Systems | Development | Analytics | API | Testing

How to Write API Test Cases Using ChatGPT | Sidharth Shukla | #apitesting #chatgpt #chatgptprompts

In this hands-on demonstration, Sidharth Shukla showcases the innovative integration of ChatGPT in writing API test cases. Breaking new ground in the world of testing, Sidharth illustrates how ChatGPT, a powerful language model, can be harnessed to streamline and enhance the process of crafting API test cases.

A Deep Dive Into Sending With librdkafka

In a previous blog post (How To Survive an Apache Kafka® Outage) I outlined the effects on applications during partial or total Kafka cluster outages and proposed some architectural strategies to handle these types of service interruptions. The applications most heavily impacted by this type of outage are external interfaces that receive data, do not control request flow, and possibly perform some form of business transaction with the outside world before producing to Kafka.

Performance Testing and ChatGPT

Performance testing applications requires a set of skill that are build and gathered over many years of studying and using the various techniques and tools that are required to make sure the application you are testing is fit for production. Now we have all heard of Artificial Intelligence (AI) and the many tools and companies that now exist in the AI space. Based on a quick look on the internet there are around 15,000 AI startups in the United States alone.

Kotlin Arrays Simplified: The Definitive Guide

An array is like a box with compartments, where you can store a set number of items of the same kind. Arrays play a crucial role in Kotlin, helping us hold many items together. They allow us to send multiple values to a function easily, or make various changes to the data. There are various different forms of arrays in Kotlin, including the object-type array, represented by something called the array class.

Cloudera's QATS Certification for Dell PowerScale Unleashes a New Era of Data Management

With its rise in popularity generative AI has emerged as a top CEO priority, and the importance of performant, seamless, and secure data management and analytics solutions to power those AI applications is essential. Cloudera Private Cloud Data Services is a comprehensive platform that empowers organizations to deliver trusted enterprise data at scale in order to deliver fast, actionable insights and trusted AI.

It's Midnight. Do You Know Which AI/ML Uses Cases Are Producing ROI?

In one of our recent blog posts, about six key predictions for Enterprise AI in 2024, we noted that while businesses will know which use cases they want to test, they likely won’t know which ones will deliver ROI against their AI and ML investments. That’s problematic, because in our first survey this year, we found that 57% of respondents’ boards expect a double-digit increase in revenue from AI/ML investments in the coming fiscal year, while 37% expect a single-digit increase.

Predictions for the Dawning AI Age: What to Expect in 2024 and Beyond

2024 is going to be an important transition year for artificial intelligence. 2023 was the public debut of generative AI and large language models (LLMs), a year of amazement, excitement, occasional panic and, yes, more than a little bit of hype. The year ahead is when businesses begin to make the promise of advanced artificial intelligence real, and we’ll begin seeing the effects on how we work and live.

ChatGPT API Pricing (Cost): Everything You Need to Know

API pricing is important for developers and businesses alike, as it shapes strategic decisions and resource allocation. As APIs are integral to AI App developers’ frameworks , cost-value alignment in pricing ensures informed choices for organizations and customers alike, preventing unexpected financial hurdles. For AI-based API products like the ChatGPT API, pricing models must offer clarity and flexibility.

Amazon Bedrock Analytics Sources - Quick Demo (using Anthropic)

Amazon Bedrock is the name of the Amazon service that offers a single API to access foundation models provided by companies such as AI21, Amazon Titan, Anthropic and Cohere, from which you can build generative AI into your Qlik applications without writing any code. With generative AI, organizations can broaden insight and context while adding a variety of new and exciting capabilities directly in analytics apps, load scripts, and through app automations. The analytics connector constructs questions and our unique associative engine passes only relevant data related to those selections, in real-time, allowing users to get contextually relevant responses while minimizing cost and complexity. Automation connectors offer the ability for developers to send questions and receive responses and data sets as part of automation workflows.