Unite.AI

JUNE 2, 2023

Based on this, it makes an educated guess about the importance of incoming emails, and categorizes them into specific folders. In addition to the smart categorization of emails, SaneBox also comes with a feature named SaneBlackHole, designed to banish unwanted emails.

Categorization 261

Categorization Natural Language Processing Automation AI 261

Artificial Corner

AUGUST 29, 2023

Through these wordclouds, we can see which areas the airline should look into and review their processes on. Topic modelling is a type of statistical modelling in Natural Language Processing to identify topics among a collection of documents. Moving on to topic modelling. The new distribution will be equal as such.

Natural Language Processing 76

Natural Language Processing Machine Learning Data Analysis Categorization 76

IBM Journey to AI blog

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate? This is where LLMs come into play.

ESG 238

ESG Categorization Large Language Models NLP 238

Marktechpost

APRIL 5, 2024

King’s College London researchers have highlighted the importance of developing a theoretical understanding of why transformer architectures, such as those used in models like ChatGPT, have succeeded in natural language processing tasks.

Neural Network 128

Neural Network Natural Language Processing Categorization Explainability 128

AssemblyAI

DECEMBER 19, 2024

Voice intelligence combines speech recognition, natural language processing, and machine learning to turn voice data into actionable insights. Natural Language Processing (NLP)  Once speech becomes text, natural language processing, or NLP, models analyze the actual meaning.

Natural Language Processing 130

Natural Language Processing Categorization Automation NLP 130

Aiiot Talk

JANUARY 24, 2024

AI algorithms can categorize emails more effectively than traditional filters, prioritizing important messages and reducing the clutter of less relevant ones. The Complexity of Contextual Understanding Despite advancements in natural language processing, AI still struggles with understanding the nuances and context of human language fully.

Automation 231

Automation Artificial Intelligence Artificial Intelligence Natural Language Processing 231

Unite.AI

DECEMBER 5, 2024

In addition, AI efficiently categorizes threats by assessing their potential severity, impact and damage. These chatbots have natural language processing algorithms that allow them to read, interpret and comprehend languages. This will trigger the incident response team to jump in and protect coverage.

Data Analysis 173

Data Analysis Automation AI AI 173

Unite.AI

MAY 10, 2024

With its intelligent search capabilities and advanced natural language processing, Elicit helps researchers quickly identify the most relevant papers and understand their core ideas through automatically generated summaries.

AI Researcher 147

AI Researcher AI Research Natural Language Processing Machine Learning 147

John Snow Labs

MAY 10, 2023

Despite the laborious nature of the task, the notes are not structured in a way that can be effectively analyzed by a computer. Without Natural Language Processing, the unstructured data is of no use to modern computer-based algorithms. They used this information to classify patients into four different groups.

Natural Language Processing 52

Natural Language Processing NLP Categorization Big Data 52

Marktechpost

FEBRUARY 22, 2024

In computer vision, convolutional networks acquire a semantic understanding of images through extensive labeling provided by experts, such as delineating object boundaries in datasets like COCO or categorizing images in ImageNet. This approach has demonstrated effectiveness in natural language processing and reinforcement learning.

Computer Vision 130

Computer Vision Natural Language Processing Neural Network Categorization 130

Unite.AI

SEPTEMBER 18, 2023

Types of AI in ITSM AI in ITSM can be categorized into three types: automation, chatbots, and predictive analysis. Modern AI chatbots are equipped with Natural Language Processing ( NLP ) to understand and respond to user queries in a more human-like manner. Let's look into these more closely in the following sections.

Chatbots 261

Chatbots Automation AI AI 261

Marktechpost

APRIL 30, 2024

PEFT’s applicability extends beyond Natural Language Processing (NLP) to computer vision (CV), garnering interest in fine-tuning large-parameter vision models like Vision Transformers (ViT) and diffusion models, as well as interdisciplinary vision-language models.

