Sebastian Ruder

JULY 4, 2019

The Natural Language Processing community has seen unprecedented growth in recent years (see for instance the ACL 2019 Chairs blog ). Conferences such as NAACL 2019 have been fostering initiatives that encourage diversity and inclusion, such as mentoring, childcare, and live captions.

Natural Language Processing 52

Natural Language Processing NLP AI AI 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. Alex Warstadt et al. print("1-",qqp["train"].homepage)

Natural Language Processing 52

Natural Language Processing NLP Deep Learning Machine Learning 52

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! But to what extent?

NLP 86

NLP Natural Language Processing Machine Learning ML 86

Sebastian Ruder

AUGUST 18, 2019

This post expands on the NAACL 2019 tutorial on Transfer Learning in NLP. Introduction For an overview of what transfer learning is, have a look at this blog post. 2017 ) and pretrained language models ( Peters et al., 2019 ) of recent years. Update 16.10.2020: Added Chinese and Spanish translations. 2018 ; Akbik et al.,

NLP 75

NLP BERT Natural Language Processing Computational Linguistics 75

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. But what if there was a way to unravel this language puzzle swiftly and accurately?

NLP 52

NLP Natural Language Processing Algorithm Categorization 52

AWS Machine Learning Blog

FEBRUARY 19, 2024

AWS launched their first inference chips (“Inferentia”) in 2019, and they have saved companies like Amazon over a hundred million dollars in capital expense. Amazon’s annual revenue increased from $245B in 2019 to $434B in 2022. Tell me again what was the revenue in 2019? Amazon’s revenue in 2019 was $245 billion.

Chatbots 93

Chatbots Data Ingestion Machine Learning Generative AI 93

John Snow Labs

SEPTEMBER 11, 2023

This blog article delves into the exciting synergy between the T5 model and Spark NLP, an open-source library built on Apache Spark, which enables seamless integration of cutting-edge NLP capabilities into your projects. Therefore, we’ll structure the Spark DataFrame with a sole column named “text.” result").show(truncate=False)

NLP 52

NLP Natural Language Processing Python Machine Learning 52

Heartbeat

JUNE 6, 2023

In recent years, researchers have also explored using GCNs for natural language processing (NLP) tasks, such as text classification , sentiment analysis , and entity recognition. Once the GCN is trained, it is easier to process new graphs and make predictions about them. Richong, Z., Yongyi, M., & Xudong L.

NLP 59

NLP Convolutional Neural Networks Neural Network Natural Language Processing 59

Heartbeat

OCTOBER 10, 2023

One of the most popular techniques for speech recognition is natural language processing (NLP), which entails training machine learning models on enormous amounts of text data to understand linguistic patterns and structures. It was developed by Facebook AI Research and released in 2019. Why Did RoBERTa Get Developed?

BERT 52

BERT NLP Machine Learning Natural Language Processing 52

Towards AI

JULY 19, 2023

The Ninth Wave (1850) Ivan Aivazovsky NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher | 09.13.20 link] Blast from the past: Check out this old (2017) blog post from Google introducing transformer models. FYI, for a more in-depth discussion/history on sparsity, you can check out HF’s new blog here.

NLP 40

NLP Natural Language Processing Machine Learning ML 40

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.

Machine Learning 52

Machine Learning Neural Network Natural Language Processing Algorithm 52

Unite.AI

AUGUST 8, 2023

LLMs can be used in multiple ways, including: Direct Utilization: Simply using a pre-trained LLM for text generation or processing. For instance, using GPT-4 to write a blog post without any additional fine-tuning. This was an impressive start, offering a glimpse into the future of language models. How Are LLMs Used?

Generative AI 243

Generative AI ChatGPT Neural Network Convolutional Neural Networks 243

The Stanford AI Lab Blog

MAY 31, 2022

Language Model Pretraining Language models (LMs), like BERT 1 and the GPT series 2 , achieve remarkable performance on many natural language processing (NLP) tasks. We will now see how LinkBERT performs on several downstream natural language processing tasks. Let’s use LinkBERT! Brown, et al.

