ODSC - Open Data Science

FEBRUARY 28, 2023

Narrowing the communications gap between humans and machines is one of SAS’s leading projects in their work with NLP. Improving Operations and Infrastructure Taipy The inspiration for this open-source software for Python developers was the frustration felt by those who were trying, and struggling, to bring AI algorithms to end-users.

Data Science 96

Data Science Auto-complete Machine Learning AI 96

Topbots

SEPTEMBER 11, 2023

This approach leads them straight into the integration fallacy: even if these experts and engineers produce exceptional models and algorithms, their outputs often get stuck at the level of playgrounds, sandboxes, and demos, and never really become full-fledged parts of a product. 3] Don Norman (2013). 2] Orbit Media (2022).

UX Design 59

UX Design AI AI Automation 59

Sebastian Ruder

OCTOBER 26, 2019

Cross-lingual learning might be useful—but why should we care about applying NLP to other languages in the first place? The NLP Resource Hierarchy In current machine learning, the amount of available training data is the main factor that influences an algorithm's performance. 2015 , Artetxe et al.,

BERT 52

BERT NLP Neural Network Natural Language Processing 52

Lexalytics

APRIL 5, 2021

This would change in 1986 with the publication of “Parallel Distributed Processing” [ 6 ], which included a description of the backpropagation algorithm [ 7 ]. In retrospect, this algorithm seems obvious, and perhaps it was. We were definitely in a Kuhnian pre-paradigmatic period. It would not be the last time that happened.)

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Artificial Corner

JUNE 6, 2023

Data mining involves using sophisticated algorithms to identify patterns and relationships in data that might not be immediately apparent. Its ability to efficiently handle iterative algorithms and machine learning tasks made it a popular choice for data scientists and engineers. Zaharia, M., Spark: cluster computing with working sets.

Data Mining 52

Data Mining Big Data ETL Machine Learning 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. 2 ] Multilingual models perform worse on several NLP tasks on low resource languages than on high resource languages such as English.[ Common Crawl makes up 60% of GPT-3 training data.[ OpenAI API.

Natural Language Processing 59

Natural Language Processing Computational Linguistics NLP ChatGPT 59

Explosion

DECEMBER 17, 2013

I wrote this blog post in 2013, describing an exciting advance in natural language understanding technology. Today, almost all high-performance parsers are using a variant of the algorithm described below (including spaCy). 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

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. They are now the foundation of today’s NLP systems. 2013. ↩ Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing.

BERT 40

BERT Natural Language Processing NLP Neural Network 40

Probably Approximately a Scientific Blog

AUGUST 30, 2019

This has caused some fear among the general population; some criticism among other NLP people; and many questions from their relatives ("hey, look at this article I've found - did they just solve NLP? The effect is similar to the effect that pre-trained word embeddings had on NLP in 2013. For a given sentence w 1.

NLP 52

NLP BERT OpenAI Natural Language Processing 52

Probably Approximately a Scientific Blog

JANUARY 3, 2016

2] , but gained extreme popularity with word2vec [3] in 2013. Without getting too technical, this is what these algorithms basically do: they start from a random vector for each word in the vocabulary. Similar words still have similar vectors - this is what the algorithms aim to do while learning these vectors. CoRR, 2013.

Natural Language Processing 52

Natural Language Processing Algorithm Deep Learning NLP 52

NLP People

JULY 24, 2019

We took the opportunity to review major research trends in the animated NLP space and formulate some implications from the business perspective. The article is backed by a statistical and – guess what – NLP-based analysis of ACL papers from the last 20 years. But what is the substance behind the buzz?

NLP 52

NLP Neural Network Deep Learning Natural Language Processing 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

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). Finally, one can use a sentence similarity evaluation metric to evaluate the algorithm.

Neural Network 52

Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

ODSC - Open Data Science

FEBRUARY 29, 2024

The Facebook AI Research Lab (FAIR) Established in 2013, FAIR has quickly become one of the most influential AI research labs in the world, partially when it comes to open-source technology and models such as Llama 2. Notably, BAIR recently unveiled a pioneering algorithm that revolutionizes the efficiency of deep learning models.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI Researcher AI Research 52

ML Review

MAY 3, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part One) This is the first instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). Thanks for reading!

Neural Network 52

Neural Network Computer Vision Deep Learning Convolutional Neural Networks 52

Viso.ai

DECEMBER 21, 2023

From the development of sophisticated object detection algorithms to the rise of convolutional neural networks (CNNs) for image classification to innovations in facial recognition technology, applications of computer vision are transforming entire industries. With this, he aimed to create more versatile and adaptive learning algorithms.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52