Large Language Models 133

Large Language Models Categorization Natural Language Processing Algorithm 133

IBM Journey to AI blog

DECEMBER 20, 2023

And retailers frequently leverage data from chatbots and virtual assistants, in concert with ML and natural language processing (NLP) technology, to automate users’ shopping experiences. Regression algorithms —predict output values by identifying linear relationships between real or continuous values (e.g.,

Machine Learning 230

Machine Learning Neural Network Algorithm Computer Vision 230

Unite.AI

DECEMBER 7, 2024

These innovative platforms combine advanced AI and natural language processing (NLP) with practical features to help brands succeed in digital marketing, offering everything from real-time safety monitoring to sophisticated creator verification systems.

AI Tools 278

AI Tools Automation NLP Algorithm 278

Marktechpost

MAY 5, 2024

Consequently, there’s been a notable uptick in research within the natural language processing (NLP) community, specifically targeting interpretability in language models, yielding fresh insights into their internal operations. Recent approaches automate circuit discovery, enhancing interpretability.

Natural Language Processing 116

Natural Language Processing Categorization Neural Network NLP 116

Marktechpost

AUGUST 31, 2024

Large Language Models (LLMs) have demonstrated remarkable capabilities in various natural language processing tasks. Categorized: Refines the flagging mechanism by incorporating granular hallucination categories, including a specific category (hallu12) to signal inconsistencies where the text is not a hallucination.

Large Language Models 130

Large Language Models Categorization LLM Explainability 130

John Snow Labs

MAY 24, 2023

Therefore, the data needs to be properly labeled/categorized for a particular use case. In this article, we will discuss the top Text Annotation tools for Natural Language Processing along with their characteristic features. The model must be taught to identify specific entities to make accurate predictions.

Natural Language Processing 52

Natural Language Processing NLP Machine Learning Auto-classification 52

AWS Machine Learning Blog

JUNE 25, 2024

Manually analyzing and categorizing large volumes of unstructured data, such as reviews, comments, and emails, is a time-consuming process prone to inconsistencies and subjectivity. Businesses can use LLMs to gain valuable insights, streamline processes, and deliver enhanced customer experiences. No explanation is required.

Automation 132

Automation Prompt Engineer Prompt Engineering Categorization 132

Marktechpost

APRIL 6, 2024

Recent advancements integrate machine learning and natural language processing with TRIZ to streamline its reasoning process. AutoTRIZ emphasizes controlling the problem-solving process while drawing problem-related knowledge from the pre-trained large-scale corpora used to train the LLM.

Large Language Models 136

Large Language Models Automation Natural Language Processing Categorization 136

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. A significant innovation in this domain is creating a specialized tool to refine the dataset compilation process.

Large Language Models 115

Large Language Models Natural Language Processing LLM Categorization 115

Marktechpost

APRIL 10, 2024

The abundance of web-scale textual data available has been a major factor in the development of generative language models, such as those pretrained as multi-purpose foundation models and tailored for particular Natural Language Processing (NLP) tasks.

Machine Learning 133

Machine Learning Natural Language Processing Categorization NLP 133

Marktechpost

MAY 7, 2024

The rapid advancement of Large Language Models (LLMs) has sparked interest among researchers in academia and industry alike. Moreover, differences in data table structures between BI and traditional SQL contexts further complicate the translation process.

Business Intelligence 119

Business Intelligence Prompt Engineer Prompt Engineering Natural Language Processing 119

Marktechpost

DECEMBER 25, 2023

This tool enhances data exploration by integrating cutting-edge Natural Language Processing (NLP) techniques. Imagine organizing and categorizing information in a way that reveals valuable insights without manually sifting through endless data points.

Natural Language Processing 115

Natural Language Processing Categorization Data Analysis NLP 115

AssemblyAI

MAY 14, 2024

It uses natural language processing to identify and organize discussion points, decisions, and future tasks. It automatically categorizes, summarizes, and extracts actionable insights from customer calls, such as flagging questions and complaints.   Fireflies.ai

Natural Language Processing 147

Natural Language Processing Automation Robotics Categorization 147

Unite.AI

AUGUST 22, 2023

In a nutshell, Algolia NeuralSearch integrates keyword matching with vector-based natural language processing , powered by LLMs, in a single API – an industry first. In September 2022, Search.io Moreover, Adaptive Learning based on user feedback fine-tunes intent understanding.