BERT 40

BERT Natural Language Processing NLP Neural Network 40

AWS Machine Learning Blog

FEBRUARY 29, 2024

We also note that our models primarily work well for search, recommendation, and natural language processing tasks that typically feature large, high-dimensional output spaces and a requirement of extremely low inference latency. You can also try Graviton t4g instances free trial.

Neural Network 96

Neural Network Deep Learning Machine Learning Algorithm 96

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). 2019 ) and work that focuses on making them smaller has gained momentum: Recent approaches rely on pruning ( Sajjad et al.,

NLP 52

NLP ML Computer Vision Natural Language Processing 52

AWS Machine Learning Blog

OCTOBER 5, 2023

His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering. an AI start-up, and worked as the CEO and Chief Scientist in 2019–2021. He focuses on developing scalable machine learning algorithms.

Machine Learning 91

Machine Learning Big Data Deep Learning Natural Language Processing 91

Mlearning.ai

FEBRUARY 6, 2023

2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics. [7] Attention is not not Explanation (2019). The 2019 Conference on Empirical Methods in Natural Language Processing. [8] Nature Machine Intelligence. [10] Attention is not Explanation. Weigreffe, Y.

Explainable AI 52

Explainable AI Explainability ChatGPT Chatbots 52

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: Pre-training of Deep Bidirectional Transformers for Language Understanding Devlin et al.

BERT 83

BERT Natural Language Processing Large Language Models Neural Network 83

AWS Machine Learning Blog

AUGUST 7, 2023

As an added inherent challenge, natural language processing (NLP) classifiers are historically known to be very costly to train and require a large set of vocabulary, known as a corpus , to produce accurate predictions. Improving Language Understanding by Generative Pre-Training” Devlin et al.,

Large Language Models 73

Large Language Models LLM BERT ML 73

Viso.ai

DECEMBER 20, 2023

In this blog article, we’ll explore MindSpore in-depth: Understanding the Architecture Reviewing Optimization Techniques Exploring Adaptability Ease of development Upsides and Commercial Risks About us : Viso Suite is the most powerful end-to-end computer vision platform. Potential Risks for Businesses Users In 2019, the U.S.

Deep Learning 52

Deep Learning Neural Network Computer Vision Natural Language Processing 52

deepsense.ai

NOVEMBER 14, 2023

source: The Missing Link in Generative AI | Fiddler AI Blog ]. Within Natural Language Processing (NLP), ‘pseudo-evaluation’ approaches that we call ‘Superficial Utility Comparison Kriterion’ ( SUCK ) methods, like BLEU [32], METEOR [33], ROUGE [34], or BLEURT [35], attempt to salvage the situation. Garrido-Merchán E.C.,

Generative AI 100

Generative AI ML Prompt Engineer Prompt Engineering 100

John Snow Labs

JULY 19, 2023

This blog post explores the emerging players in the commercial large language model (LLM) landscape, namely Anthropic, Cohere, Mosaic ML, Cerebras, Aleph Alpha, AI21 Labs and John Snow Labs. In this blog post, we will dive into the fascinating ecosystem of LLM companies.

LLM 98

LLM OpenAI Large Language Models NLP 98

AWS Machine Learning Blog

MARCH 31, 2023

Also, the introduction of federal REAL ID requirements in 2019 resulted in increased call volumes from drivers with questions. Call volumes increased further in 2020 when the COVID-19 pandemic struck and driver licensing regional offices closed.

Automation 74

Automation Natural Language Processing Conversational AI NLP 74

NLP People

JULY 24, 2019

The 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019) is starting this week in Florence, Italy. Follow us for a review of ACL 2019 and more updates on NLP trends! Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article]. References E. Cambria and B.

NLP 52

NLP Neural Network Deep Learning Natural Language Processing 52

Explosion

NOVEMBER 21, 2019

Try the new interactive demo to explore similarities and compare them between 2015 and 2019 sense2vec (Trask et. First, we trained a new sense2vec model on the 2019 Reddit comments , which makes for an interesting contrast to the previous 2015 vectors. In 2019, it’s mostly used in the context of cutting off communication by “ghosting”.

NLP 52

NLP Convolutional Neural Networks Neural Network Natural Language Processing 52

Heartbeat

JUNE 28, 2023

ALBERT (A Lite BERT) is a language model developed by Google Research in 2019. Overall, The combination of ALBERT and knowledge distillation represents a powerful approach to natural language processing that can improve the efficiency of large-scale language models and make them more accessible to researchers and developers alike.

