Towards AI

MAY 20, 2023

Challenges of building custom LLMs Building custom Large Language Models (LLMs) presents an array of challenges to organizations that can be broadly categorized under data, technical, ethical, and resource-related issues. Ensuring data quality during collection is also important.

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LLM Large Language Models Chatbots Natural Language Processing 98

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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Data Ingestion Metadata NLP Data Scientist 128

AWS Machine Learning Blog

FEBRUARY 28, 2023

The high-level steps involved in the solution are as follows: Use AWS Step Functions to orchestrate the health data anonymization pipeline. Use Amazon Athena queries for the following: Extract non-sensitive structured data from Amazon HealthLake. Perform one-hot encoding with Amazon SageMaker Data Wrangler. code, code.coding[1].display

ML 98

ML Machine Learning Categorization NLP 98

Becoming Human

MAY 9, 2024

Introduction about NER Named entity recognition (NER) is a fundamental aspect of natural language processing (NLP). NLP is a branch of artificial intelligence (AI) that aims to teach machines how to understand, interpret, and generate human language. These datasets act as training data for machine learning models.

Natural Language Processing 52

Natural Language Processing NLP Categorization Data Mining 52

Pickl AI

NOVEMBER 18, 2024

The article also addresses challenges like data quality and model complexity, highlighting the importance of ethical considerations in Machine Learning applications. Key steps involve problem definition, data preparation, and algorithm selection. Data quality significantly impacts model performance.

Machine Learning 52

Machine Learning Algorithm Data Quality Neural Network 52

AWS Machine Learning Blog

NOVEMBER 1, 2024

Fine-tuning is a powerful approach in natural language processing (NLP) and generative AI , allowing businesses to tailor pre-trained large language models (LLMs) for specific tasks. By fine-tuning, the LLM can adapt its knowledge base to specific data and tasks, resulting in enhanced task-specific capabilities.

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LLM Prompt Engineer Prompt Engineering Generative AI 101

Chatbots Life

MAY 19, 2023

A chatbot is a technological genie that uses intelligent automation, ML, and NLP to automate tasks. They achieve this by asking the user for input, seeking confirmation, and collecting essential data for back-end business systems, boosting data quality and avoiding mistakes.

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Chatbots Automation Auto-complete NLP 95

Heartbeat

AUGUST 29, 2023

In a min-max game where the generator tries to trick the discriminator and the discriminator strives to accurately categorize the samples, the generator and discriminator networks are trained in tandem. Categorizing Deep Learning Into Various Types Deep learning can be divided into distinct forms based on numerous characteristics.

Software Development 52

Software Development Deep Learning Neural Network Convolutional Neural Networks 52

Snorkel AI

JULY 19, 2023

But this approach is expensive, time-consuming, and out of reach for all but the most well-funded companies, making the use of free, open-source alternatives for data curation appealing if sufficiently high data quality can be achieved.

Categorization 52

Categorization ChatGPT Large Language Models Generative AI 52

Snorkel AI

JULY 19, 2023

But this approach is expensive, time-consuming, and out of reach for all but the most well-funded companies, making the use of free, open-source alternatives for data curation appealing if sufficiently high data quality can be achieved.

Categorization 52

Categorization ChatGPT Large Language Models Generative AI 52

Snorkel AI

JULY 19, 2023

But this approach is expensive, time-consuming, and out of reach for all but the most well-funded companies, making the use of free, open-source alternatives for data curation appealing if sufficiently high data quality can be achieved.

Categorization 52

Categorization ChatGPT Large Language Models Generative AI 52

Pickl AI

SEPTEMBER 12, 2024

Key Components of Data Science Data Science consists of several key components that work together to extract meaningful insights from data: Data Collection: This involves gathering relevant data from various sources, such as databases, APIs, and web scraping.

Data Science 52

Data Science Machine Learning Data Mining Algorithm 52

Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. Assigning complaints to staff.

Large Language Models 52

Large Language Models AI AI Natural Language Processing 52

Snorkel AI

OCTOBER 27, 2023

Instead of exclusively relying on a singular data development technique, leverage a variety of techniques such as promoting, RAG, and fine-tuning for the most optimal outcome. Focus on improving data quality and transforming manual data development processes into programmatic operations to scale fine-tuning.

LLM 52

LLM Data Scientist Machine Learning Large Language Models 52

Snorkel AI

JULY 19, 2023

But this approach is expensive, time-consuming, and out of reach for all but the most well-funded companies, making the use of free, open-source alternatives for data curation appealing if sufficiently high data quality can be achieved.

Categorization 40

Categorization ChatGPT Large Language Models Generative AI 40

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. In safety evaluation tasks, experts disagree on 40% of examples.

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Computer Vision Natural Language Processing AI Researcher AI Research 52

Viso.ai

JUNE 24, 2024

We can categorize the types of AI for the blind and their functions. Data Collection and Annotation Deep learning models are highly dependent on data quality and volume. Data collection and cleaning are critical steps in developing effective deep-learning models. A conceptual framework for most assistive tools.

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Computer Vision Convolutional Neural Networks AI AI 40

Marktechpost

JUNE 10, 2024

The emergence of large language models (LLMs) such as Llama, PaLM, and GPT-4 has revolutionized natural language processing (NLP), significantly advancing text understanding and generation. These causes can be broadly categorized into three parts: 1.

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Large Language Models Categorization Data Quality Natural Language Processing 141

Defined.ai blog

APRIL 10, 2023

Named Entity Recognition (NER) is a natural language processing (NLP) subtask that involves automatically identifying and categorizing named entities mentioned in a text, such as people, organizations, locations, dates, and other proper nouns.

NLP 52

NLP Categorization Natural Language Processing Algorithm 52

Defined.ai blog

APRIL 10, 2023

Named Entity Recognition (NER) is a natural language processing (NLP) subtask that involves automatically identifying and categorizing named entities mentioned in a text, such as people, organizations, locations, dates, and other proper nouns.

NLP 52

NLP Categorization Natural Language Processing Algorithm 52

Dlabs.ai

DECEMBER 6, 2022

They’re the perfect fit for: Image, video, text, data & lidar annotation Audio transcription Sentiment analysis Content moderation Product categorization Image segmentation iMerit also specializes in extraction and enrichment for Computer Vision , NLP , data labeling, and other technologies.

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Artificial Intelligence Artificial Intelligence Computer Vision Deep Learning 52