AssemblyAI

MARCH 21, 2023

Top 50 keywords in submitted research papers at ICLR 2022 ( source ) A recent bibliometric study systematically analysed this research trend, revealing an exponential growth of published research involving GNNs, with a striking +447% average annual increase in the period 2017-2019.

Neural Network 317

Neural Network Deep Learning AI AI 317

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

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

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.

NLP 98

NLP Neural Network Natural Language Processing Convolutional Neural Networks 98

Unite.AI

MAY 29, 2024

With nine times the speed of the Nvidia A100, these GPUs excel in handling deep learning workloads. This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction.

Data Extraction 273

Data Extraction Neural Network Large Language Models NLP 273

Towards AI

JULY 20, 2023

Natural Language Processing Getting desirable data out of published reports and clinical trials and into systematic literature reviews (SLRs) — a process known as data extraction — is just one of a series of incredibly time-consuming, repetitive, and potentially error-prone steps involved in creating SLRs and meta-analyses.

Data Extraction 80

Data Extraction NLP Natural Language Processing Automation 80

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 Quora dataset is an example of an important type of Natural Language Processing problem: text-pair classification. This data set is large, real, and relevant — a rare combination.

Neural Network 40

Neural Network Deep Learning Natural Language Processing NLP 40

Pragnakalp

JANUARY 1, 2024

Transformer models are a type of neural network architecture designed to process sequential material, such as sentences or time-series data. Since then, in the realms of AI and machine learning, transformer models have emerged as a groundbreaking approach to various language-related tasks.

Neural Network 52

Neural Network Natural Language Processing Convolutional Neural Networks NLP 52

Flipboard

MARCH 27, 2023

torch.compile Over the last few years, PyTorch has evolved as a popular and widely used framework for training deep neural networks (DNNs). Since the launch of PyTorch in 2017, it has strived for high performance and eager execution. In this series, you will learn about Accelerating Deep Learning Models with PyTorch 2.0.

Convolutional Neural Networks 158

Convolutional Neural Networks Neural Network BERT Deep Learning 158

Mlearning.ai

APRIL 21, 2023

Natural Language Processing Transformers, the neural network architecture, that has taken the world of natural language processing (NLP) by storm, is a class of models that can be used for both language and image processing. Not this Transformers!! ? as an alternative to RNN-based models.

Neural Network 52

Neural Network Natural Language Processing ChatGPT NLP 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. AlphaZero was able to surpass its capabilities relatively quickly from a blank slate using reinforcement learning from games of self-play.

Neural Network 52

Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

Heartbeat

JANUARY 23, 2023

Image from Hugging Face Hub Introduction Most natural language processing models are built to address a particular problem, such as responding to inquiries regarding a specific area. This restricts the applicability of models for understanding human language. print("1-",qqp["train"].homepage)

Natural Language Processing 52

Natural Language Processing NLP Deep Learning Machine Learning 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

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. The Most Important Large Language Models (LLMs) in 2023 1. Its design allowed the model to consider the context from both the left and the right sides of each word.

NLP 98

NLP BERT Large Language Models Natural Language Processing 98

Viso.ai

FEBRUARY 25, 2023

Transformer models have become the de-facto status quo in Natural Language Processing (NLP). For example, the popular ChatGPT AI chatbot is a transformer-based language model. They are based on the transformer architecture, which was originally proposed for natural language processing (NLP) in 2017.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

AssemblyAI

MAY 3, 2023

The core process is a general technique known as self-supervised learning , a learning paradigm that leverages the inherent structure of the data itself to generate labels for training. 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

Towards AI

JULY 21, 2023

The Ninth Wave (1850) Ivan Aivazovsky NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher | 09.13.20 declassified Blast from the past: Check out this old (2017) blog post from Google introducing transformer models. Aere Perrenius Welcome back. Hope you enjoyed your week!

NLP 86

NLP Natural Language Processing Machine Learning ML 86

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

Towards AI

JULY 21, 2023

Photo by Will Truettner on Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher | 07.26.20 The last known comms from 3301 came in April 2017 via Pastebin post. Last Updated on July 21, 2023 by Editorial Team Author(s): Ricky Costa Originally published on Towards AI.

NLP 81

NLP Inference Engine Natural Language Processing Chatbots 81

Mlearning.ai

APRIL 10, 2023

Supervised machine learning (such as SVM or GradientBoost) and deep learning models (such as CNN or RNN) can promise far superior performances when comparing them to clustering models however this can come at a greater cost with marginal rewards to the environment, end-user, and product owner of such technology. Electronics.

Algorithm 52

Algorithm Machine Learning Data Analysis Deep Learning 52

Lexalytics

APRIL 5, 2021

They were not wrong: the results they found about the limitations of perceptrons still apply even to the more sophisticated deep-learning networks of today. This subjective impression is objectively backed up by the heat map below, constructed from a dump of the Microsoft Academic Graph (MAG) circa 2017 [ 21 ].

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

John Snow Labs

JUNE 5, 2023

Sentence detection is an essential component in many natural language processing (NLP) tasks, as it enables the analysis of text at a more granular level by breaking it down into individual sentences. Sentence Detection in Spark NLP is the process of automatically identifying the boundaries of sentences in a given text.

