Photograph via snooOG

aiHub is a platform that compiles resources on Artificial Intelligence, covering topics from weak to strong AI, such as machine learning, practical applications, research, and AI-related discussions. It also features interesting video content.

aiHub gathers quality and informative research papers, blog posts, reddit submissions and discussions, etc. from the field of Artificial Intelligence, from weak to strong AI, and including:

  • Machine Learning & Data Mining.
  • Practical uses of AI.
  • Blue sky AI research, essays, articles, discussions.
  • AI questions, from practical questions to speculation on future directions.
  • Cool/interesting video lectures/talks/demos.

Philosophy / Guidelines

  • aiHub is not in competition with other subreddits. Make submissions to more appropriate (specific) AI subreddits where possible (as a first step). Good quality submissions can then be posted here as a link to the subreddit entries.

  • If no appropriate subreddit exists then go ahead and post directly to aiHub, but try to keep it high quality (high signal:noise ratio).

  • Submissions linking to notable/informative comment threads are also encouraged, in the spirit of r/DepthHub.

  • Finally, these are (A) guidelines, not rules, and (B) likely to be revised periodically depending on feedback and how aiHub develops. However, please try to stay within the spirit of the guidelines and philosophy stated here.

Associated subreddits

External sites:

  • Kaggle - Data Mining competitions with prizes!
  • CrossValidated - Stats and Machine Learning Q & A
  • aitopics.org Please inform the moderator(s) of any notable AI subreddits/sites not on these lists. Thankyou.


4,284 Subscribers


Everyone has an interesting perspective on how AI may improve something or be valuable.

That viewpoint may not be available to others (that’s UVP already). So, creating content may become a way to extract that value. And it’s worth trying to start sharing it. For example, I have a unique perspective on AI for the eCommerce industry because I was working in it, on Fashion as I was building a fashion startup, and finally on Creators & Founders as I consider myself and have a connection to that community. This helped me build Creators AI and start writing content.

Actually, starting to publish content in discovery platforms (TikTok, Substack, LinkedIn, X) dont require an audience. Starting a newsletter may sound a bit more difficult, but it is a great place to launch and validate your content's value. In the end, choosing the content form and place to publish it - is very unique.

What can I do? You can bring an interesting perspective on using AI from your work, hobbies, studies, or personal life situations.


  1. Write with AI by Nicolas Cole -Nicolas is a Digital Writer and co-founder of the famous writing accountability project Ship 30 for 30. He saw a fantastic opportunity to combine his writing community expertise with AI. The result is a Paid Newsletter with 39,000 subscribers.
  2. Educating AI by Nick Potkalitsky -PhD and English Teacher Nick started sharing his perspective on AI for teachers, parents, and educational workers. The newsletter has more than 1000 subscribers and good engagement rates.
20:18 UTC


How does Apple Intelligence work?

As the developers shared during the presentation, Apple Intelligence is the personal intelligence system that uses powerful generative models, large language models and diffusion models to check whether your mom’s plane has already landed. AI can gather data from many apps on your device such as Notes, Messages and Contacts, identify it and then use it to answer your queries. 

It is especially cool that you can just ask things as you would in real life because Siri understands natural language now. And if by chance your question requires research outside the data which was stored on your device it can call up the big brother ChatGPT. But only if you allow it, which generally complicates user experience, but is said to protect your privacy. We will talk about it later.

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19:22 UTC


Starting a collaborative effort to build and train models collectively, and redistributing the earnings among the contributors, gaining independence from the corporate world

These models will be used on scientific projects that will aim to achieve results, solving problems, innovating and creating new ideas, new architectures. Join me over here https://discord.gg/WC7YuJZ3

01:45 UTC


What Does Scale AI Do?

As I mentioned, the startup provides labeled data for AI training. Major companies use its sources to power LLMs like ChatGPT and Gemini. Scale AI also offers tools to help businesses and governments customize these models for their specific needs. From a technical point of view, the startup has made many advancements in this field.

Here are a few of them, as cited by Scale AI itself:

• Autonomy Data Engine powered breakthroughs in L4 autonomy.

• Public Sector Data Engine has powered many US Department of Defense AI programs.

• Scale partnered with OpenAI in the first reinforcement learning experiments with human feedback on GPT-2 and scaled these techniques to InstructGPT and beyond.

Scale supplies data to power nearly every leading AI model, serving organizations like OpenAI, Meta, Microsoft, and more.

Now, Scale AI is tackling a major hurdle in the field: the ever-growing hunger for data that comes with more complex models. Their solution? Building a "data foundry" to ensure an abundance of data specifically designed to push the boundaries of AI.

This new phase, fueled by a $1 billion funding round, focuses on three key principles:

  • Data Abundance: Instead of simply having enough data, the company aims to create a surplus of data specifically prepared for AI use.
  • Frontier Data: Not all data is created equal. The company plans to develop "frontier data" that challenges AI in new ways, pushing its capabilities towards complex reasoning, multimodality, and even creating intelligent agents.
  • Better Measurement: To ensure trust and widespread adoption, the company also plans to improve how AI performance is measured. This will be crucial for building confidence in the technology.

