aleph VS askai

If you're talking about tools for data, it really depends on what kind of data you're looking at and why you have it. For exploring datasets that you don't know what is contained inside (like data leaks) there's OCCRP's Aleph tool: https://github.com/alephdata/aleph

https://github.com/paperless-ngx/paperless-ngx https://github.com/alephdata/aleph

If you are doing investigative journalism, there is the OCCRP's Aleph for working with big amounts of data and connecting entities https://aleph.occrp.org/ . It's open source and self-hostable. Also for big messy dataset, the ICIJ's Datashare might be interesting.

After wrestling with it for a bit and eventually giving up, I instead turned to ChatGPT to see if it is smart enough for the task. With my free plan, I asked ChatGPT 3.5 the following:

Go to chat.openai.com and log in

In this tutorial, we will learn how to use Strapi, ChatGPT, and Next.js to build an app that displays recipes using AI.

Maybe I am bit dim, but how one can choose GPT-4 Turbo? Is this available from https://chat.openai.com/ ?

With the rise of ChatGPT, Bard Gemini, GitHub Copilot, Devin, and other AI tools1, developers started to fear that AI tooling would replace them. Even though their capabilities are indeed impressive, I don't fear our jobs will go away in 2024.

To illustrate the core concepts of ML and regression analysis, we’ll start with a simple model. ChatGPT (the free version) creates something that works with this prompt:

Fast forward to my college years. I found myself at IIIT Delhi, a prestigious tier 1 computer science engineering college. Around the same time, ChatGPT emerged, shaking the world more vigorously than COVID-19. As fate would have it, I gained temporary access to ChatGPT 4 which runs on GPT 4, and curiosity piqued my interest.