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

AWS Machine Learning Blog

AUGUST 7, 2024

In the face of these challenges, MLOps offers an important path to shorten your time to production while increasing confidence in the quality of deployed workloads by automating governance processes. This post illustrates how to use common architecture principles to transition from a manual monitoring process to one that is automated.

Automation 113

Automation Machine Learning ML Explainability 113

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 104

LLM NLP Data Integration AI 104

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

JUNE 13, 2024

For me, computer science is like solving a series of intricate puzzles with the added thrill of automation. 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.

Explainability 130

Explainability Data Integration Metadata Generative AI 130

IBM Journey to AI blog

OCTOBER 20, 2023

AI platforms offer a wide range of capabilities that can help organizations streamline operations, make data-driven decisions, deploy AI applications effectively and achieve competitive advantages. AutoML tools: Automated machine learning, or autoML, supports faster model creation with low-code and no-code functionality.

Machine Learning 225

Machine Learning Automation AI AI 225

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. Now that weve explained the key features, we examine how these capabilities come together in a practical implementation.

Generative AI 89

Generative AI Responsible AI Automation LLM 89

O'Reilly Media

OCTOBER 11, 2022

There seems to be broad agreement that hyperautomation is the combination of Robotic Process Automation with AI. Using AI to discover tasks that can be automated also comes up frequently. It’s also hard to argue against the idea that we’ll see more automation in the future than we see now. Automating Office Processes.

Automation 141

Automation Data Integration Explainability AI 141

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

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

Marktechpost

MAY 12, 2024

It is based on adjustable and explainable AI technology. The technology provides automated, improved machine-learning techniques for fraud identification and proactive enforcement to reduce fraud and block rates. Fynt AI Fynt AI is an AI automation solution developed primarily for corporate finance departments.

AI Tools 102

AI Tools Neural Network Artificial Intelligence Artificial Intelligence 102

AWS Machine Learning Blog

FEBRUARY 21, 2025

Generative AI is revolutionizing enterprise automation, enabling AI systems to understand context, make decisions, and act independently. At AWS, were using the power of models in Amazon Bedrock to drive automation of complex processes that have traditionally been challenging to streamline.

Categorization 83

Categorization IDP Generative AI Automation 83

Marktechpost

FEBRUARY 23, 2025

Robotic Process Automation (RPA): Companies like UiPath have applied AI agents to automate routine business processes, allowing human workers to focus on more complex challenges. Microsoft has described how such systems help automate routine tasks, allowing human employees to focus on more complex challenges.

Natural Language Processing 54

Natural Language Processing Machine Learning AI AI 54

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

The MLOps Blog

JUNE 27, 2023

This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics. Automated pipelining and workflow orchestration: Platforms should provide tools for automated pipelining and workflow orchestration, enabling you to define and manage complex ML pipelines.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

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. The next step in the data journey is performing analytics on the ingested data and streamlining the output in interoperability-ready formats with reproducible and scalable pipelines.

Data Analysis 186

Data Analysis Data Scientist Explainable AI AI Strategy 186

Marktechpost

MAY 8, 2024

From basic driver assistance to fully autonomous vehicles(AVs) capable of navigating without human intervention, the progression is evident through the SAE Levels of vehicle automation. Despite most scenarios being solvable with traditional methods, unresolved corner cases highlight the necessity for AI-driven solutions.

Deep Learning 120

Deep Learning Neural Network Data Scarcity Natural Language Processing 120

IBM Journey to AI blog

DECEMBER 16, 2022

With a data catalog, Alex can discover data assets she may have never found otherwise. An enterprise data catalog automates the process of contextualizing data assets by using: Business metadata to describe an asset’s content and purpose. A business glossary to explain the business terms used within a data asset.

Metadata 130

Metadata Data Quality Data Discovery Data Scientist 130

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. It involves validating, cleaning, and enriching data to ensure its accuracy, completeness, and relevance. Intuitive interface for data cleansing and enrichment.

Explainability 40

Explainability Data Quality Data Integration Automation 40

Unite.AI

JANUARY 15, 2025

Seamlessly integrate data: With the help of AI, electronic health records (EHRs) and patient management systems (PMS) can be better interconnected, creating a unified experience for both patients and providers. AI alleviates these challenges by automating routine tasks and ensuring data accuracy.

AI 113

AI AI Automation Artificial Intelligence 113

AWS Machine Learning Blog

OCTOBER 2, 2024

However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational complexities are governed on an organizational level. In this post, we discuss how to address these challenges holistically.

Generative AI 115

Generative AI Data Ingestion AI AI 115

Unite.AI

FEBRUARY 21, 2024

For users who are unfamiliar with Airflow, can you explain what makes it the ideal platform to programmatically author, schedule and monitor workflows? Airflow provides the workflow management capabilities that are integral to modern cloud-native data platforms. How does Astronomer use Airflow for internal processes?

