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GenOs Index - The May Edition: Stability on the Horizon, Maybe

Generative AI Open Source (GenOS) Index - May 2023

Back in early April, we had launched the Generative AI Open Source (GenOS) Index to track the top open source projects related to Generative AI and LLMs. Since then, we published a second edition of the GenOS Index that reflected the frenetic pace of innovation in the Generative AI space. This month, we are back with the latest edition of the GenOS Index - the May edition - showcasing the fastest growing open source projects in Generative AI between the end of February and the end of May.

First, a quick refresher on the methodology. Every month, we identify the top 30 open source projects in Generative AI as ranked by GitHub star growth (adds) in the preceding 90 days, with 500-star adds being the minimum for a project to be considered. Furthermore, we categorize the projects into three categories - Models, Infrastructure/Tooling and Applications - to provide visibility into how different parts of the Generative AI ecosystem are evolving.

The key takeaways from this month’s GenOS Index are as below.

The Top 30 list shows the first signs of stabilizing

In contrast to the April edition, when the GenOS Index (the top 30 list) had a whopping 18 new entrants, this month it has only 5 - PrivateGPT, Bark, Text Generation Web UI, Chatbox, and Chatbot for PDF. Additionally, there has been very little movement at the top of the list - Auto-GPT continues to crush it at the very top - while the top 5 projects this month were ranked almost similarly last month as shown below.

Project Rank in GenOS-May Rank in GenOS-April
Auto-GPT 1 1
GPT4All 2 3
Stable Diffusion Web UI 3 2
LangChain 4 6
Segment Anything 5 4

All in all, it feels that we are seeing some early signs of stability among the top 30 projects, with the fastest growing projects growing even faster and making it harder for the new entrants to break in.

Microsoft shows up strongly with multiple Infrastructure/Tooling projects

In this month’s Index, Microsoft showed up prominently in the Infrastructure/Tooling category, with two projects ranked in the top 30 and two more among the top 45:

  • JARVIS (#12): A unique collaborative system where multiple AI models can be used to achieve a given task, with ChatGPT acting as the controller of the task.
  • DeepSpeed (#19): A deep learning optimization software suite that powers scale and speed for both training and inference.
  • Semantic Kernel (#38): A lightweight open-source orchestration SDK that lets one easily mix and match AI prompts with conventional programming languages like C# and Python, allowing developers to integrate AI into their apps.
  • Guidance (#44): A DSL to control modern language models more effectively and efficiently than traditional prompting or chaining, thereby reducing the cost of LLM interaction.

While Microsoft has been on the forefront of all things AI for a while now, this month’s GenOS Index showcased several projects from the company that represent a few key pieces of the infrastructure stack needed to make LLMs mainstream and integrate into regular apps.

Model and Infrastructure/Tooling projects continue to dominate

Finally, the category makeup - across Models, Infrastructure/Tooling and Applications - for the top 30 projects continues to hold steady with at least 80% of the projects being in the Models and Infrastructure/Tooling categories. The relatively lighter representation of projects in the Application category likely reflects the fact that the open source ecosystem naturally favors projects that are more Model and Infrastructure/Tooling centric.

The list of all top 30 projects in this month’s GenOS Index are as follows:

The Rising Stars

As we had done in the past, we highlight below a few other really interesting projects that, while not on the GenOS Index this month, have gained significant traction and are anticipated to break into a future edition of the GenOS Index:

  • Nebuly: A platform to monitor and optimize AI costs by connecting to all AI cost sources (compute, API providers, AI software licenses, etc) and centralizing them in one place to give full visibility on a model basis. Think of this as the modern observability+optimization platform for AI costs, something that is on everyone’s mind as AI goes mainstream.
  • MLC: There are multiple MLC projects - MLC LLM and WebLLM - with the goal of enabling everyone to develop, optimize and deploy AI models natively on any consumer device. More on that from the MLC team here.
  • RoomGPT: A really cool application of AI that allows one to upload a photo of a room and generate a dream room with AI!
  • ChatALL: Since different LLM-based bots often excel at different tasks, ChatALL allows one to send a prompt to several AI bots concurrently and help discover the best results.
  • AudioGPT: While the GitHub repository has a fairly nondescript description, this is a really interesting project that can be a dialogue assistant (like ChatGPT, but with audio as input), generate audio content, and do professional voice-overs for podcast and videos using style transfer.

That is it for this month - stay tuned for the next monthly installment of the GenOS Index!