Unite.AI

JULY 19, 2024

Versatile use cases for hallucination detection in RAG, Chatbot, Summarization applications. It is designed to automatically detect and fix data issues that can negatively impact the performance of machine learning models, including language models prone to hallucinations. Automatically detects mislabeled data. Cost-effective.

LLM 274

LLM AI AI Data Quality 274

AI Weekly

MAY 30, 2024

[Download now] rws.com In The News OpenAI forms safety council as it trains latest AI model OpenAI says it is setting up a safety and security committee and has begun training a new AI model to supplant the GPT-4 system that underpins its ChatGPT chatbot. arxiv.org Sponsor Need Data to Train AI?

Robotics 261

Robotics AI AI Artificial Intelligence 261

IBM Journey to AI blog

JULY 30, 2024

Start by identifying all potential data sources across your organization, including structured databases. As a result of this, your gen AI initiatives are built on a solid foundation of trusted, governed data. Remember, the quality of your data directly impacts the performance of your gen AI models.

Generative AI 266

Generative AI Data Scientist Software Engineer AI 266

Chatbots Life

MAY 19, 2023

A chatbot is a technological genie that uses intelligent automation, ML, and NLP to automate tasks. Chatbots are transforming the IT service desk's workplace support and service delivery procedures to make them more efficient and successful in serving employees. Chatbots connect employees to support agents only when it is needed.

Chatbots 69

Chatbots Automation Auto-complete NLP 69

Unite.AI

DECEMBER 13, 2024

At a recent Gartner event, Rita Sallam, distinguished vice-president analyst, said that at least 30% of GenAI projects will be dropped after POCs by the end of 2025 due to such issues as poor data quality, insufficient risk controls, fast-growing costs, or an inability to realize desired business value.

Chatbots 130

Chatbots Natural Language Processing Data Quality Automation 130

Towards AI

FEBRUARY 17, 2025

Some of its key advantages include: Less hallucinations since the model is forced to rely on actual data; Transparent (it cites sources); Easy to adapt to changing data environment without modifying the model. Data Quality Problem: Biased or outdated training data affects the output. balance, outliers).

Data Drift 95

Data Drift LLM Automation Metadata 95

AssemblyAI

AUGUST 3, 2023

From the large-scale proliferation of biased or false information to risks of psychological distress for chatbot users, the potential for misuse of language models is a subject of intense debate. In applications such as chatbot assistants or search, where accuracy is critical, RLHF certainly proves advantageous.

LLM 238

LLM ChatGPT Chatbots OpenAI 238

Marktechpost

SEPTEMBER 30, 2023

InternLM-20B represents a significant leap forward in language model architecture and training data quality. This makes it a versatile tool for various NLP applications, from chatbots to language translation and document summarization.

Artificial Intelligence 122

Artificial Intelligence Artificial Intelligence Natural Language Processing NLP 122

Flipboard

FEBRUARY 19, 2025

In the age of generative artificial intelligence (AI), data isnt just kingits the entire kingdom. Focus should be placed on data quality through robust validation and consistent formatting. Regular security assessments and compliance monitoring are essential, as is continuous performance tracking and optimization.

Responsible AI 79

Responsible AI Natural Language Processing Explainability Large Language Models 79

IBM Journey to AI blog

JULY 3, 2024

Establishing a foundation of trust: Data quality and governance for enterprise AI As organizations increasingly rely on artificial intelligence (AI) to drive critical decision-making, the importance of data quality and governance cannot be overstated.

Data Quality 112

Data Quality Metadata Business Intelligence AI 112

IBM Journey to AI blog

SEPTEMBER 3, 2024

Hay argues that part of the problem is that the media often conflates gen AI with a narrower application of LLM-powered chatbots such as ChatGPT, which might indeed not be equipped to solve every problem that enterprises face. In this context, data quality often outweighs quantity.

Generative AI 308

Generative AI LLM Large Language Models AI 308

TheSequence

SEPTEMBER 13, 2023

Currently, he is leading the LMSYS efforts and open-source projects including Vicuna and Chatbot Arena. Chatbot Arena and MT-bench ), and systems (e.g., We emphasize the importance of data quality, so we find the best data source – user shared conversations on ShareGPT. I am a Ph.D. FastChat , Alpa ).

Chatbots 64

Chatbots LLM Large Language Models ChatGPT 64

AWS Machine Learning Blog

DECEMBER 11, 2024

Document upload When users need to provide context of their own, the chatbot supports uploading multiple documents during a conversation. We deliver our chatbot experience through a custom web frontend, as well as through a Slack application.

