IBM Journey to AI blog

MARCH 27, 2024

A 2022 CDP study found that for companies that report to CDP, emissions occurring in their supply chain represent an average of 11.4x In recent years, remarkable strides have been achieved in crafting extensive foundation language models for natural language processing (NLP). more emissions than their operational emissions.

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John Snow Labs

JULY 5, 2023

We are delighted to announce the release of Spark NLP 5.0, We are delighted to announce the release of Spark NLP 5.0, Additionally, we are also set to release an array of new LLM models fine-tuned specifically for chat and instruction, now that we have successfully integrated ONNX Runtime into Spark NLP.

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Ehud Reiter

AUGUST 25, 2024

Many people in NLP seem to think that you need to work with the latest and trendiest technology in order to be relevant, both in research and in applications. At the time, the latest and trendiest NLP technology was LSTM (and variants such as biLSTM). LSTMs worked very well in lots of areas of NLP, including machine translation.

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Google Research AI blog

FEBRUARY 28, 2023

In 2022, we expanded our research interactions and programs to faculty and students across Latin America , which included grants to women in computer science in Ecuador. See some of the datasets and tools we released in 2022 listed below. We work towards inclusive goals and work across the globe to achieve them.

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John Snow Labs

MAY 26, 2023

Sentence embeddings with Transformers are a powerful natural language processing (NLP) technique that use deep learning models known as Transformers to encode sentences into fixed-length vectors that can be used for a variety of NLP tasks. Introduction to Spark NLP Spark NLP is an open-source library maintained by John Snow Labs.

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Marktechpost

FEBRUARY 17, 2024

In the evolving landscape of natural language processing (NLP), the ability to grasp and process extensive textual contexts is paramount. 2022), and Ram et al. 2022), GTE by Li et al. 2022), remain behind closed doors. Recent advancements, as highlighted by Lewis et al. 2021), Izacard et al. 2023), and BGE by Xiao et al.

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John Snow Labs

MAY 15, 2023

The underlying principles behind the NLP Test library: Enabling data scientists to deliver reliable, safe and effective language models. However, today there is a gap between these principles and current state-of-the-art NLP models. These findings suggest that the current NLP systems are unreliable and flawed.

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AWS Machine Learning Blog

FEBRUARY 6, 2024

Overall, $384 billion is projected as the cost of pharmacovigilance activities to the overall healthcare industry by 2022. Transformers, BERT, and GPT The transformer architecture is a neural network architecture that is used for natural language processing (NLP) tasks.

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John Snow Labs

JUNE 5, 2023

Sentence detection in Spark NLP is the process of identifying and segmenting a piece of text into individual sentences using the Spark NLP library. Sentence Detection in Spark NLP is the process of automatically identifying the boundaries of sentences in a given text.

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Applied Data Science

DECEMBER 23, 2022

Just wait until you hear what happened in 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. In 2022 we got diffusion models ( NeurIPS paper ).

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IBM Journey to AI blog

JANUARY 25, 2024

Additionally, the models themselves are created from limited architectures: “Almost all state-of-the-art NLP models are now adapted from one of a few foundation models, such as BERT, RoBERTa, BART, T5, etc.

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John Snow Labs

MAY 18, 2023

Word embeddings are considered as a type of representation used in natural language processing (NLP) to capture the meaning of words in a numerical form. Word embeddings are used in natural language processing (NLP) as a technique to represent words in a numerical format.

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Marktechpost

JUNE 24, 2024

AI technologies, such as ML, NLP, and generative models like GPT-3, have reshaped job roles and demanded new skill sets. Data were gathered from 911,637 English tweets from November 2022 to January 2023, focusing on various terms related to ChatGPT. After filtering and processing, 616,073 tweets were analyzed.

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Marek Rei

NOVEMBER 7, 2024

In this post he will share some of our ideas about interpretability, introduce the idea of atomic inference, and give an overview of the work in our 2022 and 2024 EMNLP papers [1,2]. Let me walk through our EMNLP 2022 paper to give you a flavour of what atomic inference methods can look like in practice. This sounds intriguing!

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Marktechpost

SEPTEMBER 17, 2023

The creation of transformer-based NLP models has sparked advancements in designing and using transformer-based models in computer vision and other modalities. Large language models (LLMs) built on transformers, including ChatGPT and GPT-4, have demonstrated amazing natural language processing abilities.

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Sebastian Ruder

JANUARY 24, 2022

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP). 6] such as W2v-BERT [7] as well as more powerful multilingual models such as XLS-R [8]. If CNNs are pre-trained the same way as transformer models, they achieve competitive performance on many NLP tasks [28]. What happened?  

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Snorkel AI

MARCH 1, 2023

BERT BERT, an acronym that stands for “Bidirectional Encoder Representations from Transformers,” was one of the first foundation models and pre-dated the term by several years. BERT proved useful in several ways, including quantifying sentiment and predicting the words likely to follow in unfinished sentences.

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ODSC - Open Data Science

JUNE 9, 2023

The last 12 years though, is where some of the big magic has happened in NLP. Word vectorization is an NLP methodology used to map words or phrases from a vocabulary to a corresponding vector of real numbers used to find word predictions and word similarities or semantics. BERT was designed to understand the meanings of sentences.

