IBM Journey to AI blog

JUNE 27, 2024

Data lineage becomes even more important as the need to provide “Explainability” in models is required by regulatory bodies. Enterprise data is often complex, diverse and scattered across various repositories, making it difficult to integrate into gen AI solutions.

Generative AI 305

Generative AI Data Ingestion Large Language Models Data Discovery 305

Unite.AI

DECEMBER 17, 2024

Unlearn has been a pioneer in integrating digital twins into clinical trials. Could you briefly explain to our readers how digital twin technology is used in this context? In clinical trials, Unlearns AI models generate an individual digital twin for each patient before they are randomly assigned to the trial.

Artificial Intelligence 147

Artificial Intelligence Artificial Intelligence Machine Learning Explainability 147

Marktechpost

MARCH 22, 2024

Users can take advantage of DATALORE’s data governance, data integration, and machine learning services, among others, on cloud computing platforms like Amazon Web Services, Microsoft Azure, and Google Cloud. This improves DATALORE’s efficiency by avoiding the costly investigation of search spaces.

Machine Learning 136

Machine Learning Explainability Categorization ETL 136

IBM Journey to AI blog

OCTOBER 12, 2023

Security and privacy —When all data scientists and AI models are given access to data through a single point of entry, data integrity and security are improved. Explainable AI — Explainable AI is achieved when an organization can confidently and clearly state what data an AI model used to perform its tasks.

Data Scientist 234

Data Scientist Metadata Explainability Responsible AI 234

Unite.AI

JULY 19, 2024

Guardrail AI Image source Guardrail AI is designed to ensure data integrity and compliance through advanced AI auditing frameworks. Data integrity auditing techniques to identify biases. Examples include text, code, legal documents, or healthcare data. Effectiveness can vary across different domains.

LLM 279

LLM AI AI Data Quality 279

Unite.AI

JUNE 13, 2024

With the rise of generative AI, our customers wanted AI solutions that could interact with their data conversationally. A significant challenge in AI applications today is explainability. How does the knowledge graph architecture of the AI Context Engine enhance the accuracy and explainability of LLMs compared to SQL databases alone?

Explainability 130

Explainability Data Integration Metadata Generative AI 130

Unite.AI

MARCH 18, 2024

Implementing Preventative Measures To safeguard AI models from the pitfalls of AI-generated content, a strategic approach to maintaining data integrity is essential. Ethical AI Practices : This requires committing to ethical AI development, ensuring fairness, privacy, and responsibility in data use and model training.

Data Integration 189

Data Integration AI AI Generative AI 189

AWS Machine Learning Blog

MARCH 18, 2025

Extraction of relevant data points for electronic health records (EHRs) and clinical trial databases. Data integration and reporting The extracted insights and recommendations are integrated into the relevant clinical trial management systems, EHRs, and reporting mechanisms.

LLM 111

LLM NLP Data Integration AI 111

PyImageSearch

JANUARY 20, 2025

Lossy compression is suitable for scenarios where reduced file size is more critical than perfect quality, while lossless compression is essential when data integrity and accuracy cannot be compromised. Huffman encoding is a widely used lossless data compression algorithm. What Is Huffman Encoding? Thats not the case.

Computer Vision 106

Computer Vision Deep Learning Explainability Algorithm 106

AssemblyAI

JANUARY 5, 2024

Join Us On Discord AssemblyAI Integrations Check out our new  integrations  page for all the latest AssemblyAI integrations and start building with your favorite tools and services. LlamaIndex Integration : With LlamaIndex, you can easily store and index your data, and then use them with LLMs to build applications.

Large Language Models 147

Large Language Models Explainability Python Visual AI 147

PyImageSearch

JANUARY 6, 2025

Summary In this blog post, we delve into the essential task of identifying anomalies within datasets, a critical step for improving data integrity and analysis accuracy. We start by defining what an outlier is and explain its importance in various fields (e.g., finance, healthcare, and quality control).

Python 113

Python Explainability Computer Vision Deep Learning 113

Pickl AI

OCTOBER 17, 2024

Summary: The ETL process, which consists of data extraction, transformation, and loading, is vital for effective data management. Following best practices and using suitable tools enhances data integrity and quality, supporting informed decision-making. Introduction The ETL process is crucial in modern data management.