LLM 147

LLM Data Platform Software Engineer Chatbots 147

NVIDIA

OCTOBER 23, 2024

Members of the Indian healthcare ecosystem are leading the charge by advancing neuroscience research, combating antibiotic resistance, accelerating drug discovery, automating diagnostic scan analysis and more — all with AI’s help. NVIDIA NIM microservices are available as part of the NVIDIA AI Enterprise software platform.

LLM 113

LLM Generative AI Natural Language Processing Computer Vision 113

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%. He worked at Turkcell, mainly focused on time series forecasting, data visualization, and network automation.

BERT 114

BERT Auto-complete Data Scientist Data Science 114

Unite.AI

JUNE 14, 2024

Can you explain the structured approach Tricon Infotech uses to develop customized GenAI enterprise solutions? This comprehensive managed service model ensures that our customers can focus directly on capturing value from their data without the complexities and overhead of managing separate resources.

Large Language Models 130

Large Language Models Generative AI AI Tools AI 130

AWS Machine Learning Blog

SEPTEMBER 6, 2023

Realizing the impact of these applications can provide enhanced insights to the customers and positively impact the performance efficiency in the organization, with easy information retrieval and automating certain time-consuming tasks. We encourage you to deploy the AWS CDK app into your account and build the Generative AI solution.

Generative AI 115

Generative AI Large Language Models AI AI 115

Snorkel AI

OCTOBER 18, 2023

FMs can also have low explainability, making them hard to understand, adjust, or improve. The Snorkel advantage for claims processing Snorkel offers a data-centric AI framework that insurance providers can use to generate high-quality training data for ML models and create custom models to streamline claims processing.

BERT 64

BERT Machine Learning Explainability Large Language Models 64

ODSC - Open Data Science

JUNE 19, 2023

With the advent of big data in the modern world, RTOS is becoming increasingly important. As software expert Tim Mangan explains, a purpose-built real-time OS is more suitable for apps that involve tons of data processing. The Big Data and RTOS connection IoT and embedded devices are among the biggest sources of big data.

Big Data 96

Big Data ETL Data Science Artificial Intelligence 96

AWS Machine Learning Blog

DECEMBER 7, 2023

Calculating courier requirements The first step is to estimate hourly demand for each warehouse, as explained in the Algorithm selection section. Additionally, for insights on constructing automated workflows and crafting machine learning pipelines, you can explore AWS Step Functions for comprehensive guidance.

Convolutional Neural Networks 120

Convolutional Neural Networks Algorithm Neural Network Data Science 120

Snorkel AI

OCTOBER 18, 2023

FMs can also have low explainability, making them hard to understand, adjust, or improve. The Snorkel advantage for claims processing Snorkel offers a data-centric AI framework that insurance providers can use to generate high-quality training data for ML models and create custom models to streamline claims processing.

BERT 59

BERT Machine Learning Explainability Large Language Models 59

AssemblyAI

JULY 18, 2024

Leveraging SCA allows organizations to have greater transparency into “what goes into the sausage” SCA enables organizations to effectively use open-source ecosystems while conducting automated examination of components. Make sure the API uses AES-256 encryption for data at rest and in transit. or TLS 1.3)

Explainability 147

Explainability Data Integration Automation 147

Marktechpost

JULY 17, 2023

Data gathering, pre-processing, modeling, and deployment are all steps in the iterative process of predictive analytics that results in output. We can automate the procedure to deliver forecasts based on new data continuously fed throughout time. This tool’s user-friendly UI consistently receives acclaim from users.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

Pickl AI

DECEMBER 10, 2024

Summary : Data Analytics trends like generative AI, edge computing, and Explainable AI redefine insights and decision-making. Businesses harness these innovations for real-time analytics, operational efficiency, and data democratisation, ensuring competitiveness in 2025.

Explainable AI 52

Explainable AI Explainability ETL Automation 52

AWS Machine Learning Blog

FEBRUARY 29, 2024

Knowledge Bases for Amazon Bedrock automates synchronization of your data with your vector store, including diffing the data when it’s updated, document loading, and chunking, as well as semantic embedding. The form should explain all foreseeable risks, side effects, or discomforts you might experience from participating.

Machine Learning 131

Machine Learning Computer Vision Generative AI Explainability 131

Pickl AI

MARCH 10, 2023

The following blog will discuss the familiar Data Science challenges professionals face daily. It will focus on the challenges of Data Scientists, which include data cleaning, data integration, model selection, communication and choosing the right tools and techniques.

Data Scientist 52

Data Scientist Data Science Data Integration Auto-classification 52

Pickl AI

FEBRUARY 11, 2025

Summary: Tableau simplifies data visualisation with interactive dashboards, AI-driven insights, and seamless data integration. Key Takeaways Tableau enables dynamic, customisable dashboards for in-depth data exploration. Automated analytics reveal trends and predictive insights for better decision-making.

Data Analysis 52

Data Analysis Data Integration Automation Data Extraction 52

Pickl AI

JULY 8, 2024

Summary: This blog explains how to build efficient data pipelines, detailing each step from data collection to final delivery. Introduction Data pipelines play a pivotal role in modern data architecture by seamlessly transporting and transforming raw data into valuable insights.

Data Quality 52

Data Quality ETL Data Integration Automation 52