Allen AI

JULY 8, 2023

NLPositionality: Characterizing Design Biases of Datasets and Models Sebastin Santy, Jenny Liang, Ronan Le Bras*, Katharina Reinecke, Maarten Sap* Design biases in NLP systems, such as performance differences for different populations, often stem from their creator’s positionality, i.e., views and lived experiences shaped by identity and background.

Computational Linguistics 52

Computational Linguistics NLP Explainability AI Researcher 52

Topbots

JUNE 15, 2023

Language Disparity in Natural Language Processing This digital divide in natural language processing (NLP) is an active area of research. 70% of research papers published in a computational linguistics conference only evaluated English.[ Square One Bias in NLP: Towards a Multi-Dimensional Exploration of the Research Manifold.

Natural Language Processing 59

Natural Language Processing Computational Linguistics NLP ChatGPT 59

Heartbeat

FEBRUARY 8, 2023

Source: Author The field of natural language processing (NLP), which studies how computer science and human communication interact, is rapidly growing. By enabling robots to comprehend, interpret, and produce natural language, NLP opens up a world of research and application possibilities.

Natural Language Processing 52

Natural Language Processing NLP Machine Learning Deep Learning 52

Viso.ai

JULY 18, 2024

If a computer program is trained on enough data such that it can analyze, understand, and generate responses in natural language and other forms of content, it is called a Large Language Model (LLM). An easy way to describe LLM is an AI algorithm capable of understanding and generating human language.

Large Language Models 52

Large Language Models Neural Network Natural Language Processing BERT 52

Sebastian Ruder

NOVEMBER 14, 2022

At the same time, a wave of NLP startups has started to put this technology to practical use. I will be focusing on topics related to natural language processing (NLP) and African languages as these are the domains I am most familiar with. This post takes a closer look at how the AI community is faring in this endeavour.

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics BERT 52

Topbots

JANUARY 30, 2023

We are quick to attribute intelligence to models and algorithms, but how much of this is emulation, and how much is really reminiscent of the rich language capability of humans? In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics , pages 5185–5198, Online. 10.48550/arXiv.2212.08120.

Large Language Models 52

Large Language Models Computational Linguistics LLM Natural Language Processing 52

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.

Machine Learning 112

Machine Learning Natural Language Processing Computational Linguistics NLP 112

AWS Machine Learning Blog

MARCH 2, 2023

Sentiment analysis and other natural language programming (NLP) tasks often start out with pre-trained NLP models and implement fine-tuning of the hyperparameters to adjust the model to changes in the environment. He spent 10 years as Head of Morgan Stanley’s Algorithmic Trading Division in San Francisco.

BERT 97

BERT Deep Learning Metadata Auto-complete 97

Sebastian Ruder

JUNE 6, 2022

Seeing the emergence of such multilingual multimodal approaches is particularly encouraging as it is an improvement over the previous year’s ACL where multimodal approaches mainly dealt with English (based on an analysis of “multi-dimensional” NLP research we did for an ACL 2022 Findings paper ). Similarly, Hofmann et al.

NLP 52

NLP Natural Language Processing Computational Linguistics Neural Network 52

Explosion

MAY 8, 2016

The algorithmic changes needed to process German are an important step towards processing many other languages. This means that an English-only NLP system can get away with some very useful simplifying assumptions. They share a relatively recent common ancestor, so they’re structurally similar. It’s a simplifying assumption.

Convolutional Neural Networks 40

Convolutional Neural Networks NLP Algorithm Neural Network 40

Sebastian Ruder

FEBRUARY 23, 2023

For modular fine-tuning for NLP, check out our EMNLP 2022 tutorial. Fixed routing can select different modules for different aspects of the target setting such as task and language in NLP or robot and task in RL, which enables generalisation to unseen scenarios. We cover such methods for NLP in our EMNLP 2022 tutorial.

Deep Learning 52

Deep Learning NLP Computer Vision Metadata 52

Applied Data Science

DECEMBER 23, 2022

In our review of 2019 we talked a lot about reinforcement learning and Generative Adversarial Networks (GANs), in 2020 we focused on Natural Language Processing (NLP) and algorithmic bias, in 202 1 Transformers stole the spotlight. Just wait until you hear what happened in 2022. Who should I follow?

Neural Network 52

Neural Network Data Science AI AI 52

NLP People

SEPTEMBER 12, 2017

This job brought me in close contact with a large number of IT researchers, and some of them happened to work in computational linguistics and machine learning. The project I was working on was aimed at encouraging school students to consider a career in IT.

Computational Linguistics 52

Computational Linguistics Machine Learning Data Mining Natural Language Processing 52

Explosion

DECEMBER 17, 2013

Today, almost all high-performance parsers are using a variant of the algorithm described below (including spaCy). You should probably at least skim that post before reading this one, unless you’re very familiar with NLP research. This doesn’t just give us a likely advantage in learnability; it can have deep algorithmic implications.

Python 45

Python Algorithm NLP Computational Linguistics 45

The Stanford AI Lab Blog

JANUARY 21, 2022

Indeed, this recipe of massive, diverse datasets combined with scalable offline learning algorithms (e.g. self-supervised or cheaply supervised learning) has been the backbone of the many recent successes of foundation models 3 in NLP 4 5 6 7 8 9 and vision 10 11 12. Neumann, M., Gardner, M., Zettlemoyer, L. Toutanova, K. Goyal, N.,

Robotics 40

Robotics Computational Linguistics BERT Computer Vision 40

The MLOps Blog

JANUARY 25, 2023

Sentiment analysis, commonly referred to as opinion mining/sentiment classification, is the technique of identifying and extracting subjective information from source materials using computational linguistics , text analysis , and natural language processing. are used to classify the text sentiment.

BERT 52

BERT Natural Language Processing ML Deep Learning 52

ML Review

MARCH 5, 2019

Word embeddings Visualisation of word embeddings in AI Distillery Word2vec is a popular algorithm used to generate word representations (aka embeddings) for words in a vector space. Then, the algorithm proceeds with the following word as the new centre word, i.e. “learning”, sets up the new context, and repeats the same procedure.

AI 40

AI AI Computer Vision Computational Linguistics 40

NLP People

JULY 24, 2019

The 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019) is starting this week in Florence, Italy. We took the opportunity to review major research trends in the animated NLP space and formulate some implications from the business perspective. But what is the substance behind the buzz?

NLP 52

NLP Neural Network Deep Learning Natural Language Processing 52

ODSC - Open Data Science

MARCH 6, 2024

Artificial Intelligence has made significant strides since its inception, evolving from simple algorithms to highly advanced Neural Networks capable of performing sophisticated tasks such as generating completely new content, including images, audio, and video. She is currently part of the Artificial Intelligence Practice at Avanade.

Responsible AI 52

Responsible AI Generative AI Natural Language Processing Artificial Intelligence 52

ML @ CMU

SEPTEMBER 22, 2023

An algorithm audit 1 is a method of repeatedly querying an algorithm and observing its output in order to draw conclusions about the algorithm’s opaque inner workings and possible external impact. Auditing Algorithms: Understanding Algorithmic Systems from the Outside In Found. Trends Human Computer Interaction. [2]

Computational Linguistics 105

Computational Linguistics LLM Large Language Models Algorithm 105