Generative AI 90

Generative AI Data Ingestion Chatbots Software Engineer 90

IBM Journey to AI blog

AUGUST 23, 2023

Risks of training LLM models on sensitive data Large language models can be trained on proprietary data to fulfill specific enterprise use cases. For example, a company could take ChatGPT and create a private model that is trained on the company’s CRM sales data.

Large Language Models 167

Large Language Models Data Discovery LLM AI 167

Pickl AI

MARCH 4, 2025

They can process vast amounts of data in real time and interpret complex scenarios to make decisions aligned with predefined objectives. For example, A customer service AI chatbot that submits claims based on customer information. For example, a chatbot that understands user sentiment and intent through NLP.

Natural Language Processing 52

Natural Language Processing NLP Automation Artificial Intelligence 52

Mlearning.ai

SEPTEMBER 2, 2023

Medical Diagnostic Assistant Chatbot using Hugging Face pre-trained models, Python and Streamlit. Chatbots, like helpful computer programs, can talk to people and answer their questions anytime, anywhere. So, the article focuses on building a medical diagnostic assistant chatbot using pre-trained models from Hugging Face.

Chatbots 52

Chatbots Python OpenAI Data Quality 52

ODSC - Open Data Science

FEBRUARY 17, 2025

Common RAG applications extend beyond financial services to areas such as chatbots, code assistants, medical record analysis, and literature reviews. Key Takeaways Data quality is critical for effective RAG implementation. Content Generation : Uses the retrieved chunks to generate a precise and contextually accurateanswer.

Metadata 52

Metadata Machine Learning Data Scientist Data Quality 52

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. Acquiring a significant volume of domain-specific data can be challenging, especially if the data is niche or sensitive.

LLM 98

LLM Large Language Models Chatbots Natural Language Processing 98

Marktechpost

NOVEMBER 20, 2024

Phonetic Annotation: Labelling punctuation and text pauses for chatbot training is known as phonetic annotation. Disadvantages of Data Labeling Time and Cost: Manual labeling requires a lot of resources. Human error: Data quality is impacted by mislabeling brought on by bias or cognitive exhaustion.

Natural Language Processing 103

Natural Language Processing Computer Vision Machine Learning NLP 103

AWS Machine Learning Blog

FEBRUARY 18, 2025

The following sections further explain the main components of the solution: ETL pipelines to transform the log data, agentic RAG implementation, and the chat application. Creating ETL pipelines to transform log data Preparing your data to provide quality results is the first step in an AI project.

Generative AI 69

Generative AI ETL LLM AI 69

IBM Journey to AI blog

AUGUST 12, 2024

The versatility of LLMs enables their application in diverse areas such as automated report generation, customer service chatbots, and compliance document analysis. RAG implementations involve combining LLMs with external data sources to enhance their knowledge and decision-making capabilities.

Automation 159

Automation Generative AI AI AI 159

Marktechpost

NOVEMBER 10, 2023

Text analysis, translation, chatbots, and sentiment analysis are just some of its many applications. Recent NLP research has focused on improving few-shot learning (FSL) methods in response to data insufficiency challenges. NLP, or Natural Language Processing, is a field of AI focusing on human-computer interaction using language.

BERT 126

BERT ChatGPT Large Language Models NLP 126

Marktechpost

FEBRUARY 23, 2025

Common Applications: Real-time monitoring systems Basic customer service chatbots DigitalOcean explains that while these agents may not handle complex decision-making, their speed and simplicity are well-suited for specific uses. Data Quality and Bias: The effectiveness of AI agents depends on the quality of the data they are trained on.

Natural Language Processing 54

Natural Language Processing Machine Learning AI AI 54

Flipboard

JULY 4, 2023

The well-known chatbot called ChatGPT, based on GPT architecture and developed by OpenAI, imitates humans by generating accurate and creative content, answering questions, summarizing massive textual paragraphs, and language translation. From education and finance to healthcare and media, LLMs are contributing to almost every domain.

Large Language Models 138

Large Language Models Machine Learning Natural Language Processing BERT 138

Becoming Human

MAY 19, 2023

Chatathon by Chatbot Conference Top 6 AI in Banking Use Cases 1. AI Chatbots The banking sector has started to use AI and ML (machine learning) significantly, with chatbots being one of the most popular applications. Banks are using chatbots to provide a better customer experience and reduce costs.

