Unite.AI

FEBRUARY 20, 2025

The tool is not just about automating tasks; its purpose is to help researchers generate insights that would take human teams months or even years to formulate. By processing this vast amount of data, the tool not only saves time but also ensures that its outputs are grounded in evidence-based research.

Machine Learning 124

Machine Learning AI AI Natural Language Processing 124

AWS Machine Learning Blog

AUGUST 7, 2024

Innovations in artificial intelligence (AI) and machine learning (ML) are causing organizations to take a fresh look at the possibilities these technologies can offer. Automating these checks allows them to be repeated regularly and consistently rather than organizations having to rely on infrequent manual point- in-time checks.

Automation 113

Automation Machine Learning ML Explainability 113

Marktechpost

APRIL 24, 2024

Automation in modern industries often involves repetitive tasks, but the challenge arises when tasks require flexibility and spontaneous decision-making. Traditional robotic process automation (RPA) systems are designed for static, routine activities, falling short when unpredictability is introduced. Researchers at J.P.

Machine Learning 139

Machine Learning AI Researcher AI Research Large Language Models 139

Unite.AI

DECEMBER 27, 2024

They mitigate issues like overfitting and enhance the transferability of insights to unseen data, ultimately producing results that align closely with user expectations. This emphasis on data quality has profound implications. Data validation frameworks play a crucial role in maintaining dataset integrity over time.

Data Quality 130

Data Quality Data Drift Explainability Big Data 130

IBM Journey to AI blog

JUNE 27, 2024

This requires traditional capabilities like encryption, anonymization and tokenization, but also creating capabilities to automatically classify data (sensitivity, taxonomy alignment) by using machine learning.

Generative AI 305

Generative AI Data Ingestion Large Language Models Data Discovery 305

ODSC - Open Data Science

APRIL 28, 2023

Be sure to check out her talk, “ Power trusted AI/ML Outcomes with Data Integrity ,” there! Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation.

Data Integration 98

Data Integration ML ESG Big Data 98

IBM Journey to AI blog

JUNE 28, 2024

In addition to these capabilities, generative AI can revolutionize drive tests, optimize network resource allocation, automate fault detection, optimize truck rolls and enhance customer experience through personalized services. This aids in better data integration and utilization in the upper layers.

Generative AI 216

Generative AI Automation Large Language Models AI 216

IBM Journey to AI blog

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

Machine Learning 225

Machine Learning Automation AI AI 225

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. It's true that the specter of job losses due to AI automation is a real fear for many.

Automation 147

Automation Artificial Intelligence Artificial Intelligence Generative AI 147

IBM Journey to AI blog

JUNE 29, 2023

Data integration and analytics IBP relies on the integration of data from different sources and systems. This may involve consolidating data from enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, supply chain management systems, and other relevant sources.

Data Integration 237

Data Integration Business Intelligence ETL Automation 237

Unite.AI

SEPTEMBER 21, 2023

AI's real-time data analysis and decision-making capabilities expand blockchain’s authenticity, augmentation, and automation capabilities. For instance, Optimizing automation of supply chain processes by embedding AI in smart contracts. Addressing the challenges of AI ethics by ensuring the authenticity of data.

Convolutional Neural Networks 289

Convolutional Neural Networks Neural Network Artificial Intelligence Artificial Intelligence 289

AWS Machine Learning Blog

MAY 1, 2024

This post demonstrates how to build a chatbot using Amazon Bedrock including Agents for Amazon Bedrock and Knowledge Bases for Amazon Bedrock , within an automated solution. Solution overview In this post, we use publicly available data, encompassing both unstructured and structured formats, to showcase our entirely automated chatbot system.

Chatbots 121

Chatbots Automation Machine Learning DevOps 121

IBM Journey to AI blog

NOVEMBER 14, 2023

Serve: Data products are discoverable and consumed as services, typically via a platform. Serve : Build cloud services for data products through automation and platform service technology so they can be operated securely at global scale. Doing so can increase the quality of data integrated into data products.

