John Snow Labs

AUGUST 21, 2023

We are delighted to announce a suite of remarkable enhancements and updates in our latest release of Healthcare NLP. It is a testament to our commitment to continuously innovate and improve, furnishing you with a more sophisticated and powerful toolkit for healthcare natural language processing.

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NLP Categorization Natural Language Processing Automation 98

Unite.AI

APRIL 18, 2024

From self-driving cars to language models that can engage in human-like conversations, AI is rapidly transforming various industries, and software development is no exception. SWE agent LLM LLM Agents: Orchestrating Task Automation LLM agents are sophisticated software entities designed to automate the execution of complex tasks.

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Software Engineer Software Development LLM AI 261

Marktechpost

MARCH 10, 2024

Developing and refining Large Language Models (LLMs) has become a focal point of cutting-edge research in the rapidly evolving field of artificial intelligence, particularly in natural language processing. The survey delineates the extensive scale of data involved, with pre-training corpora alone exceeding 774.5

Large Language Models 97

Large Language Models Natural Language Processing LLM Categorization 97

AssemblyAI

MAY 14, 2024

Speech AI technology (including Speech-to-Text, Audio Intelligence, and LLM capabilities ) has quickly become an integral part of thousands of organizations and developer workflows. It uses natural language processing to identify and organize discussion points, decisions, and future tasks.   Fireflies.ai

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Natural Language Processing Automation Robotics AI 147

Unite.AI

MAY 29, 2024

This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction. Named Entity Recognition ( NER) Named entity recognition (NER), an NLP technique, identifies and categorizes key information in text.

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Data Extraction Neural Network Large Language Models Automation 147

Unite.AI

JANUARY 11, 2024

They serve as a core building block in many natural language processing (NLP) applications today, including information retrieval, question answering, semantic search and more. Model Training: Fine-tune a powerful open-source LLM such as Mistral on the synthetic data using contrastive loss.

Large Language Models 147

Large Language Models Prompt Engineer Prompt Engineering BERT 147

Marktechpost

AUGUST 15, 2023

Large language models (LLMs) have achieved amazing results in a variety of Natural Language Processing (NLP), Natural Language Understanding (NLU) and Natural Language Generation (NLG) tasks in recent years.

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Large Language Models Categorization LLM Natural Language Processing 98

Towards AI

MAY 20, 2023

This new era of custom LLMs marks a significant milestone in the quest for more customizable and efficient language processing solutions. Challenges in building custom LLMs include architecture selection, data quality, bias mitigation, content moderation, resource management, and expertise.

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LLM Large Language Models Chatbots Natural Language Processing 88

Topbots

JULY 24, 2023

The strategies presented in this article, are primarily relevant for developers building large language model (LLM) applications. Instances of unsatisfactory results from a language model are often due to vague instructions. Contrary to popular belief, brevity isn’t synonymous with specificity in LLM prompts.

Prompt Engineer 98

Prompt Engineer Prompt Engineering LLM ChatGPT 98

John Snow Labs

OCTOBER 19, 2023

Generating Synthetic NLP Data to Reduce Sycophancy In our continued pursuit of taming sycophantic behavior in AI models on mathematical data, we focus on Natural Language Processing (NLP). Our toolkit of NLP datasets is extensive, encompassing a wide spectrum of datasets that can be defined in the harness class.

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LLM NLP Large Language Models Categorization 52

AssemblyAI

JANUARY 23, 2024

  By leveraging Deep Learning architectures and training on vast amounts of data, LLMs can process and understand more nuance and context in human language than traditional Natural Language Processing (NLP) models. 

Large Language Models 147

Large Language Models Natural Language Processing Categorization Automation 147

Marktechpost

JULY 4, 2023

Natural language processing (NLP) activities, including speech-to-text, sentiment analysis, text summarization, spell-checking, token categorization, etc., rely on Language Models as their foundation. Unigrams, N-grams, exponential, and neural networks are valid forms for the Language Model.

Large Language Models 91

Large Language Models BERT Natural Language Processing Categorization 91

IBM Journey to AI blog

AUGUST 1, 2023

A foundation model is built on a neural network model architecture to process information much like the human brain does. A specific kind of foundation model known as a large language model (LLM) is trained on vast amounts of text data for NLP tasks. An open-source model, Google created BERT in 2018. All watsonx.ai

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Generative AI Data Scientist BERT Machine Learning 140

Unite.AI

AUGUST 28, 2023

With advancements in deep learning, natural language processing (NLP), and AI, we are in a time period where AI agents could form a significant portion of the global workforce. Transformers and Advanced NLP Models : The introduction of transformer architectures revolutionized the NLP landscape.

