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

These issues require more than a technical, algorithmic or AI-based solution. 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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Unite.AI

SEPTEMBER 25, 2023

Initially, the attempts were simple and intuitive, with basic algorithms creating monotonous tunes. These deep-learning algorithms dissect individual preferences based on various musical elements such as tempo and mood to craft personalized song suggestions. Creating music using artificial intelligence began several decades ago.

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AWS Machine Learning Blog

DECEMBER 4, 2023

An important aspect of our strategy has been the use of SageMaker and AWS Batch to refine pre-trained BERT models for seven different languages. Fine-tuning multilingual BERT models with AWS Batch GPU jobs We sought a solution to support multiple languages for our diverse user base.

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ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. NLTK is appreciated for its broader nature, as it’s able to pull the right algorithm for any job. Knowing some SQL is also essential.

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IBM Journey to AI blog

JULY 19, 2023

At re:Invent 2022, IBM Consulting was awarded the Global Innovation Partner of the Year and the GSI Partner of the Year for Latin America , cementing client and AWS trust in IBM Consulting as a partner of choice when it comes to AWS. in 10 years, from 2012 to 2022. More than half of algorithms on the U.S.

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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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Marek Rei

NOVEMBER 4, 2024

EMNLP 2022. EMNLP 2022. NeurIPS 2022. EMNLP 2022. EMNLP 2022. They show performance improvements in some settings and speed improvements in all evaluated settings, showing particular usefulness in settings where the LLM needs to retrieve information about multiple entities (e.g. UC Berkeley, CMU. Google Research.

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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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ML @ CMU

FEBRUARY 24, 2023

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. BERT and GPTs) for both classification and generation tasks. We describe the specific formulations in Section §2.1-2.3

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Mlearning.ai

JUNE 8, 2023

Use algorithm to determine closeness/similarity of points. 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. This is embedding/vector/vector embedding for this article. What are Vector Embeddings?

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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. To achieve this, we first chunk each document into segments of roughly 256 tokens, which is half of the maximum BERT LM input length.

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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. This post is partially based on a keynote I gave at the Deep Learning Indaba 2022. The Deep Learning Indaba 2022 in Tunesia.

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John Snow Labs

MAY 26, 2023

Specifically, it involves using pre-trained transformer models, such as BERT or RoBERTa, to encode text into dense vectors that capture the semantic meaning of the sentences. There is also a short section about generating sentence embeddings from Bert word embeddings, focusing specifically on the average-based transformation technique.

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Pickl AI

FEBRUARY 14, 2023

According to the Ministry of Commerce, the number of startups in India has grown from 471 in 2016 to 72,993 in 2022. Significantly, by leveraging technologies like deep learning and proprietary algorithms for analytics, Artivatic.ai Bert Labs Pvt. Artivatic.ai Artivatic.ai Accordingly, Beatoven.ai

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Unite.AI

AUGUST 1, 2023

OpenAI has been instrumental in developing revolutionary tools like the OpenAI Gym, designed for training reinforcement algorithms, and GPT-n models. 2022), innovatively adds the phrase “Let's think step by step” to the original prompt. The spotlight is also on DALL-E, an AI model that crafts images from textual inputs.

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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. This repository holds the competition rules and the benchmark code to run it.

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Dlabs.ai

MAY 22, 2022

It’ll help you get to grips with the fundamentals of ML and its respective algorithms, including linear regression and supervised and unsupervised learning, among others. We wrote about him in our article on the Top AI Influencers To Follow In 2022. Well, that’s the work of ML-powered classification algorithms.

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Heartbeat

NOVEMBER 17, 2023

Different algorithms provide different ways of calculating this distance. The StringDistanceStringEvaluator measures the similarity between two strings using a string distance algorithm like Levenshtein distance. The smaller the distance, the more similar the two strings are. This is useful for validating outputs.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

In November 2022, ChatGPT was released, a large language model (LLM) that used the transformer architecture, and is widely credited with starting the current generative AI boom. This is accomplished by breaking the problem into independent parts so that each processing element can complete its part of the workload algorithm simultaneously.

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AssemblyAI

MAY 3, 2023

This is heavily due to the popularization (and commercialization) of a new generation of general purpose conversational chatbots that took off at the end of 2022, with the release of ChatGPT to the public. Thanks to the widespread adoption of ChatGPT, millions of people are now using Conversational AI tools in their daily lives.

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John Snow Labs

MAY 18, 2023

Word embeddings are generated using algorithms that are trained on large corpora of text data. These algorithms learn to assign each word in the corpus a unique vector representation that captures the word’s meaning based on its context in the text. Using Word2Vec annotator for generating word embeddings using the Word2Vec algorithm.