BERT 52

BERT Machine Learning Deep Learning Neural Network 52

Topbots

APRIL 28, 2023

Generated by the author This article was originally published on the author’s blog and re-published to TOPBOTS with permission from the author. In recent weeks, people have used large language models (LLMs) to generate a variety of creative content, such as books , flash fiction , rap battles , and music chords. parameters).

Large Language Models 52

Large Language Models Natural Language Processing Robotics Explainability 52

Sebastian Ruder

MAY 22, 2020

This advice should be most relevant to people studying machine learning (ML) and natural language processing (NLP) as that is what I did in my PhD. Write a blog. 2019 ), and many others. 6) Write a blog. Blogging has many advantages. A blog can also be a great medium to present and share your work.

Natural Language Processing 52

Natural Language Processing NLP ML Deep Learning 52

AWS Machine Learning Blog

SEPTEMBER 14, 2023

“Data locked away in text, audio, social media, and other unstructured sources can be a competitive advantage for firms that figure out how to use it“ Only 18% of organizations in a 2019 survey by Deloitte reported being able to take advantage of unstructured data. We have made this process simple by automating the whole training pipeline.

Categorization 90

Categorization Machine Learning Data Scientist Natural Language Processing 90

AWS Machine Learning Blog

MARCH 14, 2024

Amazon Kendra uses natural language processing (NLP) to understand user queries and find the most relevant documents. This occurred in 2019 during the first round on hole number 15. To enable quick information retrieval, we use Amazon Kendra as the index for these documents.

Generative AI 94

Generative AI LLM AI AI 94

Chatbots Life

MAY 3, 2023

Simply put, It allows computers to process text or voice into a language they understand. We have listed all these steps in detail in our blog post here , which you can check out and start building your bot (without any code). NLU comes under the bracket of NLP (Natural Language Processing and conversational AI.

Conversational AI 98

Conversational AI Chatbots AI Chatbots AI 98

Flipboard

JULY 10, 2023

Figure 7: The topology of Sparse Autoencoder (source: Shi, Ji, Zhang, and Miao, “Boosting sparsity-induced autoencoder: A novel sparse feature ensemble learning for image classification,” International Journal of Advanced Robotic Systems , 2019 ). time series or natural language processing tasks).

Computer Vision 110

Computer Vision Deep Learning Neural Network Machine Learning 110

Heartbeat

MARCH 15, 2023

Photo by Fatos Bytyqi on Unsplash Introduction Did you know that in the past, computers struggled to understand human languages? 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.

BERT 52

BERT NLP Deep Learning Neural Network 52

AWS Machine Learning Blog

APRIL 19, 2023

After reading a few blog posts and DJL’s official documentation, we were sure DJL would provide the best solution to our problem. It has intuitive helpers and utilities for modalities like computer vision, natural language processing, audio, time series, and tabular data.

ML 72

ML Deep Learning Python Auto-classification 72

AWS Machine Learning Blog

APRIL 29, 2024

Historically, natural language processing (NLP) would be a primary research and development expense. In 2024, however, organizations are using large language models (LLMs), which require relatively little focus on NLP, shifting research and development from modeling to the infrastructure needed to support LLM workflows.

ML 93

ML Python Data Scientist Deep Learning 93

AWS Machine Learning Blog

APRIL 19, 2024

According to the information provided in the summary, GPT-3 from 2020 had 175B (175 billion) parameters, while GPT-2 from 2019 had 1.5B (1.5 The summary describes an image related to the progression of natural language processing and generative AI technologies, but it does not mention anything about particle physics or the concept of quarks.

Metadata 96

Metadata ML Machine Learning Natural Language Processing 96

AWS Machine Learning Blog

NOVEMBER 27, 2023

While this data holds valuable insights, its unstructured nature makes it difficult for AI algorithms to interpret and learn from it. According to a 2019 survey by Deloitte , only 18% of businesses reported being able to take advantage of unstructured data. Clean data is important for good model performance.

Generative AI 70

Generative AI Metadata LLM Python 70