Even though GPT-4 was just released I am quite proud that I am not linking to anything GPT-4 specific. ChatGPT and OpenAI, yes - but not GPT-4.
So what happened the week just gone? Some things to “wet your appetite”: learning path for Azure Data Explorer and Kusto Query Language. While we are on ADX, I finally finished the leaderboard follow-up post. Yay to me!
Some ChatGPT stuff (not GPT-4 😄), and also what impact AI will have on us as developers.
I am rounding off with the question: “Where have all the Big Data Gone?”
Azure Data Explorer
- Data analysis in Azure Data Explorer with Kusto Query Language. Thanks to a tweet by Akshay Dixit I found this. It links to an Azure Data Explorer (ADX) learning path, where students will learn how to analyze data in ADX using the Kusto Query Language (KQL).
- Develop a Real-Time Leaderboard Using Kafka and Azure Data Explorer - I. This is my second post in the Develop a Real-Time Leaderboard Using Kafka and Azure Data Explorer series (read the post why the title says it is “I” 😄). In this post, I look at Azure Data Explorer and what is required to ingest data from Kafka into ADX with low latency.
- Dialogue Prompting Over Documents Using ChatGPT API. The article discusses a project that uses the ChatGPT API to create a dialogue prompt system that can answer questions based on the information provided in a given document. The system involves inputting a question and a document and then using the API to generate an answer based on the context of the document. The author provides a detailed walkthrough of implementing the system and highlights potential use cases, such as in the education and legal fields.
- AI-generated Applications. This post by an old colleague of mine, Ted Neward, discusses the current state of AI-generated code and its potential impact on software development. Ted explains how AI-generated code could help developers automate repetitive tasks and assist with debugging but also raises concerns about the possibility of job displacement and the need for developers to understand the code generated by AI systems.
- Whatever happened to Big Data?. This post discusses the current state of big data and its evolution over the past decade. The author explains how the rise of cloud computing, the increasing popularity of real-time data processing, and the emergence of new data storage technologies have changed the big data landscape. The post concludes by emphasizing the importance of adopting a modern data platform that can handle the complexities of today’s data-driven world.
That’s all for this week. I hope you enjoy what I did put together. Please comment on this post or ping me if you have ideas for what to cover.
comments powered by Disqus