Unite.AI

JANUARY 30, 2025

Can you explain the core concept and what motivated you to tackle this specific challenge in AI and data analytics? illumex pioneered Generative Semantic Fabric – a platform that automates the creation of human and machine-readable organizational context and reasoning. Even defining it back then was a tough task.

Automation 147

Automation Metadata Explainability Data Scientist 147

Unite.AI

FEBRUARY 17, 2025

A financial crime investigator who once received large volumes of suspicious activity alerts requiring tedious investigation work manually gathering data across systems in order to weed out false positives and draft Suspicious Activity Reports (SARs) on the others.

Automation 147

Automation Responsible AI Generative AI AI Modeling 147

Unite.AI

JULY 31, 2023

AI algorithms learn from data; they identify patterns, make decisions, and generate predictions based on the information they're fed. Consequently, the quality of this training data is paramount. AI's Role in Improving Data Quality While the problem of data quality may seem daunting, there is hope.

Data Quality 130

Data Quality Algorithm Automation AI 130

Marktechpost

JULY 11, 2024

This agentic framework automates the creation of diverse and high-quality synthetic data using raw data sources like text documents and code files as seeds. These benchmarks indicate the substantial advancements made possible by AgentInstruct in synthetic data generation.

Data Quality 113

Data Quality Large Language Models AI Modeling Automation 113

IBM Journey to AI blog

MAY 9, 2023

But we’ve faced a paradoxical challenge: automation is labor intensive. It sounds like a joke, but it’s not, as anyone who has tried to solve business problems with AI may know. Traditional AI tools, while powerful, can be expensive, time-consuming, and difficult to use. But this is starting to change.

Data Platform 347

Data Platform Automation AI AI 347

Unite.AI

OCTOBER 30, 2023

Improves quality: The effectiveness of AI is significantly influenced by the quality of the data it processes. Training AI models with subpar data can lead to biased responses and undesirable outcomes. Improving AI quality: AI system effectiveness hinges on data quality.

DevOps 310

DevOps Software Development Automation Artificial Intelligence 310

Unite.AI

OCTOBER 22, 2024

With over 1,775 executives surveyed across 33 countries, the report uncovers how AI, automation, and sustainability are transforming the landscape of quality assurance. As AI technology progresses, organizations are being called to adopt new, innovative solutions for QE, especially as Generative AI (Gen AI) takes center stage.

Automation 130

Automation Data Quality AI Automation AI 130

Unite.AI

JUNE 17, 2024

Pascal Bornet is a pioneer in Intelligent Automation (IA) and the author of the best-seller book “ Intelligent Automation.” He is regularly ranked as one of the top 10 global experts in Artificial Intelligence and Automation. When did you first discover AI and realize how disruptive it would be?

Automation 147

Automation Artificial Intelligence Artificial Intelligence Generative AI 147

Marktechpost

MARCH 6, 2024

To overcome these issues, a team of researchers has presented Gen4Gen, a semi-automated method for creating datasets. This pipeline combines customized concepts with accompanying language explanations to create intricate compositions using generative models. Gen4Gen uses a series of AI models to generate datasets of superior quality.

Automation 133

Automation Artificial Intelligence Artificial Intelligence Data Quality 133

Unite.AI

NOVEMBER 27, 2024

According to McKinsey , by 2030, many companies will be approaching “ data ubiquity ,” where data is not only accessible but also embedded in every system, process, and decision point. For instance, healthcare organizations rely on AI-led platforms to predict patient needs with remarkable accuracy.

Business Intelligence 147

Business Intelligence AI AI Categorization 147

Unite.AI

FEBRUARY 21, 2025

Akeneo's Supplier Data Manager (SDM) is designed to streamline the collection, management, and enrichment of supplier-provided product information and assets by offering a user-friendly portal where suppliers can upload product data and media files, which are then automatically mapped to the retailer's and/or distributors data structure.

Natural Language Processing 147

Natural Language Processing NLP Categorization Algorithm 147

Unite.AI

JANUARY 20, 2025

Noah Nasser is the CEO of datma (formerly Omics Data Automation), a leading provider of federated Real-World Data platforms and related tools for analysis and visualization. By automating complex data queries, datma.FED accelerates access to high-quality, ready-to-use real-world data.

