Cartesia

🌈 Abstract

The article discusses Cartesia's mission to build the next generation of ubiquitous, interactive AI that can run on any device. It introduces three key releases:

• Edge: An open-source library for developing efficient on-device AI models using state space models (SSMs)
• Rene: An open-source 1.3B parameter language model designed for efficient on-device inference
• Sonic On-Device: A generative voice model that supports low-latency real-time streaming on-device

The article highlights the advantages of on-device AI over cloud-based approaches, such as reduced data transfer, lower latency, and increased privacy and security. It also discusses how new model architectures like SSMs are key to enabling powerful yet efficient AI models that can run on the edge.

🙋 Q&A

[01] On-Device Intelligence

1. What are the key advantages of on-device AI over cloud-based approaches?

• Minimizes data transfer, enabling continuous streaming of high-resolution multimodal data
• Removes network latency, enabling higher application latency and reliability
• Enables deployments in environments with poor connectivity, high security requirements, or intolerance for network drops
• Keeps deployments fully private and secure within the physical constraints of the hardware

2. What are some example use cases of on-device AI that the article discusses?

• Assistants: Turning any device into a proactive personal assistant
• Communication: Instant language translation like "Babelfish"
• Security: Identifying anomalies and events of interest on video cameras
• Healthcare: Privately communicating with patients
• Education: Generating personalized educational content on an iPad
• Robotics: Perceiving and acting with high speed and reliability
• Gaming: Generating and controlling video for fully generative games

[02] Edge: An Open-Source Library for On-Device SSMs

1. What is the purpose of the Edge library? Edge is an open-source library developed by Cartesia to facilitate the research and release of efficient state space model (SSM) architectures for on-device AI applications.

2. What features does Edge provide?

• Supports optimized inference, including Metal kernel bindings, layer quantization, and more
• Includes custom Metal kernels for the Mamba-2 SSM architecture, enabling deployment on Apple M-series chips
• Provides a Python package (cartesia-mlx) for building on top of Edge and local development/testing

3. What models are currently available in the Edge library? All official Mamba-2 models, including the Rene language model, are now available in the Edge library.

[03] Rene: An Open-Source 1.3B SSM Language Model

1. What are the key features of the Rene language model?

• 1.3B parameter hybrid model with Mamba-2 and MLP layers, as well as some sliding-window attention (SWA) layers
• Designed for highly efficient on-device use, with a fixed memory footprint at inference time
• Uses Mamba-2 layers to enable faster prefill times compared to other pure-SSM architectures

2. How does Rene perform compared to other open-source small language models (SLMs)? Rene outperforms other SLMs like Apple's OpenELM (1.1B) and Google's recurrent Gemma (2B) on a variety of standard language modeling benchmarks, including common-sense reasoning and language understanding tasks.

3. What optimizations does Edge provide for running Rene on-device? Edge supports Rene natively in MLX without any quality loss, and enables 8-bit and 4-bit quantization of Rene for faster inference without any quality degradation.

[04] Sonic On-Device Private Beta

1. What is Sonic On-Device? Sonic On-Device is the first ultra-realistic generative voice model that supports low-latency real-time streaming on-device. It has the same capabilities as the cloud-based Sonic model, including instant cloning and controllable pronunciation, speed, and emotion.

2. What are the key benefits of Sonic On-Device? Sonic On-Device enables the development of on-device personal assistants, real-time translation, and dubbing applications, while providing the benefits of low latency, privacy, and availability without network connectivity.