Unite.AI

AUGUST 2, 2023

To overcome the challenge presented by single modality models & algorithms, Meta AI released the data2vec, an algorithm that uses the same learning methodology for either computer vision , NLP or speech. For example, there are vocabulary of speech units in speech processing that can define a self-supervised learning task in NLP.

Computer Vision 246

Computer Vision Convolutional Neural Networks Natural Language Processing Algorithm 246

Unite.AI

OCTOBER 22, 2024

Put simply, if we double the input size, the computational needs can increase fourfold. AI models like neural networks , used in applications like Natural Language Processing (NLP) and computer vision , are notorious for their high computational demands.

Neural Network 147

Neural Network Convolutional Neural Networks Deep Learning Natural Language Processing 147

Marktechpost

NOVEMBER 10, 2023

NLP, or Natural Language Processing, is a field of AI focusing on human-computer interaction using language. NLP aims to make computers understand, interpret, and generate human language. This process enhances data diversity. Prepare a novel dataset (Dn) with only a few labeled samples.

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BERT ChatGPT Large Language Models NLP 130

Viso.ai

MARCH 20, 2024

Models like GPT 4, BERT, DALL-E 3, CLIP, Sora, etc., Use Cases for Foundation Models Applications in Pre-trained Language Models like GPT, BERT, Claude, etc. Applications in Computer Vision Models like ResNET, VGG, Image Captioning, etc. Foundation models are recent developments in artificial intelligence (AI).

AI Development 52

AI Development AI Developer Computer Vision BERT 52

Marktechpost

JUNE 7, 2023

The transformer models like BERT and T5 have recently got popular due to their excellent properties and have utilized the idea of self-supervision in Natural Language Processing tasks. Self-supervised learning is being prominently used in Artificial Intelligence to develop intelligent systems.

Natural Language Processing 98

Natural Language Processing BERT Computer Vision Artificial Intelligence 98

Marktechpost

SEPTEMBER 17, 2023

Large language models (LLMs) built on transformers, including ChatGPT and GPT-4, have demonstrated amazing natural language processing abilities. The creation of transformer-based NLP models has sparked advancements in designing and using transformer-based models in computer vision and other modalities.

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Large Language Models Natural Language Processing BERT Computer Vision 134

Viso.ai

APRIL 26, 2024

Promptable Object Detection (POD) allows users to interact with object detection systems using natural language prompts. Thus, these systems are grounded in traditional object detection and natural language processing frameworks. Learn how Viso Suite can optimize your applications by booking a demo with our team.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Towards AI

DECEMBER 28, 2023

The introduction of attention mechanisms has notably altered our approach to working with deep learning algorithms, leading to a revolution in the realms of computer vision and natural language processing (NLP). In 2023, we witnessed the substantial transformation of AI, marking it as the ‘year of AI.’

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Large Language Models Natural Language Processing Prompt Engineer Prompt Engineering 109

Pickl AI

OCTOBER 21, 2024

This innovative approach is transforming applications in computer vision, Natural Language Processing, healthcare, and more. descriptions like “has wings” or “is furry”) or embeddings derived from text representations (like Word2Vec or BERT), which help bridge known and unknown categories.

Natural Language Processing 52

Natural Language Processing Data Scarcity Computer Vision Machine Learning 52

Unite.AI

NOVEMBER 6, 2023

For instance, NN used for computer vision tasks (object detection and image segmentation) are called convolutional neural networks (CNNs) , such as AlexNet , ResNet , and YOLO. Prominent transformer models include BERT , GPT-4 , and T5.

Machine Learning 204

Machine Learning Neural Network Deep Learning Convolutional Neural Networks 204

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?

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Convolutional Neural Networks Neural Network BERT Deep Learning 159

Topbots

APRIL 11, 2023

In the rapidly evolving field of artificial intelligence, natural language processing has become a focal point for researchers and developers alike. We’ll start with a seminal BERT model from 2018 and finish with this year’s latest breakthroughs like LLaMA by Meta AI and GPT-4 by OpenAI. billion word corpus).

