Open-Source AI: Uncensored Models, Building Niche Apps, ChatGPT Alternatives

Uncategorized 5 Minutes

“Open source is about collaborating; not competing.” – Kelsey Hightower

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❓ What You’ll Learn

  • What are open-source ChatGPT alternatives?
  • How to easily build and deploy open-source AI models?
  • What are niche open-source AI models?
  • How to build an audience interested in open-source AI?
  • What is a copyleft license?
  • What limits open-source AI development?
  • How to win in the “blue ocean” with open-source AI?
  • What are 200+ approved open-source licenses?
  • What are 100+ open-source AI models?


💎 Why It Matters

Open-source AI helps us build faster by learning from each other.


🔍 Problem

Closed-source AI companies are gatekeepers.

They decide when and what you can use AI for.


💡 Solution

Open-source AI helps us learn from and build on each others’ work.

This turns an arms race into collaboration.

Now anyone can build ChatGPT.


🏁 Players

Open-Source AI Companies

Open-Source AI Platforms

  • Hugging Face • Build and deploy open-source AI models
  • Replicate • Build and run open-source models in the cloud
  • Google Colab • Platform for machine learning research

Open-Source AI Models

Open-Source AI Datasets

  • The Pile • Dataset of books, webpages, chat logs and more
  • ImageNet • 14,000,000+ annotated images
  • OIG • Dialogue data for AI chatbots

Open-Source AI Tools

  • PyTorch • Framework for building deep learning models
  • TensorFlow • Open-source machine learning framework
  • Keras • Deep learning API for AI models


🔮 Predictions

  • We’ll see open-source ChatGPT alternatives.
  • We’ll see more platforms built to host open-source AI models. They will make it easier to build and deploy AI models.
    • Replicate lets you use open-source models at scale.
    • Hugging Face lets you build, train and deploy open-source AI models.
    • Google Colab lets you write, run and share machine learning code in the browser.


☁️ Opportunities

  • Build a niche AI model. Cater to customers with AI tools designed for specific needs.
  • Offer paid subscriptions to your open-source AI tools. Monetization helps your project sustain the AI race.
    • Coqui is a text-to-speech and voice cloning tool.
    • Lightning AI helps you train, deploy and build AI.
    • Cody helps you read, write and understand code.
    • Giskard helps to lower bias and performance errors in AI models.


🏔️ Risks

  • Race to the Bottom • New open-source models quickly replace the old ones. You can get stuck in a rat race by trying to keep up with the pace. Don’t fall into a coma.
  • Copyleft • These licenses let you change code but you must open source any tool made with it. Making it impossible to build proprietary tools with “copylefted” code.
  • Copyright • It is hard to verify if contributed code or training data is copyright-free. This can lead to lawsuits for using copyrighted work without permission.


🔑 Key Lessons

  • Open-source addresses the problem of vendor lock-in and high switching costs. Platforms such as Hugging Face make it easier to find AI models that fit your use cases.
  • Open-source AI lets individuals build niche applications that large closed-source companies don’t have the time, insight or interest to build. From generating 3D landscapes to turning images into music.
  • Clear documentation boosts the quality and adoption of your open-source AI tool. It helps users and contributors understand what your tool does and how it works.


🔥 Hot Takes

  • AI regulations will force AI companies to open up about their closed-source configurations. OpenAI released GPT-4 without detail on how they built it. As US President Joe Biden weighs in on AI safety, OpenAI has explained how it ensures safety.
  • Open-source AI deployment is limited by hardware shortage. Open-source projects are usually run by small teams and solo developers. Who may not have access to the computing power needed for their projects.


😠 Haters

“Open-source AI is less performant than AI models made by established companies.”
Open-source AI models can be a little worse but a lot less expensive. Depending on your use case, it can be wise to sacrifice quality without wasting lots of money.

“Companies like Meta root for ‘open research’ until they find an edge. Then become closed-source to maintain it. It’s hypocrisy.”
Tech giants are commercial companies. Google invented and open-sourced Transformers that drive modern AI research. Meta open-sourced the code for LLaMA and its leaked version is used to build dozens of other models. They have spent billions on research and hardware. We can’t judge them for trying to compensate for their efforts.

“Closed-source companies make use of both internal and open-source AI research.”
True. Some open-source projects may not exist without support from closed-sourced companies.


🔗 Links

  1. We Have an Upcoming Report on Open-Source AI • The tweet behind this report.
  2. OSI-Approved Licenses • List of 200+ open-source licenses.
  3. Open LLM Leaderboard • List of 100+ open-source AI models with performance tests.


📁 Related Reports

  • ​​​​​Monetized Open Source • Monetization helps open-source projects to sustain.
  • ChatGPT • ChatGPT boosts the productivity of businesses and individuals.
  • Voice Cloning • Build an audio content machine that works anytime, anywhere.
  • Agencies • Help companies solve problems without hiring and managing large teams.
  • Prompt Engineering • Learn how to direct AI.


🙏 Thanks

Thanks to Matthew LaCrosse and Jonathan Parra. We had a great time jamming on this report.

✏️ Emin researched and wrote this report. Dru researched and edited this report.


📈 What else?

Trends PRO #0120 — Open-Source AI has more insights.

What you’ll get:

  • 6 Open-Source AI Companies (100% More)
  • 6 Open-Source AI Platforms (100% More)
  • 10 Open-Source AI Models (233% More)
  • 11 Open-Source AI Datasets (267% More)
  • 10 Open-Source AI Tools (233% More)
  • 7 Predictions (133% More)
  • 9 Opportunities (200% More)
  • 5 Risks (67% More)
  • 6 Key Lessons (100% More)
  • 8 Hot Takes (300% More)
  • 9 Links (200% More)

With Trends Pro you’ll learn:

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  • (📈 Pro) What are international open-source AI labs?
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