Systems | Development | Analytics | API | Testing

AI

Introducing Qlik's AI Accelerator - Delivering Tangible Customer Outcomes in Generative AI Integration

At Qlik, we're witnessing a thrilling shift in the landscape of data analysis, customer engagement, and decision-making processes, all thanks to the advent of generative AI, especially Large Language Models (LLMs). The potential for transformation across all sectors is enormous, but the journey toward integration can be daunting for many businesses with many leaders wondering where to start in integrating the exciting capabilities of AI into their daily workflows.

Embedded analytics in the age of generative AI

Every company around the globe is trying to get in on the GenAI wave to simplify user experiences with natural language. And this is especially true in the realm of data and analytics. Imagine if you could enable all of your marketers to evaluate the performance of their campaigns with a simple question? Or, if you could provide all of your insurance risk managers with the ability to analyze the risk profile of their claims with the power of search and automated insights?

Are We in an AI Information Bubble?

Are we in an AI bubble? We can't stop talking about AI in tech. It's at every conference and in every startup pitch. But is the rest of the world as enamored as we are? In this conversation, we explore AI’s impact beyond the echo chamber of the tech industry. We look at attitudes toward AI in other spaces, from healthcare to finance, weighing the risks and benefits of its application. We also look to the future, questioning whether we’ve reached the limits of AI given compute power constraints.

How to Perform Database Analysis with AI

This blog explores how DreamFactory leverages its robust features to perform database analysis with AI, ensuring secure and efficient data operations. We will discuss the platform’s ability to generate dynamic APIs, provide real-time data insights, and maintain stringent security measures to protect data integrity.

Introducing Tricentis Copilot solutions

We are thrilled to announce Tricentis Copilot solutions, a collection of advanced generative AI capabilities available across our products that help customers boost their efficiency throughout the entire testing lifecycle. With Tricentis Copilot solutions, you can autogenerate manual tests from requirements, optimize your portfolio, autogenerate custom code, and get meaningful insights.

Turbocharging Your Business with (Gen)AI

If you were to stop someone walking down the street and ask them how long artificial intelligence, or AI, has been a hot topic, they might say it’s something that’s emerged mostly in recent years. But AI has been around for a long time, with the term first being coined as long ago as 1955. Generative AI however is a different beast, and one that's largely responsible for moving the topic of AI to the tip of everyone’s tongues – from consumers to enterprises alike.

Introduction to Gemini in BigQuery

Data practitioners spend much of their time on complex, fragmented and sometimes, repetitive tasks. This limits their ability to focus on strategic insights and maximize the value of their data. Gemini in BigQuery shifts this paradigm by providing AI capabilities that help streamline your workflows across the entire data lifecycle.

Streamline Your AI Integration: A Deep Dive into Kong AI Gateway

Join us to learn about the AI Gateway concept and explore the rapidly evolving landscape of large language models (LLMs) in modern applications. With the surge of AI providers and the lack of standardization, organizations face significant challenges in adopting and managing AI services effectively. Kong's AI Gateway, built on the proven Kong Gateway platform, addresses these challenges head-on, empowering developers and organizations to harness the power of AI quickly and securely.

Snowflake Launches the World's Best Practical Text-Embedding Model for Retrieval Use Cases

Today Snowflake is launching and open-sourcing with an Apache 2.0 license the Snowflake Arctic embed family of models. Based on the Massive Text Embedding Benchmark (MTEB) Retrieval Leaderboard, the largest Arctic embed model with only 334 million parameters is the only one to surpass average retrieval performance of 55.9, a feat only less practical to deploy models with over 1 billion parameters are able to achieve.