NLP 98

NLP BERT Large Language Models Natural Language Processing 98

IBM Journey to AI blog

AUGUST 1, 2023

A foundation model is built on a neural network model architecture to process information much like the human brain does. A specific kind of foundation model known as a large language model (LLM) is trained on vast amounts of text data for NLP tasks. An open-source model, Google created BERT in 2018.

Generative AI 189

Generative AI BERT Data Scientist Machine Learning 189

Unite.AI

APRIL 26, 2024

The advancements in large language models have significantly accelerated the development of natural language processing , or NLP. These extend far beyond the traditional text-based processing of LLMs to include multimodal interactions.

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Large Language Models Natural Language Processing Convolutional Neural Networks Neural Network 162

Marktechpost

JULY 24, 2023

In many areas of natural language processing, including language interpretation and natural language synthesis, large-scale training of machine learning models utilizing transformer topologies has produced ground-breaking advances.

AI Research 52

AI Research AI Researcher BERT Natural Language Processing 52

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. LLMs like GPT, BERT, and OPT have harnessed transformers technology.

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Data Extraction Neural Network Large Language Models NLP 273

AWS Machine Learning Blog

JUNE 18, 2024

Traditional neural network models like RNNs and LSTMs and more modern transformer-based models like BERT for NER require costly fine-tuning on labeled data for every custom entity type. Her expertise is in building machine learning solutions involving computer vision and natural language processing for various industry verticals.

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Large Language Models Natural Language Processing LLM Computer Vision 120

Marktechpost

JUNE 4, 2024

Table 1 compares the average time per training or inference step for models like SAM, Gemma, BERT, and Mistral across different versions and frameworks of Keras. KerasCV and KerasNLP publish all pretrained models on Kaggle Models, which are accessible in Kaggle competition notebooks even in Internet-off mode.

Machine Learning 89

Machine Learning NLP Natural Language Processing BERT 89

AWS Machine Learning Blog

NOVEMBER 22, 2023

With eight Qualcomm AI 100 Standard accelerators and 128 GiB of total accelerator memory, customers can also use DL2q instances to run popular generative AI applications, such as content generation, text summarization, and virtual assistants, as well as classic AI applications for natural language processing and computer vision.

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BERT Deep Learning Python Auto-classification 121

Viso.ai

JULY 18, 2024

LLMs are pre-trained on extensive data on the web which shows results after comprehending complexity, pattern, and relation in the language. LLMs apply powerful Natural Language Processing (NLP), machine translation, and Visual Question Answering (VQA). GPT-4, BERT) based on your specific task requirements.

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Large Language Models Neural Network Natural Language Processing BERT 52

Heartbeat

MARCH 22, 2023

This week, we’ve got some fantastic pieces on NLP, including a discussion of RoBERTa, and some deep dives into computer vision. A Vision for the Future: How Computer Vision is Transforming Robotics — by Randy Barak a Computer vision is crucial to robotics because it allows robots to see and interpret their environment.

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BERT Computer Vision Robotics NLP 40

Marktechpost

JULY 3, 2023

From deep learning, Natural Language Processing (NLP), and Natural Language Understanding (NLU) to Computer Vision, AI is propelling everyone into a future with endless innovations. It is a potent model for comprehending and processing natural language with 340 million parameters.

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Large Language Models Natural Language Processing LLM BERT 98

Viso.ai

MARCH 26, 2024

This enhances the interpretability of AI systems for applications in computer vision and natural language processing (NLP). Viso Suite: The only truly end-to-end computer vision solution, Viso Suite eliminates the need for point solutions. Vaswani et al. Learn more by booking a demo.

Deep Learning 52

Deep Learning Computer Vision Neural Network Natural Language Processing 52

Unite.AI

MAY 24, 2024

In modern machine learning and artificial intelligence frameworks, transformers are one of the most widely used components across various domains including GPT series, and BERT in Natural Language Processing, and Vision Transformers in computer vision tasks.

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Convolutional Neural Networks Neural Network BERT Natural Language Processing 130

Flipboard

JUNE 20, 2023

Training experiment: Training BERT Large from scratch Training, as opposed to inference, is a finite process that is repeated much less frequently. Training a well-performing BERT Large model from scratch typically requires 450 million sequences to be processed. The first uses traditional accelerated EC2 instances.