Big Data 246

Big Data Neural Network Natural Language Processing Hybrid AI 246

Marktechpost

MAY 9, 2024

In Natural Language Processing (NLP) tasks, data cleaning is an essential step before tokenization, particularly when working with text data that contains unusual word separations such as underscores, slashes, or other symbols in place of spaces.

NLP 124

NLP Natural Language Processing Metadata Large Language Models 124

Marktechpost

MARCH 22, 2024

Despite the remarkable progress of LLMs in natural language processing, they remain susceptible to jailbreak attempts. Researchers investigating LLM security vulnerabilities have explored various jailbreak attack methodologies, categorized into Human-Design, Long-tail Encoding, and Prompt Optimization.

Machine Learning 134

Machine Learning LLM Natural Language Processing Categorization 134

Unite.AI

JUNE 11, 2024

This multilingual training regimen includes languages from diverse regions such as Western Europe, Eastern and Central Europe, the Middle East , Eastern Asia and Southern Asia. By effectively processing extended contexts, Qwen2 can provide more accurate and comprehensive responses, unlocking new frontiers in natural language processing.

Large Language Models 182

Large Language Models Natural Language Processing Categorization Artificial Intelligence 182

Marktechpost

JANUARY 21, 2024

Large Language Models (LLMs) have exhibited remarkable prowess across various natural language processing tasks. However, applying them to Information Retrieval (IR) tasks remains a challenge due to the scarcity of IR-specific concepts in natural language.

Large Language Models 140

Large Language Models Natural Language Processing Categorization NLP 140

Marktechpost

DECEMBER 18, 2023

The attention mechanism has played a significant role in natural language processing and large language models. The researchers emphasized that transformers utilize an old-school method similar to support vector machines (SVM) to categorize data into relevant and non-relevant information. Check out the Paper.

Natural Language Processing 105

Natural Language Processing Large Language Models Chatbots Explainability 105

AssemblyAI

NOVEMBER 6, 2024

Customer Service and Support Speech AI technology provides more accurate, insightful call analysis by automatically categorizing, summarizing, and extracting actionable insights from customer calls—such as flagging questions and complaints.

AI 147

AI AI Natural Language Processing Categorization 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.

Data Extraction 273

Data Extraction Neural Network Large Language Models NLP 273

Marktechpost

SEPTEMBER 25, 2023

Large Language Models (LLMs) have made significant progress in text creation tasks, among other natural language processing tasks. Existing benchmarks frequently use simple objective metrics like word overlap to gauge how well the content produced by the machine is categorizing information.

Large Language Models 130

Large Language Models LLM Natural Language Processing Categorization 130

Marktechpost

JULY 10, 2024

Lytix automatically mines text data for insights using natural language processing techniques, such as: Through sentiment analysis, Lytix can determine the tone of text data, including whether it is favorable, negative, or neutral.

LLM 111

LLM Natural Language Processing Categorization AI 111

Unite.AI

APRIL 16, 2024

One notable innovation in regulatory monitoring is the integration of natural language processing (NLP) and machine learning algorithms. By identifying relevant updates, extracting key information, and categorizing regulatory changes based on their potential impact, these technologies streamline the monitoring process.

Automation 162

Automation Natural Language Processing AI AI 162

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 105

Large Language Models BERT Natural Language Processing Categorization 105

Marktechpost

JANUARY 24, 2024

With the growth of Deep learning, it is used in many fields, including data mining and natural language processing. Further, the researchers developed a machine learning model that can categorize images according to disturbances they have via forward-backward cycles.

Neural Network 115

Neural Network Deep Learning Data Mining Natural Language Processing 115