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Auto-complete ChatGPT Large Language Models AI 240

John Snow Labs

OCTOBER 19, 2023

How to use the LangTest library to evaluate LLM for bias using CrowS-Pairs dataset? Natural language processing (NLP) is a critical branch of artificial intelligence devoted to understanding and generating natural language. Some example samples. We can check the detailed results using .generated_results()

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BERT Natural Language Processing NLP Categorization 52

AWS Machine Learning Blog

MARCH 13, 2024

The LLM analysis provides a violation result (Y or N) and explains the rationale behind the model’s decision regarding policy violation. The audio moderation workflow activates the LLM’s policy evaluation only when the toxicity analysis exceeds a set threshold. The LLM model returns an analysis result based on the prompt instructions.

LLM 101

LLM Natural Language Processing Prompt Engineer Prompt Engineering 101

Topbots

JULY 6, 2023

In the rapidly evolving field of artificial intelligence, natural language processing has become a focal point for researchers and developers alike. They suggested that scaling up language models can improve task-agnostic few-shot performance. What are the results? F1 in the zero-shot setting, 84.0 What are the results?

LLM 52

LLM Large Language Models Natural Language Processing OpenAI 52

Unite.AI

AUGUST 8, 2023

Processing these numbers through a latent vector gives birth to art that mirrors the complexities of human aesthetics. Generative AI Types: Text to Text, Text to Image Transformers & LLM The paper “ Attention Is All You Need ” by Google Brain marked a shift in the way we think about text modeling. Supports 13 programming languages.

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Generative AI ChatGPT Neural Network Convolutional Neural Networks 243

John Snow Labs

APRIL 22, 2024

While large language models (LLMs) have demonstrated impressive capabilities in various natural language processing (NLP) tasks, their performance in this domain has been limited by the inherent complexities of medical language and the nuances involved in interpreting clinical narratives.

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NLP Categorization Natural Language Processing BERT 64

Marktechpost

DECEMBER 6, 2023

Recent months have seen a significant rise in the popularity of Large Language Models (LLMs). Based on the strengths of Natural Language Processing, Natural Language Understanding, and Natural Language Generation, these models have demonstrated their capabilities in almost every industry.

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Large Language Models LLM Artificial Intelligence Artificial Intelligence 93

AWS Machine Learning Blog

AUGUST 7, 2023

AWS received about 100 samples of labeled data from the customer, which is a lot less than the 1,000 samples recommended for fine-tuning an LLM in the data science community. A rigorous and effective NLP solution, if provided sufficient amounts of labeled data, would be to train a custom language model using the customer’s labeled data.

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Large Language Models LLM BERT ML 73

NVIDIA

JULY 26, 2023

“We expect P5 instances to deliver substantial price-performance benefits over P4d instances, and they’ll be available at the massive scale required for building next-generation LLMs and related products.” For its part, Hugging Face is on a mission to democratize good machine learning. “As

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Computer Vision Machine Learning Neural Network Natural Language Processing 98

IBM Journey to AI blog

APRIL 18, 2024

AI systems like LaMDA and GPT-3 excel at generating human-quality text, accomplishing specific tasks, translating languages as needed, and creating different kinds of creative content. Achieving these feats is accomplished through a combination of sophisticated algorithms, natural language processing (NLP) and computer science principles.

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Neural Network LLM AI AI 226

Topbots

OCTOBER 4, 2023

Here are a few examples across various domains: Natural Language Processing (NLP) : Predictive NLP models can categorize text into predefined classes (e.g., spam vs. not spam), while generative NLP models can create new text based on a given prompt (e.g., a social media post or product description).

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Generative AI Natural Language Processing Machine Learning Convolutional Neural Networks 118

AWS Machine Learning Blog

SEPTEMBER 14, 2023

Amazon Comprehend is a natural-language processing (NLP) service that uses machine learning to uncover valuable insights and connections in text. Knowledge management – Categorizing documents in a systematic way helps to organize an organization’s knowledge base. This allows for better monitoring and auditing.

