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confluent

Atomic Tessellator: Revolutionizing Computational Chemistry with Data Streaming

Sep 26, 2024 By Will Stolton In Confluent
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.
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Cigniti

Enhancing Convenience and Customer Experience: The Case for Investing in Self-Service Kiosks

Sep 26, 2024 By Ruthika Belide In Cigniti
Self-service kiosks have rapidly become a staple in the retail landscape, symbolizing the growing trend toward automation in customer interactions. In 2023, the global self-checkout market was valued at approximately $4.5 billion, with estimates suggesting it could reach between $5.2 and $6.0 billion by the end of 2024. This surge is driven by increasing consumer demand for convenience, technological advancements, and the pursuit of more seamless shopping experiences.
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astera

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

Sep 26, 2024 By Khurram Haider In Astera
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.
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antino

SaaS Security Risks that every Business needs to Address

Sep 26, 2024 By Vinay Krishna Gupta In Antino
In this Digital era, getting your own hands into every operational activity is not the right thing to do. There are IT transformation consulting experts whose experience and skill set can be leveraged to reduce time, effort, and cost for your organization. In that context, today’s organizations are delivering more and more into cloud-based infrastructure.
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chaossearch

5 Ways to Approach Data Analytics Optimization for Your Data Lake

Sep 26, 2024 By Thomas Hazel In ChaosSearch
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.
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Gen AI for Marketing - From Hype to Implementation - MLOps Live #32 with McKinsey and Iguazio

Sep 25, 2024 By Iguazio In 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!
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alphabin

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

Sep 25, 2024 By Pratik Patel In Alphabin
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.
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smartbear

Four Strategies to Level-up Your Test Automation in Jira

Sep 25, 2024 By Maggie Bean In SmartBear
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.
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