NLP 52

NLP Natural Language Processing Deep Learning Algorithm 52

Mlearning.ai

MARCH 9, 2023

Recent studies have demonstrated that deep learning-based image segmentation algorithms are vulnerable to adversarial attacks, where carefully crafted perturbations to the input image can cause significant misclassifications (Xie et al., Towards deep learning models resistant to adversarial attacks. 2018; Sitawarin et al.,

Computer Vision 52

Computer Vision Deep Learning Machine Learning Algorithm 52

John Snow Labs

MAY 26, 2023

Sentence embeddings are a powerful tool in natural language processing that helps analyze and understand language. It is built on top of Apache Spark and Spark ML and provides simple, performant & accurate NLP annotations for machine learning pipelines that can scale easily in a distributed environment.

NLP 52

NLP BERT Natural Language Processing Deep Learning 52

Sebastian Ruder

NOVEMBER 14, 2022

Developing models that work for more languages is important in order to offset the existing language divide and to ensure that speakers of non-English languages are not left behind, among many other reasons. This post is partially based on a keynote I gave at the Deep Learning Indaba 2022. Shazeer, N., Nothman, J.,

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics BERT 52

Heartbeat

AUGUST 2, 2023

Introduction to LLMs LLM in the sphere of AI Large language models (often abbreviated as LLMs) refer to a type of artificial intelligence (AI) model typically based on deep learning architectures known as transformers. However, to derive the context of the language, only the encoder component is typically used.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering OpenAI 52

AWS Machine Learning Blog

AUGUST 16, 2023

The images document the land cover, or physical surface features, of ten European countries between June 2017 and May 2018. He is interested in solving business problems with the latest AI and deep learning techniques including large language models, foundational imagery models, and generative AI.

Metadata 78

Metadata Data Scientist Generative AI Natural Language Processing 78

Mlearning.ai

JULY 2, 2023

Let’s explore the Transformer model that does that precise magic, the encoder-decoder structure that powers its translation prowess, and witness the magic unfold as the model generates rich representations, transforming language from one form to another.

Neural Network 52

Neural Network NLP Natural Language Processing Large Language Models 52

Applied Data Science

JANUARY 4, 2022

At the very least, we hope that by reading this list you can cross-out “Learning about the state of AI in 2021” from your resolution list ?. ? Transformers taking the AI world by storm The family of artificial neural networks (ANNs) saw a new member being born in 2017, the Transformer. What makes the Transformer architecture special?

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 52

DataRobot Blog

MARCH 9, 2022

This is one of the reasons why detecting sentiment from natural language (NLP or natural language processing ) is a surprisingly complex task. With that said, recent advances in deep learning methods have allowed models to improve to a point that is quickly approaching human precision on this difficult task.

Machine Learning 52

Machine Learning Neural Network Convolutional Neural Networks Deep Learning 52

Viso.ai

JANUARY 16, 2024

The ANN utilizes a pair of music files, each with a natural language description, such as ‘happy’ or ‘sad.’ ’ It uses natural language processing (NLP) for the descriptions, allowing the ANN to develop a semantic understanding.

Neural Network 52

Neural Network Computer Vision Categorization Algorithm 52

NLP People

JANUARY 2, 2019

Hundreds of researchers, students, recruiters, and business professionals came to Brussels this November to learn about recent advances, and share their own findings, in computational linguistics and Natural Language Processing (NLP). 3-Is Automatic Post-Editing (APE) a Thing? 7-Have we Finally Solved Machine Translation?

BERT 52

BERT Natural Language Processing Computational Linguistics NLP 52

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Thirdly, the presence of GPUs enabled the labeled data to be processed. Together, these elements lead to the start of a period of dramatic progress in ML, with NN being redubbed deep learning. FP64 is used in HPC fields, such as the natural sciences and financial modeling, resulting in minimal rounding errors.

ML 94

ML Deep Learning Algorithm Large Language Models 94

Topbots

JULY 6, 2023

In the rapidly evolving field of artificial intelligence, natural language processing has become a focal point for researchers and developers alike. LaMDA is built on Transformer , a neural network architecture that Google Research invented and open-sourced in 2017. How is the problem approached?

LLM 52

LLM Large Language Models Natural Language Processing OpenAI 52

John Snow Labs

JUNE 6, 2023

Many different transformer models have already been implemented in Spark NLP, and specifically for text classification, Spark NLP provides various annotators that are designed to work with pretrained language models. BERT-based Transformers are a family of deep learning models that use the transformer architecture.

BERT 52

BERT Python NLP Neural Network 52

ML Review

FEBRUARY 26, 2018

During 2017’s Double 11 shopping festival, AliMe successfully responded to 9.04 Tasks such as “I’d like to book a one-way flight from New York to Paris for tomorrow” can be solved by the intention commitment + slot filing matching or deep reinforcement learning (DRL) model. ACM, 2013: 2333–2338. [2]

Robotics 52

Robotics Deep Learning Chatbots Machine Learning 52

AWS Machine Learning Blog

JUNE 8, 2023

LLMs are based on the Transformer architecture , a deep learning neural network introduced in June 2017 that can be trained on a massive corpus of unlabeled text. This enables you to begin machine learning (ML) quickly. It includes the FLAN-T5-XL model , an LLM deployed into a deep learning container.

Generative AI 80

Generative AI LLM Machine Learning Large Language Models 80