Towards AI

JULY 21, 2023

Photo by Will Truettner on Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher | 07.26.20 Transformer is the most critical alogrithm… github.com NLP & Audio Pretrained Models A nice collection of pretrained model libraries found on GitHub. Paper: [link] Where is it?

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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. What is the goal?

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Heartbeat

AUGUST 23, 2023

But what if there was a technique to quickly and accurately solve this language puzzle? Enter Natural Language Processing (NLP) and its transformational power. This is the promise of NLP: to transform the way we approach legal discovery. But exactly what is NLP , and how can it facilitate legal discovery?

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Towards AI

JUNE 12, 2024

Photo by david clarke on Unsplash The most recent breakthroughs in language models have been the use of neural network architectures to represent text. There is very little contention that large language models have evolved very rapidly since 2018. This facilitates various NLP tasks by providing meaningful word embeddings.

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Towards AI

DECEMBER 28, 2023

Later, Python gained momentum and surpassed all programming languages, including Java, in popularity around 2018–19. 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).

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Towards AI

APRIL 5, 2023

Picture created with Dall-E-2 Yoshua Bengio, Geoffrey Hinton, and Yann LeCun, three computer scientists and artificial intelligence (AI) researchers, were jointly awarded the 2018 Turing Prize for their contributions to deep learning, a subfield of AI.

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Marktechpost

JANUARY 10, 2024

BERT is a language model which was released by Google in 2018. It is based on the transformer architecture and is known for its significant improvement over previous state-of-the-art models.

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Heartbeat

MARCH 15, 2023

But now, a computer can be taught to comprehend and process human language through Natural Language Processing (NLP), which was implemented, to make computers capable of understanding spoken and written language. The masked language modeling objective is referred to as this.

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Mlearning.ai

MAY 5, 2023

However, these early systems were limited in their ability to handle complex language structures and nuances, and they quickly fell out of favor. In the 1980s and 1990s, the field of natural language processing (NLP) began to emerge as a distinct area of research within AI.

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Marktechpost

JULY 5, 2023

OpenAI’s GPT models have allowed major natural language processing (NLP) advancements. One machine learning model for NLP applications is the Generative Pre-trained Transformer (GPT). That makes them malleable for NLP applications such as question answering, translation, and text summarization.

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AWS Machine Learning Blog

FEBRUARY 6, 2024

Transformers, BERT, and GPT The transformer architecture is a neural network architecture that is used for natural language processing (NLP) tasks. This allows the model to learn long-range dependencies between words, which is essential for many NLP tasks, such as machine translation and text summarization.

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Bugra Akyildiz

AUGUST 6, 2023

However, it was back in 2018-2019, ChatGPT has not taken over the industry both in terms of model accuracy, but also overall deployment options. Embeddings can be used for a variety of tasks in different downstream applications, such as natural language processing (NLP), recommendation systems, and search engines.

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John Snow Labs

JUNE 27, 2023

Are you curious about the groundbreaking advancements in Natural Language Processing (NLP)? Prepare to be amazed as we delve into the world of Large Language Models (LLMs) – the driving force behind NLP’s remarkable progress. Ever wondered how machines can understand and generate human-like text?

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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. Dear Heartbeat Readers, The Comet team is still buzzing from our recent Convergence Conference - We were so excited to have thousands of you there learning from the most innovative minds in the industry!

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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). BERT is a new milestone in NLP. 7-Have we Finally Solved Machine Translation?

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Viso.ai

JUNE 12, 2024

Large Language Models – Source In 2018, OpenAI researchers and engineers published an original work on AI-based generative large language models. They pre-trained the models with a large and diverse corpus of text, in a process they call Generative Pre-Training (GPT). without supervised pre-training.

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Unite.AI

AUGUST 3, 2023

Our journey took a big leap when we joined the Techstars Mobility Accelerator in Detroit in 2018. AI-Enhanced Chat Feature : Powered by leading-edge natural language processing algorithms, Maven's AI Chat enables users to access necessary information quickly and efficiently using natural language queries.

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Topbots

JUNE 22, 2023

SA is a very widespread Natural Language Processing (NLP). Hence, whether general domain ML models can be as capable as domain-specific models is still an open research question in NLP. Also, since at least 2018, the American agency DARPA has delved into the significance of bringing explainability to AI decisions.

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Chatbots Life

MAY 16, 2023

Services : AI Solution Development, ML Engineering, Data Science Consulting, NLP, AI Model Development, AI Strategic Consulting, Computer Vision. Data Monsters can help companies deploy, train and test machine learning pipelines for natural language processing and computer vision. Elite Service Delivery partner of NVIDIA.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

For unstructured data, the agent uses AWS Lambda functions with AI services such as Amazon Textract for document analysis, Amazon Transcribe for speech recognition, Amazon Comprehend for NLP, and Amazon Kendra for intelligent search. Can you build an optimized portfolio using these three stocks? ” WWW: $85.91 DDD: $9.82 WWW: $85.91

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Towards AI

SEPTEMBER 26, 2023

Back when BERT and GPT2 were first revolutionizing natural language processing (NLP), there was really only one playbook for fine-tuning. You had to be very careful with fine-tuning because of catastrophic forgetting. There are a few downsides to this approach.

