AWS Machine Learning Blog

DECEMBER 6, 2023

This method of enriching the LLM generation context with information retrieved from your internal data sources is called Retrieval Augmented Generation (RAG), and produces assistants that are domain specific and more trustworthy, as shown by Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

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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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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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AWS Machine Learning Blog

OCTOBER 11, 2024

Role of metadata while indexing data in vector databases Metadata plays a crucial role when loading documents into a vector data store in Amazon Bedrock. Content categorization – Metadata can provide information about the content or category of a document, such as the subject matter, domain, or topic.

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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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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. 2022 ) : 193k instruction-output examples sourced from 61 existing English NLP tasks. 2022 ) : A crowd-sourced collection of prompts for 177 English NLP tasks.

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Bugra Akyildiz

NOVEMBER 17, 2024

Unite files and metadata together into persistent, versioned, columnar datasets. Generate metadata using local AI models and LLM APIs. Generate metadata using local AI models and LLM APIs. Filter, join, and group by metadata. which uses LLMs and various other NLP models that runs locally on your machine for evaluation.

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AWS Machine Learning Blog

FEBRUARY 20, 2024

ZOO Digital works with over 11,000 freelancers and localized over 600 million words in 2022 alone. Her primary areas of interest encompass Deep Learning, with a focus on GenAI, Computer Vision, NLP, and time series data prediction. in a code subdirectory. in a code subdirectory. in a code subdirectory. in a code subdirectory.

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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 is partially based on a keynote I gave at the Deep Learning Indaba 2022.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

As a first step, they wanted to transcribe voice calls and analyze those interactions to determine primary call drivers, including issues, topics, sentiment, average handle time (AHT) breakdowns, and develop additional natural language processing (NLP)-based analytics.

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Sebastian Ruder

FEBRUARY 23, 2023

For modular fine-tuning for NLP, check out our EMNLP 2022 tutorial. d) Hypernetwork: A small separate neural network generates modular parameters conditioned on metadata. We cover such methods for NLP in our EMNLP 2022 tutorial. This post gives a brief overview of modularity in deep learning. Machine translation.

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John Snow Labs

JUNE 2, 2023

Spark NLP’s deep learning models have achieved state-of-the-art results on sentiment analysis tasks, thanks to their ability to automatically learn features and representations from raw text data. Spark NLP has multiple approaches for detecting the sentiment (which is actually a text classification problem) in a text.

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AWS Machine Learning Blog

MARCH 29, 2023

The creation of AIDA aligns with the UNDP Strategic Plan 2022–2025 to use digitization and innovation for greater development impact. The postprocessing component uses bounding box metadata from Amazon Textract for intelligent data extraction. Metadata tracking is particularly useful to handle errors and retries.

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John Snow Labs

JUNE 6, 2023

Many different transformer models have already been implemented in Spark NLP, and specifically for text classification, Spark NLP provides various annotators that are designed to work with pretrained language models. The table shows the language models and the corresponding annotators for text classification provided by Spark NLP.

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AWS Machine Learning Blog

JUNE 7, 2023

billion in Q3 2021 and Q3 2022, and $6 million and $(11.3) billion for the nine months ended September 30, 2021 and 2022. (2) billion as of December 31, 2021 and September 30, 2022, respectively. However, you can use the asynchronous StartDocumentAnalysis API to process multi-page documents (with up to 3,000 pages).

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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.[ Common Crawl makes up 60% of GPT-3 training data.[

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Topbots

JULY 7, 2023

Chat history was enabled on the 15th of December 2022, and let’s be honest: we all benefit from the storage of our conversations! Complete Conversation History There is another file containing the conversation history, and also including some metadata. The metadata provides information about the main data.

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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. Below follows a transcription of his presentation, lightly edited for readability.

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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. Below follows a transcription of his presentation, lightly edited for readability.

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Pickl AI

JANUARY 16, 2024

Value in 2022 – $271.83 Value in 2022 – $18.10 billion 15.83% Metadata-Driven Data Fabric Systematic data management efficiency. billion 15.60% NLP (Natural Language Processing) Unlocking unstructured data potential. Quantum Computing Awareness Awareness of quantum computing’s potential impact.

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Snorkel AI

JULY 5, 2023

Abhishek Ratna, in AI ML marketing, and TensorFlow developer engineer Robert Crowe, both from Google, spoke as part of a panel entitled “Practical Paths to Data-Centricity in Applied AI” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Robert, you can go first. I have a certain point of view on this.

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AWS Machine Learning Blog

MARCH 6, 2023

The preparation of a natural language processing (NLP) dataset abounds with share-nothing parallelism opportunities. FSx for Lustre uses distributed file storage (stripping) and physically separates file metadata from file content to achieve high-performance read/writes.

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Unite.AI

AUGUST 4, 2023

Langchain: The Fastest Growing Prompt Tool LangChain, launched in October 2022 by Harrison Chase , has become one of the most highly rated open-source frameworks on GitHub in 2023. Here, we also import the transformers library, which is extensively used in NLP tasks. LangChain fills a crucial gap in AI development for the masses.

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Mlearning.ai

DECEMBER 21, 2023

The Curse of the LLMs 30th November, 2022 will be remembered as the watershed moment in artificial intelligence. In May 2020, researchers in their paper “ Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks ” explored models which combine pre-trained parametric and non-parametric memory for language generation.

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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. The Inferentia chip became generally available (GA) in December 2019, followed by Trainium GA in October 2022, and Inferentia2 GA in April 2023.

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AWS Machine Learning Blog

SEPTEMBER 21, 2023

They wanted to take advantage of machine learning (ML) techniques such as computer vision (CV) and natural language processing (NLP) to automate document processing pipelines. As part of this strategy, they developed an in-house passport analysis model to verify passenger IDs. The following diagram illustrates this architecture.

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Flipboard

MARCH 9, 2023

To learn more about large-scale multi-GPU training, refer to Train 175+ billion parameter NLP models with model parallel additions and Hugging Face on Amazon SageMaker and New performance improvements in Amazon SageMaker model parallel library. The models you use can be fine-tuned and served on a single GPU.

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The MLOps Blog

MARCH 21, 2023

To make that possible, your data scientists would need to store enough details about the environment the model was created in and the related metadata so that the model could be recreated with the same or similar outcomes. The challenge is tracking what worked and what didn’t and maintaining reproducibility while maximizing code reuse.

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