Mohammad Musa, Founder and CEO, Deepen AI, Inc.
Sahil Potnis, Director, Business Development, Deepen AI, Inc.
Physical AI applications in the space of automotive, autonomous vehicles, and (largely) robotics require diversely curated datasets to iteratively develop and verifiably deploy the products in the real world environment. Existing data generation, curation and value extraction methods are distributed, expensive and present a steep operational - technical Curve; moving the primary focus away from building the actual inference - reasoning AI models necessary for such safety critical applications.
Deepen Refinery is an unified managed pipeline that transforms raw physical AI data into actionable data insights for product Validation and ODD expansion. In this talk, Deepen will provide a first unveil that demonstrates the product value to its audience in three broad stages: Data collection → PII processing → Data curation → Data enrichment & Validation. It reinforces the notions of data relevance and quality (over data volumes) necessary for taking the physical AI products through the end-to-end Verification and Validation in the landscape of upcoming regulations.
The conversation will provide a live experience of a featured Use-Case that Deepen AI has executed on its Refinery platform with the support of its certified partners. Through this power of commoditized datasets and a buffet of data enrichment options, Deepen intends to solidify its position as a Physical AI data engine technology leader and accelerate the end-to-end AV / ADAS deployment.