Scale AI emphasizes that achieving data abundance requires expertise across engineering, operations, and AI itself. But with the new funding there shouldn't be much of a problem with that.

If we draw parallels with other industries, Scale AI reminds me more and more of the ASML. It develops equipment to produce the best and highest performing chips on the market. And while everyone thinks that the IT sector is completely dependent on TSMC, it is ASML that plays a decisive role. And it makes you wonder what heights Alexander Wang and his startup might have reached.

22:53 UTC


Mrs. Puff x Mr. Krabs - Be My Lover (AI Cover | La Bouche)

17:20 UTC


AI Code Generation: Evolution of Development and Tools

The article explains how AI code generation tools provide accelerating development cycles, reducing human errors, and enhancing developer creativity by handling routine tasks in 2024: AI Code Generation

It shows hands-on examples of how it addresses development challenges like tight deadlines and code quality issues by automating repetitive tasks, and enhancing code quality and maintainability by adhering to best practices.

15:57 UTC


From Prompt Engineering to Flow Engineering - AI Breakthroughs to Expect in 2024

The following guide looks forward to what new developments we anticipate will come for AI programming in the next year - how flow engineering paradigm could provide shift to LLM pipelines that allow data processing steps, external data pulls, and intermediate model calls to all work together to further AI reasoning: From Prompt Engineering to Flow Engineering: 6 More AI Breakthroughs to Expect

  • LLM information grounding and referencing
  • Efficiently connecting LLMs to tools
  • Larger context sizes
  • LLM ecosystem maturity leading to cost reductions
  • Improving fine-tuning
  • AI Alignment
16:22 UTC


Codiumate Coding Agent - CodiumAIResources And Tips

The 4-min video guide shows adding a release notes feature to the Codium AI agent project with the Codium agent to develop a feature for a project: Codiumate Coding Agent - CodiumAI

  • The Codium agent provides a coding plan with steps to implement the release notes feature, and generates the code for the release notes feature according to the plan.
  • The user reviews and refines the generated code to ensure it's accurate, tests the new release notes feature in the CLI, and it works as expected.
06:30 UTC


AI Recommendations

Can someone recommend an AI news subreddit? I want to stay up-to-date on the latest developments.

07:23 UTC


Tandem Coding with Codiumate-Agent - Hands-on Guide

The guide explores using new Codiumate-Agent task planner and plan-aware auto-complete while releasing a new feature: Tandem Coding with my Agent

  • Planning prompt (refining the plan, generating a detailed plan)
  • Plan-aware auto-complete for implementation
  • Receive suggestions on code smell, best practices, and issues
07:40 UTC


Generative AI Code Testing Tools for AWS Code - Automated Testing in AWS Serverless Architecture

The guide explores how CodiumAI AI coding assistant simplifies automated testing for AWS Serverless, offering improved code quality, increased test coverage, and time savings through automated test case generation for a comprehensive set of test cases, covering various scenarios and edge cases, enhancing overall test coverage.

15:29 UTC


Women watching the sunrise: AI generated images 3D style

20:08 UTC


Axl Rose - Rollover DJ (AI Cover | Jet)

18:28 UTC


CopyMonkey Review: Skyrocket Your Amazon Sales with CopyMonkey AI!

15:55 UTC


Movable Type

Hey all,

Quick share: Movabletype has been a total game-changer for my self-help writing. I'm talking lightning-fast outlines and manuscripts – like having a writing buddy who just gets it. Plus, they're cooking up an interview tool for memoirs that's got me pumped.


If you're serious about self-improvement writing, or really any publishing any type of book, Movabletype's worth checking out.


18:21 UTC


Understand how Sora AI Video generator works (for the non tech savvy)

11:26 UTC


Originality AI Review: Inside Look at Originality AI

18:16 UTC


Mr. Krabs - Handsomer (AI Cover | Russ)

19:40 UTC


How Alpha Codium achieves performance on coding challenges - CodiumAI CEO talk

15:50 UTC


⚡Edgen now supports Vulkan, CUDA and Metal | Open Source and local GenAI server alternative to OpenAI's API. Supports all GGUF models, across Windows, Mac and Linux with one 30MB download.

Our goal with⚡Edgen is to make privacy-centric, local GenAI app development accessible to more people.

It is compliant with OpenAI's API and built in 🦀 Rust so it can be natively compiled into Windows, Linux and MacOS (with a 30MB executable).

We'd love for this community to be among the first to try it out and provide feedback!

Check out⚡Edgen on GitHub: GitHub - edgenai/edgen: ⚡ Edgen: Local, private GenAI server alternative to OpenAI.

And keep an an eye out for future releases:

  • Speech to Text
  • Embeddings Endpoint
  • Multimodal Endpoint
  • Text to Image Endpoint

14:59 UTC

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