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AI

Ethical considerations in AI-powered software testing

Integrating Artificial Intelligence (AI) in software testing is a major advancement in software development, enhancing efficiency and accuracy while handling complex scenarios. This technological leap introduces significant ethical challenges, such as concerns over data misuse and the need for algorithmic transparency. Understanding and addressing these issues is crucial for fostering responsible innovation in AI.

Hitting the Ground Running with Generative AI

Generative AI was undoubtedly the most important data moment of 2023, and created a level of excitement for our industry that will certainly continue to be felt in 2024. As we welcome the new year, I am thrilled to share that Qlik is hitting the ground running on that front: today we are announcing the acquisition of groundbreaking technology from Kyndi, an innovator in natural language processing, search, and generative AI.

Top 4 Data + AI Predictions for Telecommunications in 2024

The sheer breadth of data that telecommunications providers collect day-to-day is a huge advantage for the industry. Yet, many providers have been slower to adapt to a data-driven, hyperconnected world even as their services — including streaming, mobile payments and applications such as video conferencing — have driven innovation in nearly every other industry. The speed with which generative AI will change how we work, live, communicate and entertain ourselves is nearly unfathomable.

Revolutionizing Hurricane Property Insurance: The Dynamic Duo of Imaging Data and Generative AI

A catastrophe hazard is a severe and widespread event that causes significant damage and financial loss. These events are frequently natural disasters or large-scale human-made incidents that affect expansive and contemporary claims. Catastrophe hazards pose substantial trouble to insurers, as they can lead to a high volume of claims within a short period, potentially impacting insurance companies’ financial stability.

How #ChatGPT Acquires Its Knowledge? | Raju Kandaswamy | #SoftwareTesting #GenerativeAI

In this intriguing video, Raju Kandaswamy delves into the fascinating world of ChatGPT, unraveling the mechanisms behind how this powerful language model acquires its knowledge. Gain insights into the training process, the vast datasets involved, and the continuous learning loop that refines ChatGPT's language capabilities. Whether you're a curious user or a tech enthusiast, this session offers a behind-the-scenes look at the knowledge acquisition journey of ChatGPT, shedding light on the technology that powers its diverse and contextually rich responses.

4 AI Privacy Issues-and How to Combat Them

Artificial intelligence is changing the world. With use cases ranging from content generation to deep data analysis to detecting health issues, AI can greatly improve lives and enhance business outcomes. And with the explosion of generative AI services and large language models, we can expect AI to become even more ubiquitous than it already is. But AI isn’t perfect. In particular, AI privacy issues put organizations at risk or prevent adoption in the first place.