Automation 130

Automation Data Platform Data Quality Explainability 130

Unite.AI

DECEMBER 6, 2024

When framed in the context of the Intelligent Economy RAG flows are enabling access to information in ways that facilitate the human experience, saving time by automating and filtering data and information output that would otherwise require significant manual effort and time to be created.

AI 130

AI AI Data Platform LLM 130

Marktechpost

JUNE 15, 2024

Current methods to counteract model collapse involve several approaches, including using Reinforcement Learning with Human Feedback (RLHF), data curation, and prompt engineering. RLHF leverages human feedback to ensure the data quality used for training, thereby maintaining or enhancing model performance.

AI Modeling 130

AI Modeling Prompt Engineer Prompt Engineering Large Language Models 130

Unite.AI

JANUARY 9, 2024

AI represents a significant competitive advantage to the RCM function, and healthcare finance leaders who dismiss AI as hype will soon find their organizations left behind. Where AI Can Fall Short Truly autonomous AI in healthcare is a pipe dream. Building a strong data foundation. Continuous training.

Metadata 290

Metadata AI AI AI Tools 290

Unite.AI

JUNE 12, 2024

Key Insights AI Improves Efficiency and Productivity in IT Teams Automation and Efficiency : A significant portion of IT professionals (46%) believe that AI investments will lead to increased efficiency, making it the primary driver for adopting AI technologies.

Data Quality 147

Data Quality Automation AI AI 147

Pickl AI

JULY 24, 2024

Summary: Data quality is a fundamental aspect of Machine Learning. Poor-quality data leads to biased and unreliable models, while high-quality data enables accurate predictions and insights. What is Data Quality in Machine Learning?

Data Quality 52

Data Quality Machine Learning Automation Data Integration 52

Ehud Reiter

JANUARY 22, 2025

Unfortunately, digital interventions (including AI) almost always lose people over time; keeping people engaged and using a system for ten years is a huge challenge. Data : High-quality large medical data sets are very hard to get. But also, many doctors are not enthusiastic in general.

AI 118

AI AI Automation Data Quality 118

Unite.AI

SEPTEMBER 12, 2024

Much like a solid foundation is essential for a structure's stability, an AI model's effectiveness is fundamentally linked to the quality of the data it is built upon. In recent years, it has become increasingly evident that even the most advanced AI models are only as good as the data they are trained on.

Data Quality 162

Data Quality Data Scarcity AI AI 162

Unite.AI

SEPTEMBER 18, 2024

AI's integration into sales processes can significantly enhance efficiency, streamline workflows, and drive business success through insights derived from complex data. Automating Routine Tasks Sales professionals often spend a significant amount of time on repetitive tasks such as data entry, email management, and scheduling.

Automation 200

Automation AI AI Algorithm 200

Unite.AI

JANUARY 18, 2024

What are Large Vision Models (LVMs) Over the last few decades, the field of Artificial Intelligence (AI) has experienced rapid growth, resulting in significant changes to various aspects of human society and business operations. This is where the emergence of Large Vision Models (LVMs) becomes crucial.

Computer Vision 264

Computer Vision OpenAI Deep Learning Artificial Intelligence 264

Unite.AI

MAY 23, 2024

Taking stock of which data the company has available and identifying any blind spots can help build out data-gathering initiatives. From there, a brand will need to set data governance rules and implement frameworks for data quality assurance, privacy compliance, and security.

Machine Learning 269

Machine Learning AI AI AI Engineer 269

IBM Journey to AI blog

OCTOBER 12, 2023

The tasks behind efficient, responsible AI lifecycle management The continuous application of AI and the ability to benefit from its ongoing use require the persistent management of a dynamic and intricate AI lifecycle—and doing so efficiently and responsibly. Here’s what’s involved in making that happen.

