Assuming it is the software that enables or prevents the adoption of a new AI chip, a reasonable assumption, SiMa has created a new tool called Palette Edgematic to simplify AI solution creation greatly. And build demand for their silicon.
As everyone says, “It’s the software, stupid!” when it comes to porting AI models to a new piece of hardware. A vast repository of tools from NVIDIA would need rewriting and replacing in most software stacks, especially if you want to get the maximum performance out of your chip. That is a lot of challenging work.
But with Large Language Models , the community has done much of the work for you, at least to a first level of performance. Hugging Face, for example, has hundreds of open-source LLMs you can use free or at a smallish charge. And for makers of new hardware, like Cerebras or SiMa.ai, this provides a far better starting point.But most AI applications aren’t just one model. They are interconnected AI models, each performing a different task. SiMa.
Say you want to build an edge AI app to run Centernet, an object detection AI that detects each object as a triplet, rather than a pair, of keypoints, improving precision and recall with the new SiMa.ai Palette platform. As shown below, you can create a workflow from pre-processing, processing, and post-processing with a simple point-and-click interface.
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