Hal Daumé III

AUGUST 14, 2016

Spruit The Social Impact of Natural Language Processing This is a nice paper summarizing four issues that come up in ethics that also come up in NLP. The paper also shows that this gets worse over time, presumably as evaluators get tireder. P16-2096 : Dirk Hovy; Shannon L.

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Towards AI

APRIL 12, 2023

All of these companies were founded between 2013–2016 in various parts of the world. Soon to be followed by large general language models like BERT (Bidirectional Encoder Representations from Transformers).

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Flipboard

APRIL 8, 2023

The law is starting to catch up Laws related to AI passed in 127 countries has jumped, HAI reported, with only one passed in 2016 compared with 37 in 2022. researchers surveyed natural language processing researchers, as evidenced by publications, to get a handle on what AI experts think about AI research, HAI reported.

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Topbots

JUNE 22, 2023

SA is a very widespread Natural Language Processing (NLP). Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 595–605. ALLDATA, The Second Inter-national Conference on Big Data, Small Data, Linked Data and Open Data (2016). Hamilton, W. Leskovec, J.,

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Heartbeat

FEBRUARY 2, 2024

Visual Question Answering (VQA) stands at the intersection of computer vision and natural language processing, posing a unique and complex challenge for artificial intelligence. is a significant benchmark dataset in computer vision and natural language processing. or Visual Question Answering version 2.0,

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Mlearning.ai

APRIL 10, 2023

2016) Data Management : By allowing clustering to occur locally, edge devices in the network can enable near-real-time data analysis in order to make data-driven decisions Energy : Clustering methods have been known to be more energy efficient when it comes to data transmission and processing (Loganathan & Arumugan, 2021).

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John Snow Labs

MAY 23, 2023

Visual question answering (VQA), an area that intersects the fields of Deep Learning, Natural Language Processing (NLP) and Computer Vision (CV) is garnering a lot of interest in research circles. A VQA system takes free-form, text-based questions about an input image and presents answers in a natural language format.

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Explosion

OCTOBER 22, 2016

This is a guest post by Wah Loon Keng , the author of spacy-nlp , a client that exposes spaCy ’s NLP text parsing to Node.js (and other languages) via Socket.IO. Natural Language Processing and other AI technologies promise to let us build applications that offer smarter, more context-aware user experiences. CLI: 2.4.0,

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AWS Machine Learning Blog

MARCH 31, 2023

He has been with the Transportation Cabinet since 2016 working in various IT roles. The contact center is powered by Amazon Connect, and Max, the virtual agent, is powered by Amazon Lex and the AWS QnABot solution. Amazon Connect directs some incoming calls to the virtual agent (Max) by identifying the caller number.

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NLP People

APRIL 2, 2018

It was created in 2002 to study and advance machine translation, natural language processing, low-resourced languages and how machines and humans interact. The Meetup for Natural Language Processing enthusiasts and career professionals in France can be found by clicking here.

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Unite.AI

JANUARY 9, 2024

Apple prioritizes computer vision , natural language processing , voice recognition, and healthcare to enhance its products. Likewise, Microsoft strengthens its cloud and enterprise software through acquisitions in natural language processing , computer vision , and cybersecurity.

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ODSC - Open Data Science

OCTOBER 15, 2023

Ikigai Labs Ikigai Labs is a company that provides a platform for building and managing natural language processing models. Outerbounds Founded in 2016, Outerbounds is a company that provides a platform for building and managing anomaly detection models.

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How to Learn Machine Learning

DECEMBER 4, 2022

In 2016, Google released an open-source software called AutoML. Another way AI is being used to write code is through the use of natural language processing (NLP). NLP is a type of AI that can understand human language and convert it into code. One recent example of the usage of Ai is in the field of code writing.

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Explosion

DECEMBER 30, 2021

Mar 29: Ines joined the at the German Python Podcast to talk about Natural Language Processing with spaCy. ? Since founding Explosion in 2016, we’ve run the company as a profitable business. Mar 17: March saw a new episode of Vincent Warmerdam’s “Intro to NLP with spaCy” series. September ?

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Unite.AI

FEBRUARY 13, 2024

According to some of the latest public data, over $509 billion of counterfeit products were traded internationally in 2016. Additionally, natural language processing models can help them communicate regardless of their language or cultural barriers. Counterfeit Products Logistics fraud is a massive global issue.

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Topbots

OCTOBER 10, 2023

Finally, let’s talk about the additional design and development challenges of building a voice UI: There is an additional step of speech recognition that happens before user inputs can be processed with LLMs and Natural Language Processing (NLP). Retrieved on January 13, 2022. [3] 3] Patrick Lewis et al. 4] Paul Grice.

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ML Review

FEBRUARY 26, 2018

Following its successful adoption in computer vision and voice recognition, DL will continue to be applied in the domain of natural language processing (NLP). In Proceedings of The First International Workshop on Machine Learning in Spoken Language Processing. [5] 2016 [6] Li J, Monroe W, Ritter A, et al.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Her research interests lie in Natural Language Processing, AI4Code and generative AI. He joined Amazon in 2016 as an Applied Scientist within SCOT organization and then later AWS AI Labs in 2018 working on Amazon Kendra. His research interests lie in the area of AI4Code and Natural Language Processing.