ETL 52

ETL Explainability Data Integration Data Extraction 52

Flipboard

DECEMBER 3, 2024

By integrating multiple data sources and explainable research results, including weather patterns and soil data, the agent delivers personalized and context-aware recommendations.

Generative AI 150

Generative AI Metadata Machine Learning Natural Language Processing 150

Unite.AI

DECEMBER 2, 2024

Think of it like a system of record that provides a permanent, shareable record of your security decision-making process – something essential for explaining to your boss why you did something when it comes to audits, compliance reviews, and the incident response process. But more importantly, we've built our platform to be adaptable.

Explainability 173

Explainability Data Integration AI AI 173

Unite.AI

MAY 13, 2024

For instance, when explaining a scientific concept, the AI can provide relevant diagrams or images to help students grasp complex ideas more easily. This integration facilitates smoother collaboration and enhances productivity. Concerns Real-time collaboration features can raise security and data integrity concerns.

ChatGPT 189

ChatGPT OpenAI Conversational AI Explainability 189

ODSC - Open Data Science

MARCH 31, 2025

Gen AI in Asset Management: Use Cases and Lessons from Building an Industry-Specific Copilot Yu Yu, PhD, Director of Data Science at BlackRock Explore how a leading firm in asset management built a specialized generative AI copilot for its domain.

Software Engineer 52

Software Engineer AI AI Large Language Models 52

IBM Journey to AI blog

AUGUST 4, 2023

Here are some advantages—and potential risk—to consider during this organizational change: Productivity Many companies look to data democratization to eliminate silos and get more out of their data across departments. Security Data security is a high priority.

Machine Learning 183

Machine Learning Metadata Automation AI 183

AWS Machine Learning Blog

MARCH 6, 2025

It simplifies data integration from various sources and provides tools for data indexing, engines, agents, and application integrations. Diagram Architecture The following diagram is a high-level reference architecture that explains how you can evaluate the RAG solution with RAGAS or LlamaIndex.

LLM 112

LLM Generative AI ML Prompt Engineer 112

Unite.AI

JULY 5, 2024

Transparent, explainable AI models are necessary for informed decision-making. Comprehensive data collection is essential, including information such as socioeconomic status, education and environmental factors. This data provides insights into the social factors that influence patient health.

Data Integration 147

Data Integration Data Quality Algorithm AI Modeling 147

IBM Journey to AI blog

SEPTEMBER 23, 2024

. “It all starts with our upstream collaboration on data—connecting watsonx.data with Salesforce Data Cloud. ” Data integration fuels AI agents The partnership also plans to incorporate AI agents into Slack, Salesforce’s workplace communication platform.

Explainability 100

Explainability AI AI Data Quality 100

Pickl AI

JULY 19, 2023

In this article, we will delve into the concept of data hygiene, its best practices, and key features, while also exploring the benefits it offers to businesses. Comprehensive data cleansing and enrichment options. Scalable for handling enterprise-level data. Offers data quality monitoring and reporting.

Explainability 40

Explainability Data Quality Data Integration Automation 40

Unite.AI

JANUARY 29, 2025

Reliability is also paramountAI systems often support mission-critical tasks, and even minor downtime or data loss can lead to significant disruptions or flawed AI outputs. Security and data integrity further complicate AI deployments.

AI Strategy 130

AI Strategy Automation AI AI 130

Pickl AI

JUNE 7, 2024

Encapsulation safeguards data integrity by restricting direct access to an object’s data and methods. Encapsulate Data: To safeguard data integrity, encapsulate data within classes and control access through well-defined interfaces and access modifiers.

Python 40

Python Explainability Software Development Data Integration 40

Pickl AI

JANUARY 10, 2025

This article will analyse the functions of artificial intelligence and machine learning and how they can affect the data backup process. Still, we will discuss the importance of backups for the average user and explain the universal benefits of data management that AI improves. What is the Importance of Data Backup?

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Automation AI 52

IBM Journey to AI blog

JUNE 28, 2023

Processing terabytes or even petabytes of increasing complex omics data generated by NGS platforms has necessitated development of omics informatics. gene expression; microbiome data) and any tabular data (e.g., clinical) using a range of machine learning models.