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Unite.AI

SEPTEMBER 25, 2023

However, as technology advanced, so did the complexity and capabilities of AI music generators, paving the way for deep learning and Natural Language Processing (NLP) to play pivotal roles in this tech. Technical Insights The MusicLM leverages the principles of AudioLM , a framework introduced in 2022 for audio generation.

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Flipboard

JUNE 20, 2023

Training experiment: Training BERT Large from scratch Training, as opposed to inference, is a finite process that is repeated much less frequently. Training a well-performing BERT Large model from scratch typically requires 450 million sequences to be processed. The first uses traditional accelerated EC2 instances.

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Sebastian Ruder

NOVEMBER 15, 2023

This post consists of two articles that were first published in NLP News. NLP and ML have gone through several phases of how models are trained in recent years. With the arrival of pre-trained models such as BERT, fine-tuning pre-trained models for downstream tasks became the norm.   Zhang et al.

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Sebastian Ruder

NOVEMBER 14, 2022

Research models such as BERT and T5 have become much more accessible while the latest generation of language and multi-modal models are demonstrating increasingly powerful capabilities. At the same time, a wave of NLP startups has started to put this technology to practical use. Data is based on: ml_nlp_paper_data by Marek Rei.

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Unite.AI

AUGUST 1, 2023

2022), innovatively adds the phrase “Let's think step by step” to the original prompt. Let's create an advanced prompt where ChatGPT is tasked with summarizing key takeaways from AI and NLP research papers. This approach, introduced by Kojima et al.

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Snorkel AI

APRIL 18, 2023

Prasanna Balaprakash, research and development lead from Argonne National Laboratory gave a presentation entitled “Extracting the Impact of Climate Change from Scientific Literature using Snorkel-Enabled NLP” at Snorkel AI’s Future of Data-Centric AI Workshop in August, 2022. Even for NLP folks, this is a pretty remarkable thing.

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Snorkel AI

APRIL 18, 2023

Prasanna Balaprakash, research and development lead from Argonne National Laboratory gave a presentation entitled “Extracting the Impact of Climate Change from Scientific Literature using Snorkel-Enabled NLP” at Snorkel AI’s Future of Data-Centric AI Workshop in August, 2022. Even for NLP folks, this is a pretty remarkable thing.

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Flipboard

MARCH 27, 2023

Project Structure Accelerating Convolutional Neural Networks Parsing Command Line Arguments and Running a Model Evaluating Convolutional Neural Networks Accelerating Vision Transformers Evaluating Vision Transformers Accelerating BERT Evaluating BERT Miscellaneous Summary Citation Information What’s New in PyTorch 2.0?

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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. LinkBERT improves previous BERT models on many applications.

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ML @ CMU

FEBRUARY 24, 2023

TL;DR : Prompting enables large language models (LLMs) to perform various NLP tasks without changing the model. Prompting has emerged as a promising approach to solving a wide range of NLP problems using large pre-trained language models (LMs), including left-to-right models such as GPT s and masked LMs such as BERT , RoBERTa , etc.

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Mlearning.ai

JUNE 8, 2023

A few embeddings for different data type For text data, models such as Word2Vec , GLoVE , and BERT transform words, sentences, or paragraphs into vector embeddings. What are Vector Embeddings? Pinecone Used a picture of phrase vector to explain vector embedding. All we need is the vectors for the words.

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Sebastian Ruder

AUGUST 15, 2021

My favourite resources on this topic from the conference are: Chris Pott's keynote on Reliable characterizations of NLP systems as a social responsibility. More recently, in 2022, Benjamin Marie has written additional posts where he analysed shortcomings in the MT evaluation of prominent papers. Mind Your Outliers!

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ODSC - Open Data Science

AUGUST 3, 2023

How to Compute Sentence Similarity Using BERT and Word2Vec The sent2vec is an open-source library. The main goal of this project is to expedite building proof of concepts in NLP projects. CAGR from 2022 to 2031. Global Market for AI Chips Will See a Massive CAGR of 31.8% the global market for AI chipsets will see a 31.8%

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Snorkel AI

MAY 25, 2023

BERT, the first breakout large language model In 2019, a team of researchers at Goole introduced BERT (which stands for bidirectional encoder representations from transformers). By making BERT bidirectional, it allowed the inputs and outputs to take each others’ context into account.

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Snorkel AI

MAY 25, 2023

BERT, the first breakout large language model In 2019, a team of researchers at Goole introduced BERT (which stands for bidirectional encoder representations from transformers). By making BERT bidirectional, it allowed the inputs and outputs to take each others’ context into account.

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AssemblyAI

NOVEMBER 8, 2023

We’ve used the DistilBertTokenizer , which inherits from the BERT WordPiece tokenization scheme. 2022 (Google Research) propose Canine, a tokenization-free Transformer architecture operating directly on character sequences. Training Data : We trained this neural network on a total of 3.7 billion words). Clark et al.,

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Explosion

MAY 17, 2023

But if you’re working on the same sort of Natural Language Processing (NLP) problems that businesses have been trying to solve for a long time, what’s the best way to use them? However, LLMs are not a direct solution to most of the NLP use-cases companies have been working on. That’s definitely new.

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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.[ Are All Languages Created Equal in Multilingual BERT?

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Bugra Akyildiz

DECEMBER 18, 2022

7:08 PM ∙ Dec 18, 2022 Articles Dramatron is a system that uses large language models that could be useful for authors for co-writing theatre scripts and screenplays. Dragon can be used as a drop-in replacement for BERT.

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