Systems | Development | Analytics | API | Testing

Streamlining Generative AI Deployment with New Accelerators

The journey from a great idea for a Generative AI use case to deploying it in a production environment often resembles navigating a maze. Every turn presents new challenges—whether it’s technical hurdles, security concerns, or shifting priorities—that can stall progress or even force you to start over.

Atomic Tessellator: Revolutionizing Computational Chemistry with Data Streaming

Computational chemistry relies on large volumes of complex data in order to provide insights into new applications, whether it’s for electric vehicles or new battery development. With the emergence of generative AI (GenAI), the rapid, scalable processing of this data has become possible and critical to investigate previously unexplored areas in catalysis and materials science.

AI Governance, Data Governance, and AI Data Governance: Pillars of AI Success

How are AI governance and data governance related? Better still, what’s more important for an organization to focus on, AI-powered data governance or AI data governance? These are important questions, but before we answer these, let’s understand how AI and data governance are related to each other.

5 Ways to Approach Data Analytics Optimization for Your Data Lake

While data lakes make it easy to store and analyze a wide variety of data types, they can become data swamps without the proper documentation and governance. Until you solve the biggest data lake challenges — tackling exponential big data growth, costs, and management complexity — efficient and reliable data analytics will remain out of reach.

Gen AI for Marketing - From Hype to Implementation - MLOps Live #32 with McKinsey and Iguazio

In this MLOps Live session we were joined by Eli Stein, Partner and Modern Marketing Capabilities Leader at McKinsey, to delve into how data scientists can leverage generative AI to support the company’s marketing strategy. We showcased a live demo of a customer-facing AI agent developed for a jewelry retailer, which can be used as a marketing tool to offer personalized product recommendations and purchasing information and support. Following the demo, we held an interactive discussion and Q&A session. Enjoy!

A Comprehensive Guide to End-to-End Microservices Testing for Modern Applications

As part of gaining deeper insights into the rapidly evolving landscape of microservices testing and QA, I had the privilege of attending the Starwest 2024 conference, where one of the highlights was the insightful session led by Tariq King, CEO and Head of Test IO. His session on Full-Stack Testing for Microservices Architectures highlighted the growing leverage of microservices in modern applications and their seamless alignment with Agile and DevOps practices.

Four Strategies to Level-up Your Test Automation in Jira

For years, the traditional approach to automating tests relied heavily on scripted automation frameworks like Selenium, JUnit, and TestNG. While these tools are powerful and adaptable, they require a significant level of technical expertise. Testers need to write, debug, and maintain complex scripts, often leading to bottlenecks in the development process. Relying only on coded solutions limits test automation to a small portion of the team that has deep coding skills.

API Generation to ETL: How DreamFactory Handles Full Data Replication

While many API tools are available on the market—such as enterprise service buses (ESBs) like Apigee and MuleSoft, or low-code solutions like Hasura and CData—few offer the level of flexibility that DreamFactory does. A recent project underscored just how dynamic this lightweight, enterprise-ready API generation tool can be. In this article, we'll dive into this unique project and explore how DreamFactory proved to be much more than just an API generator.