ESG 315

ESG Generative AI AI AI 315

NVIDIA

FEBRUARY 28, 2025

Accelerated AI-Powered Cybersecurity Modern cybersecurity relies heavily on AI for predictive analytics and automated threat mitigation. They offer: Faster AI model training : GPUs reduce the time required to train machine learning models for tasks like fraud detection or phishing prevention.

Algorithm 99

Algorithm Automation AI AI 99

IBM Journey to AI blog

JANUARY 15, 2024

Digital transformation trends that drive a competitive advantage Trend: Artificial intelligence and machine learning We’re entering year two of widespread adoption of generative AI tools. But organizations still need humans to decide what actions to take based on what the ML-analyzed data shows.

Machine Learning 219

Machine Learning Automation DevOps Artificial Intelligence 219

Flipboard

FEBRUARY 11, 2025

In this post, we propose an end-to-end solution using Amazon Q Business to address similar enterprise data challenges, showcasing how it can streamline operations and enhance customer service across various industries. The Process Data Lambda function redacts sensitive data through Amazon Comprehend.

Data Ingestion 155

Data Ingestion Metadata Machine Learning Generative AI 155

Unite.AI

MAY 23, 2024

The pitch for AI solutions to be utilized in a myriad of different ways, from machine learning tools that bolster customer service to better personalization and product recommendation engines for customers to logistics and supply chain optimization tools, is a strong one.

Machine Learning 269

Machine Learning AI AI AI Engineer 269

Unite.AI

JANUARY 29, 2025

Dr. Sood is interested in Artificial Intelligence (AI), cloud security, malware automation and analysis, application security, and secure software design. This exposure naturally led me to delve deeper into cybersecurity, where I recognized the critical importance of safeguarding data and networks in an increasingly interconnected world.

AI Strategy 130

AI Strategy Automation AI AI 130

Marktechpost

JUNE 13, 2024

Data scientists often spend up to 80% of their time on data engineering in data science projects. Objective of Data Engineering: The main goal is to transform raw data into structured data suitable for downstream tasks such as machine learning.

ETL 128

ETL Machine Learning Data Ingestion Big Data 128

IBM Journey to AI blog

SEPTEMBER 5, 2024

Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success. Emerging technologies and trends, such as machine learning (ML), artificial intelligence (AI), automation and generative AI (gen AI), all rely on good data quality.

Metadata 188

Metadata Data Quality Auto-classification DevOps 188

Unite.AI

AUGUST 28, 2024

Furthermore, while machine learning (ML) algorithms can offer personalized treatment recommendations, the lack of transparency in these algorithms complicates individual accountability. Investing in modern data integration tools, such as Astera and Fivetran , with built-in data quality features will also help.

Data Quality 317

Data Quality Algorithm AI AI 317

IBM Journey to AI blog

DECEMBER 4, 2023

Generative AI could also help maintenance, repair and overhaul (MRO) technicians by enabling them to retrieve relevant information more effectively for repairs, or by automating the creation of parts and equipment orders so repair or maintenance can start as soon as a plane lands.

Generative AI 213

Generative AI AI AI Automation 213

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 79

LLM NLP Data Integration AI 79

IBM Journey to AI blog

NOVEMBER 10, 2023

Ring 3 uses the capabilities of Ring 1 and Ring 2, including the data integration capabilities of the platform for terminology standardization and person matching. The introduction of Generative AI offers to take this solution pattern a notch further, particularly with its ability to better handle unstructured data.

Natural Language Processing 295

Natural Language Processing AI AI Data Platform 295

AWS Machine Learning Blog

MARCH 14, 2025

Although automated metrics are fast and cost-effective, they can only evaluate the correctness of an AI response, without capturing other evaluation dimensions or providing explanations of why an answer is problematic. Human evaluation, although thorough, is time-consuming and expensive at scale.