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Probably Approximately a Scientific Blog

MAY 25, 2016

For so many years people have been saying these two approaches are complementary, and turns out it was actually not too difficult to combine them :) Paper details Improving Hypernymy Detection with an Integrated Path-based and Distributional Method. Vered Shwartz, Yoav Goldberg and Ido Dagan.

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TheSequence

DECEMBER 13, 2023

He has previously built machine learning-powered applications for start-ups and enterprises in the domains of natural language processing, topological data analysis, and time series. My path to working in AI is somewhat unconventional and began when I was wrapping up a postdoc in theoretical particle physics around 2016.

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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.

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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.

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Explosion

AUGUST 1, 2019

Transformers and transfer-learning Natural Language Processing (NLP) systems face a problem known as the “knowledge acquisition bottleneck”. 2019) have shown that a transformer models trained on only 1% of the IMDB sentiment analysis data (just a few dozen examples) can exceed the pre-2016 state-of-the-art.

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Dlabs.ai

AUGUST 10, 2020

On principle, all chatbots work by utilising some form of natural language processing (NLP). The challenges of intent detection One of the biggest challenges in building successful intent detection is, of course, natural language processing. at the SentiCognitiveServies project ).

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Viso.ai

MAY 1, 2024

Natural Language Processing (NLP) and knowledge representation and reasoning have empowered the machines to perform meaningful web searches. Moreover, they can answer any question and communicate naturally. Stanford University and panel researchers P. Stone and R. Brooks et al. Brooks et al.

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Mlearning.ai

FEBRUARY 15, 2023

Introduction In natural language processing, text categorization tasks are common (NLP). Foundations of Statistical Natural Language Processing [M]. Depending on the data they are provided, different classifiers may perform better or worse (eg. Uysal and Gunal, 2014). Manning C. and Schutze H.,

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Lexalytics

APRIL 5, 2021

Going forward, it was clear that we would need to be supporting even more models across more languages, yet our code and training data were scattered across many cloud computing instances. This is the sort of representation that is useful for natural language processing.

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Sebastian Ruder

DECEMBER 6, 2021

A domain can be seen as a manifold in a high-dimensional variety space consisting of many dimensions such as socio-demographics, language, genre, sentence type, etc ( Plank et al., 2016 ), Natural Questions (NQ; Kwiatkowski et al., 2016 ), among many others. 2016 ), and BookTest ( Bajgar et al., 2018 ; Gupta et al.,

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Viso.ai

DECEMBER 4, 2023

PyTorch Overview PyTorch was first introduced in 2016. PyTorch is suitable for natural language processing ( NLP ) tasks to power intelligent language applications using deep learning. TensorFlow Distribution Strategies is a TensorFlow API to distribute training across multiple GPUs, multiple machines, or TPUs.

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Unite.AI

OCTOBER 27, 2023

According to Stanford University's AI Index Report 2023, while only one law was adopted in 2016, there were 12 of them in 2018, 18 – in 2021, and 37 – in 2022. This prompted the United Nations to define a position on the ethics of using artificial intelligence at the global level.

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ML Review

JUNE 4, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part Two) This is the second instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). 2016)[ 91 ] You et al. Source : You et al.

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Explosion

NOVEMBER 9, 2016

Over the last six months, a powerful new neural network playbook has come together for Natural Language Processing. A four-step strategy for deep learning with text Embedded word representations, also known as “word vectors”, are now one of the most widely used natural language processing technologies.

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Mlearning.ai

MARCH 9, 2023

Generative adversarial networks-based adversarial training for natural language processing. 2018; Papernot et al., Towards deep learning models resistant to adversarial attacks. arXiv preprint arXiv:1706.06083. Papernot, N., McDaniel, P., Fredrikson, M., B., & Swami, A. Sitawarin, C., Chen, Y., & Du, B. 501–509).

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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). Pre-trained language models were found to be prone to generating toxic language ( Gehman et al.,

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Defined.ai blog

APRIL 10, 2023

Named Entity Recognition (NER) is a natural language processing (NLP) subtask that involves automatically identifying and categorizing named entities mentioned in a text, such as people, organizations, locations, dates, and other proper nouns. What is Named Entity Recognition (NER)?

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Defined.ai blog

APRIL 10, 2023

Named Entity Recognition (NER) is a natural language processing (NLP) subtask that involves automatically identifying and categorizing named entities mentioned in a text, such as people, organizations, locations, dates, and other proper nouns. What is Named Entity Recognition (NER)?

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Sebastian Ruder

OCTOBER 26, 2019

Depending on the task, there are other ways of transferring information across languages such as by domain adaptation (as seen above), annotation projection ( Padó & Lapata, 2009 ; Ni et al., 2016 ; Eger et al., 2016 ; Lample et al., Why not Machine Translation? 2018 ; Artetxe et al., 2015 , Artetxe et al.,

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