InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Simplifying Persistence Integration with Jakarta EE Data
Jakarta Data streamlines Java enterprise data integration. Supporting various databases, it boosts productivity, is open-source, and community-driven. GitHub offers hands-on experience for modernizing enterprise architectures.
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Building Kafka Event-Driven Applications with KafkaFlow
KafkaFlow, a .NET open-source project, simplifies Kafka-based event-driven app development with features like middleware for message processing, enhancing maintainability, customization potential, and allowing developers to prioritize business logic.
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/articles/ai-ml-data-engineering-trends-2023/en/smallimage/the-infoq-trends-report-small-logo-1693560017882.jpeg)
InfoQ AI, ML, and Data Engineering Trends Report - September 2023
In this annual report, the InfoQ editors discuss the current state of AI, ML, and data engineering and what emerging trends you as a software engineer, architect, or data scientist should watch. We curate our discussions into a technology adoption curve with supporting commentary to help you understand how things are evolving.
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Managing the Carbon Emissions Associated with Generative AI
There’s an increasing concern about the energy use and corresponding carbon emissions of generative AI models. And while the concerns may be overhyped, they still require attention, especially as generative AI becomes integrated into our modern life. Factors such as model architecture, transparency and quantization of models are required to decrease carbon emission from AI systems.
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Leveraging Eclipse JNoSQL 1.0.0: Quarkus Integration and Building a Pet-Friendly REST API
Eclipse JNoSQL 1.0.0 modernizes NoSQL integration with advanced features, standardized specs (Jakarta NoSQL & Jakarta Data), enhanced queries, schema migration, and Quarkus framework compatibility. It simplifies NoSQL use, boosts performance, scalability, and integrates seamlessly, empowering developers with tools to streamline data management in modern apps.
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/articles/ai-based-prose-programming-for-subject-matter-experts/en/smallimage/AI-based-prose-programming-small-1691410669692.jpg)
AI-Based Prose Programming for Subject Matter Experts: Will This Work?
In this article, author Markus Völter discusses the future of programming using Large Language Model (LLM) tools like ChatGPT and GitHub’s Copilot for prose-to-code generation. He also talks about what new approaches and language changes need to be in place to help non-programmers take advantage of the "program in prose" techniques.
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/articles/chatgpt-agent-C-plus-plus/en/smallimage/creating-your-own-AI-co-author-using-Cplusplus-small-1687936436760.jpg)
Creating Your Own AI Co-Author Using C++
While using ChatGPT through a web interface is one thing, creating your own autonomous AI tool that interfaces with ChatGPT via its API is a different story altogether. As strong proponents of C++, in this article we are going to present a GPT tool written in C++ to ease the pain of dealing with the daunting task of editing endless editorial comments.
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Comparative Analysis of Major Distributed File System Architectures: GFS vs. Tectonic vs. JuiceFS
As storage needs continue to grow, traditional disk file systems have revealed their limitations. To address the growing storage demands, distributed file systems have emerged as dynamic and scalable solutions. In this article, we explore the design principles, innovations, and challenges addressed by three representative distributed file systems: Google File System (GFS), Tectonic, and JuiceFS.
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/articles/analytical-data-management-duckdb/en/smallimage/in-process-analytical-data-management-with-DuckDB-small-1686236227723.jpg)
In-Process Analytical Data Management with DuckDB
DuckDB is an open-source OLAP database for analytical data management that operates as an in-process database, avoiding data transfer overhead. Leveraging vectorized query processing and Morsel-Driven parallelism, the database optimizes performances and multi-core utilization for analytical data processing.
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/articles/gdpr-with-spring-and-aop/en/smallimage/easy-implementation-of-GDPR-with-aspect-oriented-programming-small-1684505109873.jpg)
Easy Implementation of GDPR with Aspect Oriented Programming
GDPR compliance should be a default feature in every application that handles PII (Personally Identifiable Information). Most organizations have an impression that GDPR is a luxury feature that needs special tools to implement. But, we can see that the frameworks and design patterns we already use in our everyday development can very well be used to implement the GDPR rules.
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AIOps: Site Reliability Engineering at Scale
AIOps can simplify and streamline processes which can reduce the mental burden on employees while improving communication and collaboration between departments.
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The Wonders of Postgres Logical Decoding Messages
In this article, author Gunnar Morling discusses Postgres database's logical decoding function to retrieve the messages from write-ahead log, process them, and relay them to external consumers, with help of use cases like outbox, audit logs and replication slots.