Chatbots 84

Chatbots AI Chatbots Natural Language Processing Artificial Intelligence 84

Pickl AI

MARCH 7, 2025

Real-time data processing helps businesses react faster to market trends and risks. Managing data quality is crucial to avoid misleading insights and poor decisions. Advanced tools like AI and cloud computing help tackle Big Data challenges effectively. Understanding the 4 Vs of Big Data Big Data is all around us.

Big Data 52

Big Data Machine Learning Data Quality Data Science 52

O'Reilly Media

NOVEMBER 19, 2024

A generalized, unbundled workflow A more accountable approach to GraphRAG is to unbundle the process of knowledge graph construction, paying special attention to data quality.

LLM 125

LLM NLP Hybrid AI Large Language Models 125

Unite.AI

JUNE 13, 2024

Across fields such as Natural Language Processing (NLP) , computer vision , and recommendation systems , AI workflows power important applications like chatbots, sentiment analysis , image recognition, and personalized content delivery. This foundational step requires clean and well-structured data to facilitate accurate model training.

Natural Language Processing 144

Natural Language Processing Robotics Algorithm AI 144

Marktechpost

MARCH 13, 2024

These are based on an evolved transformer architecture that’s been fine-tuned with a keen eye on data quality, a factor that significantly boosts performance across various benchmarks. The model series includes language-specific models capable of processing visual information alongside text.

Natural Language Processing 103

Natural Language Processing Computer Vision Artificial Intelligence Artificial Intelligence 103

Towards AI

APRIL 2, 2024

This can come from algorithmic improvements and more focus on pretraining data quality, such as the new open-source DBRX model from Databricks. X’s Grok Chatbot Will Soon Get an Upgraded Model, Grok-1.5 This new model is expected to power the Grok chatbot on X. has announced an upgraded version of its AI model, Grok-1.5.

LLM 103

LLM OpenAI Explainable AI AI 103

Unite.AI

JANUARY 23, 2025

Part of the reason for this is that today, the most prominent AI user interfaces are based on natural language delivered through a chatbot paradigm. In a cross-country and industry survey of 1,000 CxOs and senior executives, BCG found that 74% of companies struggle to realize and scale value in their AI investments.

Responsible AI 111

Responsible AI AI Tools Data Analysis Data Quality 111

Marktechpost

DECEMBER 8, 2024

Structured data is important in this process, as it provides a clear and organized framework for the AI to learn from, unlike messy or unstructured data, which can lead to ambiguities. Employ Data Templates With data quality, implementing data templates offers another layer of control and precision.

Prompt Engineer 111

Prompt Engineer Prompt Engineering Large Language Models LLM 111

How to Learn Machine Learning

OCTOBER 10, 2024

This article explores real-world cases where poor-quality data led to model failures, and what we can learn from these experiences. By the end, you’ll see why investing in quality data is not just a good idea, but a necessity. Why Does Data Quality Matter? The outcome?

Machine Learning 52

Machine Learning Data Quality Algorithm Chatbots 52

Unite.AI

JUNE 17, 2024

For instance, many banks now use AI-powered chatbots to handle customer inquiries, providing 24/7 support and freeing up human agents to focus on more complex issues. These chatbots can understand natural language, access account information, and even make personalized recommendations, greatly enhancing the customer experience.

Automation 144

Automation Artificial Intelligence Artificial Intelligence Generative AI 144

Marktechpost

AUGUST 10, 2024

Moderate-Risk AI: This category includes systems like chatbots and AI-generated content, which must clearly inform users they’re interacting with AI. They must meet strict standards for accuracy, security, and data quality, with ongoing human oversight. Developers can choose to follow voluntary guidelines for transparency.

Artificial Intelligence 132

Artificial Intelligence Artificial Intelligence AI AI 132

Towards AI

FEBRUARY 20, 2024

If you want an overview of the Machine Learning Process, it can be categorized into 3 wide buckets: Collection of Data: Collection of Relevant data is key for building a Machine learning model. It isn't easy to collect a good amount of quality data. You need to know two basic terminologies here, Features and Labels.

Machine Learning 109

Machine Learning ML Neural Network Algorithm 109

NVIDIA

JULY 13, 2023

On that day, OpenAI released ChatGPT, the most advanced artificial intelligence chatbot ever developed. Financial Transformers , or “FinFormers,” can learn context and understand the meaning of unstructured financial data. A watershed moment on Nov.

Generative AI 98

Generative AI AI AI Natural Language Processing 98