Top open source AI models and tools

Open source AI projects have become increasingly popular, giving developers access to frameworks, libraries, and models for building cutting-edge applications. Without massive budgets of their own, developers can now prototype and experiment with the latest AI open source innovations through these readily available (and free!) resources.

There is now a diverse landscape of open source AI for uses like natural language processing, computer vision, and robotics including open source AI art generators, open source AI chatbots, open source AI writers, open source text-to-speech AI and more! Developers are tapping into these tools to build intelligent open source AI assistants, enhance user personalization, optimize recommendation systems, and push the boundaries of what's possible with AI. 

In this piece, we’ll share some of the top open source AI projects and how you can start utilizing them in your own development. Then, we’ll end by telling you a bit more about Inworld’s vision and commitment to AI open source projects. Whether you're prototyping a video game or working on an app, these projects provide customizable building blocks to create performant, scalable AI-powered solutions. Let's dive in!

Stable Diffusion - Open source AI art generator

Stable Diffusion, created by Stability AI, is a powerful open source AI art generator built on text-to-image diffusion model. It produces remarkably high-quality and diverse images from text prompts and is one of the best open source AI generators available. 

With Stable Diffusion, you get excellent results out of the box with the ability to

further customize models. On top of that, the active open source ecosystem offers multiple interfaces from command line to GUI. For those looking to create AI art without paid APIs, it is currently the top option.

Benefits

• Cutting-edge image generation quality rivaling leading commercial alternatives
• Ability to run locally on GPUs without relying on cloud APIs
• Active open source community providing models, scripts, GUIs, and updates
• Can customize and fine-tune models for specific needs

Drawbacks

• Requires high-end GPU to run locally
• Can be challenging to set up and use without technical skills
• Limited real-time control compared to commercial interactive platforms

Other open source AI options

• DALL-E Mini
• NightCafe Creator

Commercial alternatives

• DALL-E 2
• Midjourney

DALL-E Mini - Open source AI art generator

DALL-E Mini has made a splash in the AI community as an accessible, open source variant of the more renowned DALL-E model, which is known for generating images from textual descriptions. This streamlined version offers a glimpse into the world of AI-driven art creation, making it an exciting tool for developers, artists, and hobbyists alike.

DALL-E Mini is great because of its user-friendly approach to image generation, allowing for quick experimentation with AI concepts without the need for extensive computational resources. While it doesn't match the full resolution or fidelity of its big brother, DALL-E 2, DALL-E Mini still manages to capture the imagination with its quirky and often surprising interpretations of text prompts. These qualities make DALL-E Mini a top open source AI art generator.. 

Benefits

• Rapid prototyping of AI-generated images
• Straightforward and accessible platform

Drawbacks

• Lower resolution image quality compared to full-scale models
• May generate unpredictable and less accurate representations
• Limited control over the finer aspects of image generation

Other open source AI art generators

• Stable Diffusion
• NightCafe Creator

Commercial alternatives

• DALL-E 2
• Midjourney

LLaMA - Open source AI chatbot

LLaMA, unveiled by Meta, is an open source large language model (LLM) that serves as a versatile tool for various natural language processing tasks. It's designed to provide an alternative to other open source AI chatbot models like OpenAI's GPT and Google's PaLM, with the significant advantage of being publicly accessible for both research and commercial use. 

LLaMA stands out as one of the best open source AI chatbots for its readiness to be adapted and fine-tuned to a wide array of specific applications, from chatbots to content generation. With its various sizes, ranging from billions to trillions of parameters, LLaMA is flexible enough to accommodate different computational and performance needs.

Benefits

• Broad accessibility 
• Easily customizable and fine-tuned with datasets 

Drawbacks

• Substantial computational power required for its larger versions
• Training requires technical expertise
• Initial quality without training is less refined

Other open source AI chatbots

• Bot Framework
• Rasa
• Botpress

Commercial alternatives

• IBM Watson Assistant
• Oracle Digital Assistant

Bot Framework - Open source AI chatbot

Bot Framework, created by Microsoft, is a comprehensive open source SDK for building chatbots and conversational interfaces using AI. It provides tools to build, connect, deploy and manage bots.

Microsoft Bot Framework serves as a robust open source AI writer for developers to build chatbots powered by AI with natural language capabilities. The open source SDK makes conversational AI more accessible to creators and supports integration with top NLP services like LUIS for language understanding.

Benefits

• Offers SDKs for multiple programming languages
• Easily deployable across multiple channels
• Extensive customization

Drawbacks

• Steep learning curve
• Extensive but complex integration options

Other open source AI chatbots

• LLaMA
• Rasa
• Botpress

Commercial alternatives

• IBM Watson Assistant
• Oracle Digital Assistant

AudioCraft - Open source AI audio generator

AudioCraft, is an open source AI audio generator introduced by Meta for creating music and audio from text prompts. Whether you’re a developer or a content creator, this open source AI content generator enables you to create complex audio content solely through text descriptions.

AudioCraft can power your audio needs with three different models: MusicGen, AudioGen, and EnCodec. AudioGen specializes in generating a variety of audio effects and soundscapes, such as environmental sounds or specific actions (like a dog barking or footsteps inside your home). MusicGen creates musical compositions and melodies across different genres from descriptive prompts. EnCodec is a neural network-based audio compression codec that can be used to deliver high quality audio with significant compression. 

These three models can be used by developers who want to explore the musical landscape, experiment with different sounds, or simply generate an audio track for their latest project. 

