Hacker News

MARCH 22, 2024

2017) is now ubiquitous across application domains, from natural language processing to speech processing and image understanding. The transformer architecture by Vaswani et al.

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Dataconomy

JUNE 23, 2017

To learn more about this topic, please consider attending our fourth annual PyData Berlin conference on June 30-July 2, 2017. The post How Faulty Data Breaks Your Machine Learning Process appeared first on Dataconomy. Miroslav Batchkarov and other experts will be giving talks.

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Data Science Dojo

DECEMBER 8, 2023

For instance, in natural language processing, a model trained on various languages might be tasked with translating a language it has never seen before. By understanding the semantic relationships between languages, the model can make informed translations even in the absence of explicit training data.

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ODSC - Open Data Science

JUNE 9, 2023

Once a set of word vectors has been learned, they can be used in various natural language processing (NLP) tasks such as text classification, language translation, and question answering. GloVe uses a different approach than word2vec and learns word vectors by training on co-occurrence matrices.

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Hacker News

MARCH 25, 2022

First described in a 2017 paper from Google, transformers are among the newest and one of the most powerful classes of models invented to date. That’s a radical shift from a 2017 IEEE study that reported RNNs and CNNs were the most popular models for pattern recognition. No Labels, More Performance. How Transformers Got Their Name.

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Towards AI

FEBRUARY 21, 2025

The Large Language Models have changed the face of Natural Language Processing by enabling machines to generate human-like copies of text, translate languages, summarize texts, and perform a multitude of other tasks. Author(s): Veritas AI Originally published on Towards AI. This member-only story is on us.

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Towards AI

MARCH 3, 2025

Can machines understand human language? These questions are addressed by the field of Natural Language processing, which allows machines to mimic human comprehension and usage of natural language. Last Updated on March 3, 2025 by Editorial Team Author(s): SHARON ZACHARIA Originally published on Towards AI.

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Towards AI

FEBRUARY 6, 2024

Photo by Johannes Plenio on Unsplash Since the 2017 paper “Attention Is All You Need” invented the Transformer architecture, natural language processing (NLP) has seen tremendous growth. And with the release of ChatGPT in November 2022, large language models (LLMs) has captured everyone’s interest.

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Towards AI

FEBRUARY 20, 2024

The state-of-the-art Natural Language Processing (NLP) models used to be Recurrent Neural Networks (RNN) among others. Transformer architecture significantly improved natural language task performance compared to earlier RNNs. Exploring the encoder-decoder magic in NLP behind LLMsImage created by the author.

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Dataconomy

OCTOBER 2, 2024

cum laude in machine learning from the University of Amsterdam in 2017. He played a pivotal role in the creation of influential AI systems such as DALL-E and ChatGPT , which have helped revolutionize text-to-image generation and natural language processing. He earned his Ph.D.

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Flipboard

MAY 10, 2023

They have published upwards of 1,000 research papers in the fields of natural language processing , computer vision , common sense reasoning , and other key components of artificial intelligence. Researchers help startup founders at the incubator test ideas and develop and train AI models.

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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.

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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.

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Data Science Dojo

FEBRUARY 8, 2024

In the ever-evolving landscape of natural language processing (NLP), embedding techniques have played a pivotal role in enhancing the capabilities of language models. The rise of transformer models The real game-changer in the evolution of embedding techniques came with the advent of the Transformer architecture.

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Data Science Dojo

DECEMBER 8, 2023

For instance, in natural language processing, a model trained on various languages might be tasked with translating a language it has never seen before. By understanding the semantic relationships between languages, the model can make informed translations even in the absence of explicit training data.

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Data Science Dojo

OCTOBER 18, 2023

Transformers have revolutionized natural language processing with their use of self-attention mechanisms.

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Towards AI

AUGUST 25, 2023

Packt, ISBN: 978–1787125933, 2017. O’Reilly Media, ISBN: 978–1491957660, 2017. Natural Language Processing with Python — Analyzing Text with the Natural Language Toolkit. Mirjalili, Python Machine Learning, 2nd ed. Klein, and E. Jurafsky and J.