Generative AI 87

Generative AI Responsible AI Automation LLM 87

ODSC - Open Data Science

JUNE 6, 2023

Be sure to check out their talk, “ Getting Up to Speed on Real-Time Machine Learning ,” there! The benefits of real-time machine learning are becoming increasingly apparent. This is due to a deep disconnect between data engineering and data science practices.

Machine Learning 90

Machine Learning ML Engineer Neural Network Data Science 90

AWS Machine Learning Blog

MARCH 17, 2025

Healthcare agents can integrate LLM models and call external functions or APIs through a series of steps: natural language input processing , self-correction, chain of thought, function or API calling through an integration layer, data integration and processing, and persona adoption.

LLM 97

LLM Natural Language Processing ML Computer Vision 97

Aiiot Talk

JANUARY 17, 2024

Machine learning may uncover a spike in specific respiratory ailments, allowing biopharmaceuticals to prioritize them as the most pressing concerns. “In It optimizes processes by reducing human error and automating repetitive manual tasks like scanning data, which reveals patterns in test samples for more high-value adjustments.

Data Integration 148

Data Integration Robotics Machine Learning Computer Vision 148

IBM Journey to AI blog

DECEMBER 11, 2023

Kubernetes , Docker Swarm ) to automate the deployment of apps across all clouds. This centralized management system makes implementing security measures like encryption , automation, access control and endpoint data security easier. This redundancy prevents data loss if one of the backups is comprised.

DevOps 308

DevOps Automation Generative AI Big Data 308

Unite.AI

SEPTEMBER 24, 2024

The company offers a comprehensive suite of tools designed to optimize various aspects of supply chain operations, from demand forecasting and inventory management to transportation and warehouse automation. At the core of Blue Yonder's offerings is its innovative approach to supply chain planning.

AI Tools 162

AI Tools Natural Language Processing Machine Learning Artificial Intelligence 162

Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Learning these tools is crucial for building scalable data pipelines. There are some differences between these two terms.

Big Data 52

Big Data Automation Data Science Python 52

The MLOps Blog

JUNE 27, 2023

How to evaluate MLOps tools and platforms Like every software solution, evaluating MLOps (Machine Learning Operations) tools and platforms can be a complex task as it requires consideration of varying factors. This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

Pickl AI

OCTOBER 15, 2024

Summary: Selecting the right ETL platform is vital for efficient data integration. Consider your business needs, compare features, and evaluate costs to enhance data accuracy and operational efficiency. Introduction In today’s data-driven world, businesses rely heavily on ETL platforms to streamline data integration processes.

ETL 52

ETL Data Integration Automation Data Quality 52

Marktechpost

FEBRUARY 23, 2025

Defining AI Agents At its simplest, an AI agent is an autonomous software entity capable of perceiving its surroundings, processing data, and taking action to achieve specified goals. Microsoft has described how such systems help automate routine tasks, allowing human employees to focus on more complex challenges.

Natural Language Processing 56

Natural Language Processing Machine Learning AI AI 56

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? What is Data Quality in Machine Learning?

Data Quality 52

Data Quality Machine Learning Automation Data Integration 52

IBM Journey to AI blog

JANUARY 29, 2024

By using AI, automation, and hybrid cloud, among others, organizations can drive intelligent workflows, streamline supply chain management, and speed up decision-making. Companies are becoming more reliant on data analytics and automation to enable profitability and customer satisfaction. Why digital transformation?

Automation 213

Automation Artificial Intelligence Artificial Intelligence Big Data 213

AWS Machine Learning Blog

MARCH 10, 2025

Automated deployment strategy Our GitOps-embedded framework streamlines the deployment process by implementing a clear branching strategy for different environments. This automation handles CreditAI component deployments through CI/CD pipelines, reducing human error through automated validation and testing.

DevOps 81

DevOps Metadata Auto-complete Automation 81