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Heartbeat

JANUARY 29, 2024

Imagine an AI system that becomes proficient in many tasks through extensive training on each specific problem and a higher-order learning process that distills valuable insights from previous learning endeavors. Natural Language Processing: With Meta-Learning, language models can be generalized across various languages and dialects.

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Sebastian Ruder

AUGUST 15, 2021

My favourite resources on this topic from the conference are: Chris Pott's keynote on Reliable characterizations of NLP systems as a social responsibility. Samuel Bowman's and George Dahl's position paper asking " What Will it Take to Fix Benchmarking in Natural Language Understanding?

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Marktechpost

JUNE 27, 2023

A wide variety of services, including predictive analytics, deep learning, application programming interfaces, data visualization, and natural language processing, are available from various suppliers. Data visualization, APIs galore, facial recognition, NLP, PA, DL, and more are all on the menu here.

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NLP For Hackers

MARCH 28, 2018

Updates 29-Apr-2018 – Fixed import in extension code (Thanks Ruben) spaCy is a relatively new framework in the Python Natural Language Processing environment but it quickly gains ground and will most likely become the de facto library. import spacy nlp = spacy.load('en') doc = nlp('Hello World!')

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Sebastian Ruder

JULY 31, 2020

Natural language processing (NLP) research predominantly focuses on developing methods that work well for English despite the many positive benefits of working on other languages. Most of the world's languages are spoken in Asia, Africa, the Pacific region and the Americas. Each feature has 5.93

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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. His specialty is Natural Language Processing (NLP) and is passionate about deep learning. The following are a few example RGB images and their labels.

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Towards AI

JULY 23, 2023

In the first part of the series, we talked about how Transformer ended the sequence-to-sequence modeling era of Natural Language Processing and understanding. In this article, we aim to focus on the development of one of the most powerful generative NLP tools, OpenAI’s GPT. Let’s see it step by step. In 2015, Andrew M.

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Sebastian Ruder

JANUARY 19, 2021

The selection of areas and methods is heavily influenced by my own interests; the selected topics are biased towards representation and transfer learning and towards natural language processing (NLP).  2020 saw the development of ever larger language and dialogue models such as Meena ( Adiwardana et al.,

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Sebastian Ruder

AUGUST 18, 2019

This post expands on the NAACL 2019 tutorial on Transfer Learning in NLP. In the span of little more than a year, transfer learning in the form of pretrained language models has become ubiquitous in NLP and has contributed to the state of the art on a wide range of tasks. 2017 ) and pretrained language models ( Peters et al.,

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ML Review

JUNE 13, 2018

This article is part of the Academic Alibaba series and is taken from the paper entitled “Learning Chinese Word Embeddings with Stroke n-gram Information” by Shaosheng Cao, Wei Lu, Jun Zhou, and Xiaolong Li, accepted by the 2018 Conference of the Association for the Advancement of Artificial Intelligence. The full paper can be read here.

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AWS Machine Learning Blog

MAY 22, 2023

Amazon EBS is well suited to both database-style applications that rely on random reads and writes, and to throughput-intensive applications that perform long, continuous reads and writes. """, """ Amazon Comprehend uses natural language processing (NLP) to extract insights about the content of documents.

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Explosion

AUGUST 1, 2019

Huge transformer models like BERT, GPT-2 and XLNet have set a new standard for accuracy on almost every NLP leaderboard. It features consistent and easy-to-use interfaces to several models, which can extract features to power your NLP pipelines. apple2 = nlp("Apple sold fewer iPhones this quarter.") print(apple1[0].similarity(apple2[0]))

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Sebastian Ruder

JANUARY 6, 2020

This post gathers ten ML and NLP research directions that I found exciting and impactful in 2019.  Unsupervised pretraining was prevalent in NLP this year, mainly driven by BERT ( Devlin et al., 2019) find winning ticket initialisations also for LSTMs and Transformers in NLP and RL models. 2019 ) and other variants.

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Mlearning.ai

FEBRUARY 19, 2023

You don’t need to have a PhD to understand the billion parameter language model GPT is a general-purpose natural language processing model that revolutionized the landscape of AI. GPT-3 is a autoregressive language model created by OpenAI, released in 2020 . What is GPT-3?

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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. All watsonx.ai

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Marek Rei

NOVEMBER 12, 2019

Below you will find short summaries of a number of different research papers published in the areas of Machine Learning and Natural Language Processing in the past couple of years (2017-2019). Improving Language Understanding by Generative Pre-Training Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever.

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