variance problems: If you have a high avoidable bias; then it is recommended to use a bigger model i.e. a neural network with more hidden layers and hidden units. A more giant network and big data will improve the performance significantly. URL: htts://info.

Machine Learning 52

Machine Learning Neural Network Deep Learning Computer Vision 52

Mlearning.ai

JANUARY 27, 2023

Save this blog for comprehensive resources for computer vision Source: appen Working in computer vision and deep learning is fantastic because, after every few months, someone comes up with something crazy that completely changes your perspective on what is feasible. Template Matching —  Video Tutorial , Written Tutorial 12.

Computer Vision 98

Computer Vision Deep Learning Python Neural Network 98

AssemblyAI

MAY 23, 2023

Neural Networks and Transformers What determines a language model's effectiveness? The performance of LMs in various tasks is significantly influenced by the size of their architectures, which are based on artificial neural networks. A simple artificial neural network with three layers.

Large Language Models 130

Large Language Models Neural Network LLM Chatbots 130

Heartbeat

DECEMBER 8, 2023

He focused on generative AI trained on large language models, The strength of the deep learning era of artificial intelligence has lead to something of a renaissance in corporate R&D in information technology, according to Yann LeCun, chief AI. Hinton is viewed as a leading figure in the deep learning community.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Deep Learning LLM 52

Mlearning.ai

MAY 16, 2023

Deployment of deep neural network on mobile phone. (a) Introduction As more and more deep neural networks, like CNNs, Transformers, and Large Language Models (LLMs), generative models, etc., to boost the usages of the deep neural networks in our lives. Hope these series of posts help.

Neural Network 98

Neural Network Convolutional Neural Networks Deep Learning Inference Engine 98

Explosion

FEBRUARY 12, 2017

In this post, I’ll explain how to solve text-pair tasks with deep learning, using both new and established tips and technologies. The SNLI dataset is over 100x larger than previous similar resources, allowing current deep-learning models to be applied to the problem. Most NLP neural networks start with an embedding layer.

Neural Network 40

Neural Network Deep Learning Natural Language Processing NLP 40

Viso.ai

JUNE 12, 2024

Our software helps several leading organizations start with computer vision and implement deep learning models efficiently with minimal overhead for various downstream tasks. GPT models are based on transformer-based deep learning neural network architecture. About us : Viso.ai Get a demo here.

Large Language Models 52

Large Language Models ChatGPT Computer Vision Neural Network 52

Viso.ai

OCTOBER 7, 2024

Roles of Humans in the Machine Learning Cycle The recent developments in deep learning models have led to AI’s irreplaceable role in many fields. Consequently, human-in-the-loop machine learning is gaining increasing importance. 2017)): This paper addresses the interesting task of video object segmentation.

Computer Vision 52

Computer Vision Machine Learning Deep Learning Convolutional Neural Networks 52

Marktechpost

JULY 18, 2023

One of the most significant advances in deep learning and image processing is object detection, locating and labeling objects inside a given image. Interest in object detection has been strong for a long time, well before the advent of deep learning techniques and cutting-edge image processing tools.

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Artificial Intelligence Artificial Intelligence Algorithm Convolutional Neural Networks 52