Data Scientist 234

Data Scientist Metadata Explainability Responsible AI 234

IBM Journey to AI blog

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 130

Metadata Data Quality Data Discovery Data Scientist 130

Unite.AI

AUGUST 25, 2023

The variety and volume of data and the different types of data add additional complexity to an extremely complex real-world problem: how to optimize supply chain performance. Generative AI can take this a step further by supporting various functional areas of supply chain management.

Generative AI 245

Generative AI ESG AI AI 245

IBM Journey to AI blog

AUGUST 12, 2024

The integration of generative AI, particularly LLMs, offers transformative potential to automate compliance processes, detect anomalies, and provide comprehensive insights into regulatory requirements. Financial institutions are prioritizing the integration of AI to address pressing challenges and enhance their competitive edge.

Automation 159

Automation Generative AI AI AI 159

AWS Machine Learning Blog

NOVEMBER 15, 2024

If you are planning on using automated model evaluation for toxicity, start by defining what constitutes toxic content for your specific application. Automated evaluations come with curated datasets to choose from. Accuracy evaluation helps AI models produce reliable and correct outputs across various tasks and datasets.

Responsible AI 113

Responsible AI Prompt Engineering Prompt Engineer AI 113

Unite.AI

OCTOBER 25, 2024

AI SDRs (Sales Development Representatives) have emerged as sophisticated systems that automate and enhance the traditional role of human SDRs, handling everything from initial prospecting and lead qualification to scheduling appointments and managing follow-ups.

Automation 147

Automation Artificial Intelligence Artificial Intelligence AI 147

Unite.AI

OCTOBER 12, 2023

Another key takeaway from that experience is the crucial role that data plays, through quantity and quality, as a key driver of AI model capabilities and performance. Throughout my academic and professional experience prior to LXT, I have always worked directly with data.

Machine Learning 278

Machine Learning Deep Learning Conversational AI Data Quality 278

IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

ETL 234

ETL Metadata AI AI 234

IBM Journey to AI blog

DECEMBER 20, 2023

Artificial intelligence (AI) is a transformative force. The automation of tasks that traditionally relied on human intelligence has far-reaching implications, creating new opportunities for innovation and enabling businesses to reinvent their operations. Insufficient data How and where is your data, really?

AI Strategy 224

AI Strategy Artificial Intelligence Artificial Intelligence Machine Learning 224

IBM Journey to AI blog

AUGUST 23, 2023

The recent success of artificial intelligence based large language models has pushed the market to think more ambitiously about how AI could transform many enterprise processes. However, consumers and regulators have also become increasingly concerned with the safety of both their data and the AI models themselves.

Large Language Models 167

Large Language Models Data Discovery LLM AI 167

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. will, while 6.5%

Chatbots 130

Chatbots Natural Language Processing Data Quality Automation 130

IBM Journey to AI blog

JULY 3, 2024

By 2026, over 80% of enterprises will deploy AI APIs or generative AI applications. AI models and the data on which they’re trained and fine-tuned can elevate applications from generic to impactful, offering tangible value to customers and businesses.

Data Quality 112

Data Quality Metadata AI Business Intelligence 112

Marktechpost

AUGUST 27, 2024

The quantity and quality of data directly impact the efficacy and accuracy of AI models. Getting accurate and pertinent data is one of the biggest challenges in the development of AI. LLMs require current, high-quality internet data to address certain issues. How Does Saldor Work?

Data Extraction 101

Data Extraction Automation Linked Data Artificial Intelligence 101

Unite.AI

JUNE 10, 2024

The grid is complex, and so much so that AI in itself cannot learn about the complex power flows and operational processes that exist in the grid space. What specific challenges in grid management does ThinkLabs AI aim to solve? How does ThinkLabs AI ensure the reliability and accuracy of its AI models in real-world scenarios?

Continuous Learning 130

Continuous Learning Automation Data Quality AI 130

Aiiot Talk

APRIL 30, 2024

For example, AI-powered image processing can identify patterns and subtle anomalies that may be invisible to the human eye. Automated Defect Detection AI provides a viable framework for automatically detecting specific defects like corrosion and deposits by analyzing test images. AI-Driven NDT in the Industry 4.0

Automation 130

Automation Algorithm Machine Learning ML 130