Benefits

• High quality audio and music
• Supports training with personal datasets
• Easy to build on and reuse

Drawbacks

• Requires self-hosting instead of fully managed API
• Computational performance is directly correlated to the local hardware 
• User interface could be improved 

Other open source AI audio generators

• Jukebox

Commercial alternatives

• MusicLM

Coqui - AI voice generator open source

Coqui is an open source AI model for creating natural sounding text-to-speech voices from data. It provides tools to train custom TTS models on new languages and voices. 

Coqui TTS is a good open source text-to-speech AI option as it generates high-fidelity voices from speech data. This enables the user to create unique voice clones and custom voices for different needs.

Benefits

• Creates human-like voices from speech data
• Custom voices tailored for specific applications
• Active development community providing models
• Avoid recurring costs of paid voice APIs

Drawbacks

• Requires expertise to train custom voices
• Compute-intensive training process
• Limited fine-tuned control compared to commercial

Other AI voice generators,  open source

• Resemblyzer
• ESPNET

Commercial alternatives

• Replica Studios
• Respeecher

Blender - Open source AI video generator

Blender is an open source 3D creation suite that can be used for AI-assisted video generation. It has integrations with leading generative models to create animations and 3D scenes.

Blender provides accessible tools to incorporate AI into video generation without costly licensing or proprietary software. The integrations with GPT-3, Stable Diffusion, and other AI models open up creative possibilities!

Benefits

• Open source 3D creation tools with AI plugins
• Supports leading models like GPT-3 and Stable Diffusion
• Large open community providing models and assets
• Avoid recurring costs of commercial tools

Drawbacks

• Still requires 3D and creative expertise
• Limited real-time AI video generation control
• High hardware costs if running locally

Other open source AI video generators

• Potat1

Commercial alternatives

• Synthesia
• HeyGen

Benefits of open source AI projects

If you’re wondering whether you should choose an open source AI project or a commercial alternative, we’ll break down the benefits and drawbacks of both in the next two sections. 

Open source AI provides a myriad of advantages to developers looking to implement AI capabilities in their applications and systems. Let's explore some of the key benefits:

• Access to cutting-edge research and models often not yet commercially available
• Ability to customize and tune models beyond off-the-shelf limitations
• Savings on licensing fees and cloud costs
• Greater transparency into how models work
• Rapid prototyping and iteration on solutions
• Leverage community knowledge and best practices
• Inspect code and model architectures for transparency
• Collaboration with developers worldwide on new innovations

Downsides of open source AI projects

While open source AI offers many benefits, there are also some potential drawbacks to keep in mind. Understanding these downsides upfront helps you make informed adoption decisions and mitigate risks early on in the development process. Now, let's look at some key challenges with open source AI projects:

• Less user support available compared to commercial solutions
• Can take more effort to deploy and maintain complex systems
• Advanced features like auto-scaling may require additional work
• Documentation quality varies greatly across projects
• Harder to ensure regulatory compliance for sensitive use cases
• Fragmented frameworks, languages, and tooling
• Long-term viability and maintenance can be uncertain

Is an AI open source model right for you?

When it comes to integrating AI into your applications, the decision between open source AI projects and commercial products largely depends on several key factors.

Risk tolerance 

Your tolerance for risk is one of the primary considerations. Open source AI projects are excellent for early-stage prototyping or non-critical applications. They allow you to test concepts quickly without a significant upfront investment and offer the freedom to experiment and iterate. However, for mission-critical or customer-facing production use cases, you might need the performance, scalability, and reliability that commercial solutions offer.

Technical skills

The technical capabilities of your team are also crucial! Deploying, customizing, and maintaining complex open source AI models requires a certain level of expertise. If your team is equipped with this, then open source AI projects can be a great choice!  Otherwise, if you lack these capabilities in-house, an end to end commercial solution might be a better fit. Commercial products often come with robust documentation and technical support which makes it easier for teams to implement and manage.

Control and integration

Control and integration are other essential aspects to evaluate. Open source AI models provide unlimited access to customize models to fit your exact needs and flexibility that's hard to match! On the other hand, commercial solutions are purpose built for specific use cases and often provide better out of the box performance that can reduce the time and effort needed to tweak and adjust models for optimal results. 

Data privacy and compliance

Last but certainly not least, your data privacy and compliance requirements also play a pivotal role in this decision. Commercial solutions generally have more advanced security features and controls and they're more likely to have relevant regulatory certifications.

Choosing: To AI open source or not to AI open source?

As mentioned, open source comes with some common challenges, like less support, trickier deployments, and lower level controls than commercial counterparts. 

When is open source AI the right choice? 

• Rapid prototyping and proof of concepts
• Testing new ideas and capabilities
• Non-critical systems
• Need flexibility to iterate quickly 

When is commercial AI the right choice? 

• Mission-critical apps
• Deploying to customers and users
• Need scalability and reliability

Of course, there's plenty of middle ground, too. Many leverage open source AI models as a starting point before working with vendors to optimize and productize. With the right platform, you can get the best of both worlds.

Inworld’s commitment to open source

Inworld’s Character Engine AI technology is pushing the bounds of what’s possible in gaming by delivering dynamic and interactive AI NPC performances that enhance player engagement and drive substantive improvements in core metrics. 

Our commitment to developing open source AI models is a testament to our belief that collaboration fuels innovation. Together with the open source community, we’re going to push forward innovations in generative AI that elevate the generative AI and gaming development communities.  

Over the last two years, we’ve learned a lot from our developer community and we’re excited to give back by open-sourcing parts of our platform! Developers can learn more about our open source plans at inworld.ai/open-source or try out our Character Engine in Inworld Studio.