Machine Learning 123

Machine Learning BERT Deep Learning ML Engineer 123

Marktechpost

JUNE 11, 2024

Recent advancements in LLMs like BERT, T5, and GPT have revolutionized natural language processing (NLP) using transformers and pretraining-then-finetuning strategies. After testing the LLaVA-1.5 These models excel in various tasks, from text generation to question answering.

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Natural Language Processing BERT LLM NLP 111

Snorkel AI

MARCH 1, 2023

This process results in generalized models capable of a wide variety of tasks, such as image classification, natural language processing, and question-answering, with remarkable accuracy. BERT proved useful in several ways, including quantifying sentiment and predicting the words likely to follow in unfinished sentences.

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BERT Natural Language Processing Large Language Models Neural Network 83

Marktechpost

JULY 22, 2023

State-of-the-art large language models (LLMs), including BERT, GPT-2, BART, T5, GPT-3, and GPT-4, have been developed as a result of recent advances in machine learning, notably in the area of natural language processing (NLP).

Computer Vision 52

Computer Vision Large Language Models NLP Natural Language Processing 52

Marktechpost

JULY 19, 2023

Examples of text-only LLMs include GPT-3 , BERT , RoBERTa , etc. Why is there a need for Multimodal Language Models The text-only LLMs like GPT-3 and BERT have a wide range of applications, such as writing articles, composing emails, and coding.

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Artificial Intelligence Artificial Intelligence Large Language Models Robotics 98

Viso.ai

FEBRUARY 25, 2023

Vision Transformer (ViT) have recently emerged as a competitive alternative to Convolutional Neural Networks (CNNs) that are currently state-of-the-art in different image recognition computer vision tasks. ViT models outperform the current state-of-the-art (CNN) by almost x4 in terms of computational efficiency and accuracy.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Viso.ai

APRIL 5, 2024

Components of Vision Language Models To achieve this multimodal understanding, VLMs typically consist of 3 main elements: An Image Model : Responsible for extracting meaningful visual information such as features and representations from visual data, i.e., Image encoder. word embeddings) and visual features (e.g., mPLUG-Huge 83.62

Natural Language Processing 52

Natural Language Processing Computer Vision BERT AI 52

Marktechpost

JULY 22, 2023

The well-known large language models such as GPT, DALLE, and BERT perform extraordinary tasks and ease lives. While GPT-3 can complete codes, answer questions like humans, and generate content given just a short natural language prompt, DALLE 2 can create images responding to a simple textual description.

LLM 52

LLM Large Language Models Natural Language Processing Artificial Intelligence 52

Snorkel AI

SEPTEMBER 21, 2023

Natural language processing ( NLP ) and computer vision can capture values specific to the trial subject that help identify or exclude potential participants, creating alignment across different systems and document types. High-quality training sets are essential to this customization.

BERT 64

BERT Data Scientist AI Natural Language Processing 64

Viso.ai

JULY 9, 2024

Transfer Learning is a key technique implemented by researchers and ML scientists to enhance efficiency and reduce costs in Deep learning and Natural Language Processing. About us : Viso Suite is our end-to-end computer vision infrastructure for enterprises. Book a demo to learn more. What is Transfer Learning?

Neural Network 52

Neural Network BERT Deep Learning Computer Vision 52

AWS Machine Learning Blog

APRIL 7, 2023

As an example, smart venue solutions can use near-real-time computer vision for crowd analytics over 5G networks, all while minimizing investment in on-premises hardware networking equipment. In our example, we use the Bidirectional Encoder Representations from Transformers (BERT) model, commonly used for natural language processing.

BERT 90

BERT Metadata Natural Language Processing ML 90

Snorkel AI

SEPTEMBER 21, 2023

Natural language processing ( NLP ) and computer vision can capture values specific to the trial subject that help identify or exclude potential participants, creating alignment across different systems and document types. High-quality training sets are essential to this customization.

BERT 59

BERT Data Scientist AI Natural Language Processing 59

Pragnakalp

JANUARY 1, 2024

The transformer “requires less training time than previous recurrent neural architectures, such as long short-term memory (LSTM), and its later variation has been prevalently adopted for training large language models on large (language) datasets,” notes Wikipedia.

Neural Network 52

Neural Network Natural Language Processing Convolutional Neural Networks NLP 52