Data Analysis 186

Data Analysis Data Scientist Explainable AI Machine Learning 186

Marktechpost

JANUARY 27, 2024

Techniques like data augmentation and counterfactual training can also help address biases and misinformation present in existing data. This could involve creating interpretable models or developing tools explaining the generated text’s reasoning.

LLM 141

LLM Large Language Models Explainability Prompt Engineer 141

Marktechpost

MAY 8, 2024

Conclusion: In the realm of autonomous driving, several open challenges persist, all of which can be addressed with the help of Deep Learning and AI: Perception: Deep learning enhances object detection and recognition accuracy, but future systems should aim for increased detail recognition and improved camera and LiDAR data integration.

Deep Learning 122

Deep Learning Neural Network Data Scarcity Natural Language Processing 122

O'Reilly Media

OCTOBER 11, 2022

So from the start, we have a data integration problem compounded with a compliance problem. An AI project that doesn’t address data integration and governance (including compliance) is bound to fail, regardless of how good your AI technology might be. Some of these tasks have been automated, but many aren’t.

Automation 141

Automation Data Integration Explainability AI 141

AWS Machine Learning Blog

SEPTEMBER 28, 2023

This reduces the average model training duration from 186 to 73 minutes and the average prediction time from 33 to 18 minutes for a typical batch of 750 time series with data size up to 100 MB. Previously, introducing incremental data required retraining the entire model, which was time-consuming and caused operational delays.

Machine Learning 118

Machine Learning ML Explainability Automation 118

Marktechpost

MAY 12, 2024

SEON SEON is an artificial intelligence fraud protection platform that uses real-time digital, social, phone, email, IP, and device data to improve risk judgments. It is based on adjustable and explainable AI technology. CorgiAI CorgiAI is a fraud detection and prevention tool designed to increase income and reduce losses due to fraud.

AI Tools 103

AI Tools Neural Network Artificial Intelligence Artificial Intelligence 103

Unite.AI

OCTOBER 10, 2024

Can you explain how DecisionNext leverages AI and machine learning to improve commodity price and supply forecasting? DecisionNext uses artificial intelligence and machine learning to consume thousands of data sets and find historical and current relationships between key factors.

Machine Learning 147

Machine Learning Large Language Models Robotics Artificial Intelligence 147

AWS Machine Learning Blog

DECEMBER 4, 2023

In this post, we explain how we built an end-to-end product category prediction pipeline to help commercial teams by using Amazon SageMaker and AWS Batch , reducing model training duration by 90%. An important aspect of our strategy has been the use of SageMaker and AWS Batch to refine pre-trained BERT models for seven different languages.

BERT 121

BERT Auto-complete Data Scientist Machine Learning 121

The MLOps Blog

JUNE 27, 2023

This includes features for model explainability, fairness assessment, privacy preservation, and compliance tracking. Integration with ML tools and libraries: Provide you with flexibility and extensibility. LakeFS LakeFS is an open-source platform that provides data lake versioning and management capabilities.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

MARCH 14, 2025

Now that weve explained the key features, we examine how these capabilities come together in a practical implementation. Feature overview The Amazon Bedrock Knowledge Bases RAG evaluation feature provides a comprehensive, end-to-end solution for assessing and optimizing RAG applications.

Generative AI 95

Generative AI Responsible AI Automation LLM 95

Pickl AI

APRIL 29, 2024

A DBMS is a software application that helps create, store, manage, and retrieve data in a structured and efficient way. It acts as a central repository for data, ensuring data integrity, security, and accessibility. DELETE : Removes data from a table. Explain the concept of normalization in DBMS.

Data Integration 52

Data Integration Explainability Categorization Big Data 52

John Snow Labs

SEPTEMBER 26, 2024

Data integration has been an enormous challenge in healthcare for decades. Building this unified patient view from multi-modal source data. Explaining results with full traceability. The post Turning Straw into Gold: Building Patient Journeys from Raw Medical Data appeared first on John Snow Labs.

Explainability 52

Explainability Data Integration Large Language Models AI 52

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 56

Natural Language Processing Machine Learning AI AI 56