SiMa.ai Launches Modalix: A Game-Changing Chip for On-Device Physical AI

SiMa.ai Launches Chip to Run Reasoning-Based LLMs On-Device in Under 10 Watt | AIM

The new Modalix SoM and DevKit are now available, with pricing for the 8GB SoM starting at $349 and the 32GB version at $599. SiMa.ai, the US-based AI chip company, has launched its next-generation platform to accelerate the growth of Physical AI applications. The company introduced the Modalix Machine Learning System on a Chip (MLSoC) along with a new System-on-Module (SoM) and development kits, aiming to meet the growing demand for Physical AI in sectors like robotics, automotive, and healthcare. Modalix is a second-generation MLSoC designed to deliver high performance without compromising power efficiency, operating at less than 10 watts. "The era of Physical AI is here. With Modalix now in production, we're accelerating its global adoption," said Krishna Rangasayee, founder and CEO of SiMa.ai. Its flexible, Arm-based architecture enables real-time decision-making, natural language interaction, and

SiMa.ai launches its next-gen system-on-chip for physical AI into production - SiliconANGLE

SiMa.ai launches its next-gen system-on-chip for physical AI into production Artificial intelligence chip startup SiMa Technologies Inc. today announced it is shipping its second-gen system-on-chip platform specifically designed for multimodal physical AI workloads intended for embedding in robots, industrial equipment, vehicles and more. The new chip, named MLSoC Modalix, is designed for a system-on-module that matches the pin configuration and form factor of leading graphics processing units, enabling it to serve as the physical "brain" for edge devices running AI models. The chip allows companies to run various AI systems, including large language models such as Meta Platforms Inc.'s Llama models, convolutional neural networks, transformer models, vision language models, and other machine learning algorithms. Physical AI refers to the combination of artificial intelligence and physical systems, including robots, autonomous vehicles and smart devices. This integration enables these systems to perceive their environment, interact with it, and learn from their experiences. It combines AI algorithms, such as LLMs, so that they can process data from cameras and other sensors and then make decisions based on that information. This technology depends heavily on having low-power hardware that can handle computation at the edge, where small computers can process massive amounts of sensor data and run AI models directly in vehicles or robots without needing to offload them to the cloud. The further away from the action that data needs to be processed, the longer it takes for a round-trip for a reaction from a robot or a machine. This latency can make or break when safety or critical decisions must be made, or when networking is not available. The company originally debuted the Modalix machine learning SoC last year, but is announcing today that it's shipping the system and chipset, available immediately. According to SiMa.ai, the Modalix SoM will help operations address the diverse needs of the industry for different types of AI systems across the edge market by providing a chip that can handle many kinds of models and integrate easily into existing systems. SiMa.ai said it partnered with Synopsys Inc., a leading company in the field of electronic design and automation, to develop and innovate the new chip, accelerate design and achieve bug-free silicon in record time. "The development of Physical AI applications requires validated, purpose-built silicon and software that is only possible using the most advanced design solutions," said Ravi Subramanian, chief product management officer of Synopsys. In addition to the Modalix SoM, SiMa.ai introduced LLiMa, a unified on-device framework for running LLMs, VLMs and more on board. It enables developers to quickly import both open-source and custom AI models into Modalix-ready binaries, while also supporting numerous libraries for physical AI applications. VLMs, or vision language models, combine the capabilities of LLMs with visual reasoning, allowing them to process both text and images, which is fundamental for categorizing components of an image or video and understanding it. Combined with robotics or other systems, VLMs can be used to automate visual inspection of products and parts to identify defects and ensure quality standards, enable robots to understand and execute tasks based on natural language commands, track and monitor products through a supply chain, and more. "The era of Physical AI is here! With Modalix now in production, we're accelerating its global adoption," said Krishna Rangasayee, founder and chief executive of SiMa.ai. Rangasayee added that demand for the system-on-module has been strong leading up to the worldwide launch. The module and devkit are available from SiMa.ai today for enterprise deployments for 1,000 units, starting at $349 for 8GB SoM and $599 for 32GB SoM per unit. The devkit is priced at $1,499.