Categorization 90

Categorization Machine Learning Data Scientist Natural Language Processing 90

Flipboard

DECEMBER 6, 2023

Tools like LangChain , combined with a large language model (LLM) powered by Amazon Bedrock or Amazon SageMaker JumpStart , simplify the implementation process. Types of summarizations There are several techniques to summarize text, which are broadly categorized into two main approaches: extractive and abstractive summarization.

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BERT Large Language Models Artificial Intelligence Artificial Intelligence 128

AWS Machine Learning Blog

OCTOBER 24, 2023

You can use LLMs in one or all phases of IDP depending on the use case and desired outcome. In this architecture, LLMs are used to perform specific tasks within the IDP workflow. Document classification – In addition to using Amazon Comprehend , you can use an LLM to classify documents using few-shot prompting.

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IDP LLM Prompt Engineer Prompt Engineering 107

Snorkel AI

MAY 25, 2023

in the linked article) in a process that results not only in a set of valuable weights for the model, but also an embedding for each word fed to it. At inference time, users provide “prompts” to the LLM—snippets of text that the model uses as a jumping-off point. Within a short time, BERT became the standard tool for NLP tasks.

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Large Language Models BERT Neural Network LLM 52

Snorkel AI

MAY 25, 2023

in the linked article) in a process that results not only in a set of valuable weights for the model, but also an embedding for each word fed to it. At inference time, users provide “prompts” to the LLM—snippets of text that the model uses as a jumping-off point. Within a short time, BERT became the standard tool for NLP tasks.

Large Language Models 52

Large Language Models BERT Neural Network LLM 52

Snorkel AI

MARCH 1, 2023

This process results in generalized models capable of a wide variety of tasks, such as image classification, natural language processing, and question-answering, with remarkable accuracy. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Devlin et al.

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BERT Natural Language Processing Large Language Models Neural Network 83

AWS Machine Learning Blog

MAY 7, 2024

We also examine the uplift from fine-tuning an LLM for a specific extractive task. Whether you’re looking to classify documents, extract keywords, detect and redact personally identifiable information (PIIs), or parse semantic relationships, you can start ideating your use case and use LLMs for your natural language processing (NLP).

Prompt Engineer 89

Prompt Engineer Prompt Engineering Large Language Models LLM 89

IBM Journey to AI blog

FEBRUARY 9, 2024

The incoming generation of interdisciplinary models, comprising proprietary models like OpenAI’s GPT-4V or Google’s Gemini, as well as open source models like LLaVa, Adept or Qwen-VL, can move freely between natural language processing (NLP) and computer vision tasks.

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AI AI Generative AI Artificial Intelligence 241

AWS Machine Learning Blog

APRIL 25, 2024

Calculate a ROUGE-N score You can use the following steps to calculate a ROUGE-N score: Tokenize the generated summary and the reference summary into individual words or tokens using basic tokenization methods like splitting by whitespace or natural language processing (NLP) libraries.

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BERT NLP Algorithm Neural Network 101

Explosion

FEBRUARY 15, 2023

As many large financial institutions push to use Natural Language Processing (NLP) to digitize their customer support channels, smaller financial institutions like credit unions and community banks are having a tough time to keep pace. Cheyanne Baird is a NLP Research Scientist on Posh Technologies’ NLP team.

Chatbots 59

Chatbots NLP Data Scientist OpenAI 59

AWS Machine Learning Blog

APRIL 27, 2023

Solution overview With the onset of large language models, the field has seen tremendous progress on various natural language processing (NLP) benchmarks. We also convert the categorical variable t into a natural language sentence. Multitask Learning 66.22 ± 0.7% Iterative Refinement 61.85 ± 3.3%

Machine Learning 64

Machine Learning Large Language Models Categorization Natural Language Processing 64

AWS Machine Learning Blog

NOVEMBER 1, 2023

Visual language processing (VLP) is at the forefront of generative AI, driving advancements in multimodal learning that encompasses language intelligence, vision understanding, and processing. Central to the architecture are the fine-tuned VLM and LLM, both instrumental in decoding visual and textual data streams.

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Auto-classification LLM Auto-complete Generative AI 87

Topbots

DECEMBER 19, 2023

The Many Faces of Responsible AI In her presentation , Lora Aroyo, a Research Scientist at Google Research, highlighted a key limitation in traditional machine learning approaches: their reliance on binary categorizations of data as positive or negative examples. million ratings in total).

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Computer Vision Natural Language Processing AI Researcher AI Research 52