Launching DecisionsCX: Customer engagement with data and AI
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Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
AI
API Generation vs. ELT/ETL | Key Differences
Organizations often grapple with the choice between two distinct but equally vital technologies: API generation and ELT (Extract, Load, Transform) solutions. While both serve as essential tools, they stand at opposite ends of the data management spectrum. API generation focuses on facilitating real-time data access and dynamic communication between software applications, whereas ELT specializes in the consolidation, transformation, and preparation of data for analytics.
Implications of the AI Executive Order for Government Procurement Systems
Artificial intelligence holds the potential to enhance efficiency, streamline processes, and improve decision-making across various government sectors. But without robust safeguards, there is a heightened risk of biased decision-making, privacy breaches, and misuse of sensitive data. The Biden administration’s AI executive order establishes new standards for AI safety and security as well as for responsible use of AI at federal agencies and in state and local governments.
The rise of AI in software testing: trends
AI growing relevance in software testing has garnered substantial attention in today's software industry. While incorporating AI and ML approaches into software testing is not required, it is worthwhile to explore and study how these methods may deliver valuable benefits in specific elements of the testing process. With the incorporation of artificial intelligence (AI) techniques software testing will undergo a transformational transition.
ChatGPT Models: Choosing the Right Fit for Databox Analytics
At Databox, our mission is to help growing businesses leverage their data to make better decisions and improve their performance. We envision a future where every company, no matter the size, can harness its existing data to create more accurate marketing plans, sales goals, budget planning, and more.
7 AI-Driven Tools That Can Improve Content Quality
It is unbelievable how AI is changing our lives by automating some of the most tedious tasks. Thanks to the fast development of AI technologies, the content marketing industry is changing on a daily basis. Here are 7 AI-driven tools that will help you improve your content quality.
Using ChatGPT for Coding
Welcome to Test Case Scenario! In this episode, join our host Jason Baum, and panelists from Sauce Labs as they discuss the report about “Developers Behaving Badly,” what are these so-called bad behaviors, why is this happening, and what are its implications? In this insightful discussion, our host is joined by Evelyn and Titus as they share not only their perspective about these “bad behaviors,” but the possible underlying reasons for it and things we can look forward to in the future of coding and the rise of AI.
Top AI Automation Testing Tools 2024
Ever since we have entered the third decade of the 21st century, artificial intelligence has proven to be the driving force behind innovation. However, the growing need for technology and constant development demands access to rapid testing and quality assurance. Besides, the software testing landscape is undergoing a revolutionary transformation, as we hurtle into a tech-driven era. It means AI-powered tools are being tested using the power of AI automation testing tools.
Generative AI in Insurance: How is Generative AI Helping in Risk Assessment and Claim Processing
Generative artificial intelligence represents a category of AI that utilizes generative models to produce text, images, or other forms of media. These models grasp the intricacies and structure of their input training data, enabling them to generate new data with similar characteristics. In insurance, generative AI plays a pivotal role in expediting digitization processes.
How to Build Accurate and Scalable LLMs with ClearGPT
Large Language Models (LLMs) have now evolved to include capabilities that simplify and/or augment a wide range of jobs. As enterprises consider wide-scale adoption of LLMs for use cases across their workforce or within applications, it’s important to note that while foundation models provide logic and the ability to understand commands, they lack the core knowledge of the business. That’s where fine-tuning becomes a critical step.