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Towards AI

SEPTEMBER 7, 2023

The encoder will process the sentence word by word (technically token by token as per Natural Language Processing (NLP) terminology). Transformer Architecture The first transformer was introduced in a paper in 2017. Figure 1: Image courtesy [link] Figure 1 shows an example of French to English-translation.

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Dataconomy

AUGUST 10, 2023

With the application of natural language processing (NLP) and machine learning algorithms, AI systems can understand and translate spoken language into written notes. It can also help with retrieving information from electronic health records (EHRs) and other tasks to alleviate administrative burdens.

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Towards AI

APRIL 8, 2024

While numerous techniques have been explored, methods harnessing natural language processing (NLP) have demonstrated strong performance. Understanding Word2Vec Word2Vec is a pioneering natural language processing (NLP) technique that revolutionized the way we represent words in vector space.

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Smart Data Collective

AUGUST 27, 2019

Did you know that nearly 2 million banking requests were handled by AI bots in 2017? Utilizing natural language processing, banks employ AI chatbots to help customers online. They essentially did the work of 50 full-time employees. That’s powerful stuff. Automated Banking Customer Service.

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Dataconomy

FEBRUARY 6, 2024

Besides, natural language processing (NLP) allows users to gain data insight in a conversational manner, such as through ChatGPT, making data even more accessible. They have a platform called Generative AI Operating System (GenOS) that uses large language models to handle tasks like taxes, accounting, and managing cash flow.

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AWS Machine Learning Blog

JULY 9, 2024

of its consolidated revenues during the years ended December 31, 2019, 2018 and 2017, respectively. Sonnet made key improvements in visual processing and understanding, writing and content generation, natural language processing, coding, and generating insights. As pointed out in Anthropic’s Claude 3.5

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Dataconomy

FEBRUARY 19, 2025

BERT is an open source machine learning framework for natural language processing (NLP) that helps computers understand ambiguous language by using context from surrounding text. In 2017, Google introduced the transformer model, paving the way for innovations like BERT.

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Towards AI

OCTOBER 19, 2024

It’s particularly useful in natural language processing [3]. Kim, “Towards A Rigorous Science of Interpretable Machine Learning,” arXiv preprint arXiv:1702.08608, 2017. [2] Techniques for Peering into the AI Mind Scientists and researchers have developed several techniques to make AI more explainable: 1. References [1] F.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Her research interests lie in Natural Language Processing, AI4Code and generative AI. She received her PhD from Virginia Tech in 2017. He received his PhD from University of Illinois at Urbana-Champaign in 2017. His research interests lie in the area of AI4Code and Natural Language Processing.

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Dataconomy

SEPTEMBER 4, 2023

It uses natural language processing (NLP) techniques to extract valuable insights from textual data. Downtime, like the AWS outage in 2017 that affected several high-profile websites, can disrupt business operations. Text analytics is crucial for sentiment analysis, content categorization, and identifying emerging trends.

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Smart Data Collective

FEBRUARY 24, 2021

Tomorrow Sleep was launched in 2017 as a sleep system startup and ventured on to create online content in 2018. In order to achieve this, Grammarly’s technology combines machine learning with natural language processing approaches. Tomorrow Sleep Achieved 10,000% Increase in Web Traffic.

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IBM Journey to AI blog

JUNE 21, 2023

Learn more about watsonx Automated AI commentary built from foundation models IBM first pioneered the use of AI to curate video highlight reels in 2017, work that earned the IBM Consulting team a 2023 Emmy® Award.

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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!

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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.

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Explosion

FEBRUARY 12, 2017

The Quora dataset is an example of an important type of Natural Language Processing problem: text-pair classification. Tackström, Oscar; Das, Dipanjan; Uszkoreit, Jakob (2016) A large annotated corpus for learning natural language inference Bowman, Samuel R.;

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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.

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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.

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Flipboard

FEBRUARY 5, 2023

First, to ensure expertise, we employ natural-language-processing tools to assist our content developers in auditing and improving our 100-odd courses in more than 40 different languages. Duolingo uses machine learning and other cutting-edge technologies to mimic these three qualities of a good tutor.

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Hacker News

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. This concept is not exclusive to natural language processing, and has also been employed in other domains.

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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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