COMPUTE
AI MODELS
IN A CHIP
ORDERS OF MAGNITUDE FASTER
Next generation AI accelerator providing
superior efficiency and low power consumption
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TESTIMONIAL
"Based on current test results, we reduce biomarker selection from several days to a few minutes, enabling us to complete biomarker discovery for up to 10 times as many diseases per year."
Patrick Lilley, CEO, Liquid Biosciences
The problem
AI is exponentially integrating into every aspect of our personal and professional lives. This will not stop. Drastic technological leaps are needed to overcome impending challenges in transistor packaging, thermal management, energy consumption, and system complexity.
AI spending surge
Major AI players are spending billions, desperately trying to solve exponential market demand, without success.
None of them are developing fundamentally different approaches to both large- and micro-scale AI.
None of them are developing fundamentally different approaches to both large- and micro-scale AI.
Our solution
A new configurable learning engine: ultralight algorithms that require massively fewer transistors in a chip to train and use the same AI models.
Orders of magnitude faster and at a fraction of the cost and energy use of current AI methodologies.
Orders of magnitude faster and at a fraction of the cost and energy use of current AI methodologies.
Liquid Biosciences use case
Liquid Biosciences, EvoChip customer, is the leading AI biomarker discovery platform for diagnostics, prognostics, treatment response, and drug target discovery.
EvoChip helped them reduce biomarker selection from several days to a few minutes, allowing them to complete biomarker discovery for up to 10 times as many diseases per year.
EvoChip helped them reduce biomarker selection from several days to a few minutes, allowing them to complete biomarker discovery for up to 10 times as many diseases per year.
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