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Jay Alammar

OCTOBER 3, 2022

V2 Nov 2022 : Updated images for more precise description of forward diffusion. In technical terms, this component is made up of a UNet neural network and a scheduling algorithm. The released Stable Diffusion model uses ClipText (A GPT-based model ), while the paper used BERT. Translations: Chinese , Vietnamese. (

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John Snow Labs

JUNE 5, 2023

Let's just peek into the pre-BERT world… For creating models, we need words to be represented in a form n understood by the training network, ie, numbers. Thus many algorithms were used to convert words into vectors or more precisely, word embeddings. One of the earliest algorithms used for this purpose is word2vec.

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Heartbeat

JANUARY 9, 2024

This is brought on by various developments, such as the availability of data, the creation of more potent computer resources, and the development of machine learning algorithms. LLMs received a lot of media attention when ChatGPT was released in December 2022. BERT and GPT are examples.

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Bugra Akyildiz

FEBRUARY 5, 2023

AITemplate highlights include: High performance: close to roofline fp16 TensorCore (NVIDIA GPU) / MatrixCore (AMD GPU) performance on major models, including ResNet, MaskRCNN, BERT, VisionTransformer, Stable Diffusion, etc. Unified, open, and flexible. Seamless fp16 deep neural network models for NVIDIA GPU or AMD GPU.

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ODSC - Open Data Science

FEBRUARY 14, 2023

Since its release on November 30, 2022 by OpenAI , the ChatGPT public demo has taken the world by storm. Some examples of large language models include GPT (Generative Pre-training Transformer), BERT (Bidirectional Encoder Representations from Transformers), and RoBERTa (Robustly Optimized BERT Approach).

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Mlearning.ai

JANUARY 17, 2024

Major milestones in the last few years comprised BERT (Google, 2018), GPT-3 (OpenAI, 2020), Dall-E (OpenAI, 2021), Stable Diffusion (Stability AI, LMU Munich, 2022), ChatGPT (OpenAI, 2022). And it will change everything. Let us dive into the wild world of genAI.

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Snorkel AI

APRIL 11, 2023

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. And this work appeared in AAAI 2022. The following is a transcript of his presentation, edited lightly for readability. AB : Got it.

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Snorkel AI

APRIL 11, 2023

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. And this work appeared in AAAI 2022. The following is a transcript of his presentation, edited lightly for readability. AB : Got it.

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Snorkel AI

APRIL 11, 2023

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. And this work appeared in AAAI 2022. The following is a transcript of his presentation, edited lightly for readability. AB : Got it.

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Dlabs.ai

MARCH 9, 2022

The authors will walk you through the practical parts of using algorithms in place of mathematical theory. Data Science from Scratch Author: Joel Grus Here’s a title for all data scientists with basic Python, statistics, maths, and algebra knowledge (alongside a grasp of algorithms and machine learning).

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Topbots

JUNE 15, 2023

A comprehensive explanation of the BPE algorithm can be found on the HuggingFace Transformers course. In Findings of the Association for Computational Linguistics: ACL 2022 , pages 2340–2354, Dublin, Ireland. Are All Languages Created Equal in Multilingual BERT? New York: Riverhead Books, 2022 (p. Dryer, Matthew S. &

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AWS Machine Learning Blog

MARCH 6, 2023

Large language models (LLMs) are neural network-based language models with hundreds of millions ( BERT ) to over a trillion parameters ( MiCS ), and whose size makes single-GPU training impractical. NCCL is an NVIDIA-developed open-source library implementing inter-GPU communication algorithms. Note that effective in NCCL 2.12

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Sebastian Ruder

JANUARY 24, 2022

6] such as W2v-BERT [7] as well as more powerful multilingual models such as XLS-R [8]. In mathematics, ML was shown to be able to guide the intuition of mathematicians in order to discover new connections and algorithms [77]. For more work on this topic, check out the EvoNLP workshop at EMNLP 2022. In biology, AlphaFold 2.0

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Snorkel AI

FEBRUARY 13, 2023

Jan Neumann, Vice President, Machine Learning, Comcast Applied AI and Discovery gave a presentation entitled “Data-Centric AI in Comcast’s Voice and Conversational Interfaces” at Snorkels Future of Data-Centric AI conference in 2022. JN: Currently our model is an adaptation of the BERT model.

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Snorkel AI

FEBRUARY 13, 2023

Jan Neumann, Vice President, Machine Learning, Comcast Applied AI and Discovery gave a presentation entitled “Data-Centric AI in Comcast’s Voice and Conversational Interfaces” at Snorkels Future of Data-Centric AI conference in 2022. JN: Currently our model is an adaptation of the BERT model.

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