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Over the next decade, we will witness the majority of classic compute shift to the edge giving life to groundbreaking new innovations in robotics, UAVs, automotive, healthcare and manufacturing and other important industries. While many organizations understand that the pursuit of machine learning and artificial intelligence is a necessity to stay competitive, as this innovation race at the edge unfolds, the journey to harness the power of ML presents formidable challenges. SiMa.ai is a machine learning company that has purpose-built the hardware and software platform required for any company to get started with and scale AI and computer vision at the edge.

The Rise of Edge ML

AI innovation is not relegated to data centers or smartphones, but the semiconductor industry has not created the technology to efficiently power everything in-between. Extending Generative AI, LLMs, and vision transformers into IoT, industrial IoT, security, defense, automotive, and any machine that exists between the smartphone and data center, requires a new form factor where hardware and software are optimized to increase performance and save energy to meet the requirements of the edge.  

The cloud, while a valuable tool for many AI applications, falls short in delivering real-time AI and ML capabilities. The industry is now trying to force the same chips built for data centers, personal computing and mobile phones into servicing everything from autonomous vehicles to smart manufacturing, and robotics, to drone delivery. These chips were never intended for these use cases and to run such large algorithms within the constraints of an edge or low powered device. To reach the future of smart cars and robot assistants that innovators are working towards, it’s imperative to design both software and hardware in parallel to optimize for low latency, which a cloud warehouse miles away from the tech it runs simply cannot promise. 

Visualize robotics in a production line that before would be tripped up by a misalignment of products on a shipping conveyor belt that can now optimize and handle any configuration thrown its way. That’s real time inference. Or a consumer packaged goods company wasting supplies and resources on defective products who can now identify the exact point of quality control issues before shipping millions of dollars of product that will not materialize into revenue. Or a more intelligent medical device that helps identify potential conditions and complements a physician’s in-the-moment diagnostics ability. In all of these cases there’s no room for the time spent on cloud latency.

Critical real life ML applications at the edge demand real time inferencing; the latency bar at the edge cannot be met by traditional cloud based approaches. Human beings live at the edge and this is just the beginning for how ML will transform everyday machines. 

A New ML Performance Standard for the Embedded Edge

To realize the potential of edge ML, organizations need to be equipped with an entirely new approach, one that gives machines and devices the vision, speed, efficiency, and reasoning of real-world environments. SiMa.ai is the machine learning company delivering purpose-built solutions for and setting a new performance and efficiency standard for the edge. The company was founded on the premise of solving any computer vision application challenge with 10x better performance per watt, delivered in a push-button experience. 

In the edge AI sector, where both performance and energy efficiency are paramount, the standout metric is FPS/Watt. This metric is not just a number; it’s a critical indicator of how many frames a system can process per watt of electricity consumed. This is vital for edge AI workloads, where energy constraints often pose significant challenges. SiMa.ai’s purpose-built MLSoc is the linchpin of SiMa’s success in achieving unparalleled power efficiency. Engineered with precision, SiMa.ai is optimized for low power consumption without compromising performance. It’s not just about doing more; it’s about doing more with less—less energy, less cost, and less environmental impact. SiMa.ai focuses on power efficiency to meet the needs of customers, who are increasingly concerned with sustainable, efficient and performant computing.

SiMa consistently outperforms legacy competitor solutions in customer trials on a FPS/Watt basis and has earned some of the highest scores in the realm of ML Perf benchmarks for 2023 in the Closed Edge Power category, both in April (see: SiMa.ai Wins MLPerf™ Closed Edge ResNet50 Benchmark Against Industry ML Leader) and again in August (see: Breaking New Ground: SiMa.ai’s Unprecedented Advances in MLPerf™ Benchmarks) of this year. 

SiMa.ai’s ML Perf benchmark ratings are a powerful testament to SiMa.ai’s unwavering commitment to excellence in both performance and power efficiency, validating SiMa.ai MLSoc’s ability to provide a software user experience with SiMa.ai Palette™ that is “push button” easy.

Simplify Compute at the Edge with No Code ML

SiMa.ai Palette software is designed for complete ML stack application development. The platform supports any ML workflow that customers plan to deploy on the edge without compromising on performance and ease of use. Palette Edgematic, a visual extension of SiMa.ai’s Palette software platform, is a new browser-based development environment available to any organization looking to create, evaluate and fine tune ML applications at the edge at no cost.

Palette Edgematic enables a “drag and drop,” code-free approach where users can create, build and deploy their own models and complete computer vision pipelines automatically in minutes versus months, while evaluating the performance and power consumption needs of their edge ML application in real time. ML applications developed with Palette Edgematic can later be deployed and executed with the purchase of a SiMa Developer or Production board.

With Palette Edgematic, anyone with a computer vision pipeline concept can evaluate it directly on an edge device without an intermediate simulation in the cloud, providing a direct path to implementation at the edge. With Palette Edgematic, a developer can:

• Rapidly prototype and evaluate ML pipelines on edge devices in minutes; 
• Use real-time data streams to measure KPIs and then use the Palette Edgematic new visual canvas to rapidly iterate design to improve pipeline performance, eliminating the specialized embedded coding translation for edge ML implementations; 
• Utilize the automated build capabilities of Palette to convert visual representations of the pipeline to executable code with the push of a button; 
• Convert ML pipelines to demonstrable proofs of concept in as little as five minutes, speeding the concept to production deployment and reducing time to market. 

Powered remotely by SiMa.ai MLSoC, the initial release of Palette Edgematic delivers a GUI based visual experience to evaluate five optimized pipelines and 40 different models covering object detection, tracking, classification, semantic segmentation and instance segmentation use cases. 

Palette Edgematic empowers any individual, developer or organization to create production-ready ML applications in minutes versus months – freeing them of the complexity of executing ML at the edge, the uncertainty of how to get started, and the angst of how to AI-enable their product or service. 

With the introduction of Palette Edgematic, SiMa.ai now more than ever, is a software company building its own silicon, putting the potential of ML in the hands of everyone, its customers, partners, and the ML community.

Build your computer vision ML Application in 5 minutes with SiMa.ai’s Palette Edgematic today.