Wednesday, October 27, 2021
Enterprises with AI experience face an upward struggle, as research demonstrates that only 53% of AI projects make it from prototype to production. This issue can largely be attributed to difficulties navigating the cumbersome deep learning lifecycle given that new features and use cases are stymied by limited hardware availability, slow and ineffective models, wasted time during development cycles, and financial barriers. AI developers need better tools that examine and address the algorithms themselves; otherwise, they will keep getting stuck. However, there just is not one tool available on the market that gives developers production-grade performance while still being flexible and user-friendly. In this talk, Yonatan presents an innovative and unique solution to this problem- using AI to craft the next generation of AI. Yonatan developed an Automated Neural Architecture Construction engine (AutoNAC), the first commercially viable Neural Architecture Search (NAS) technology set to unlock a whole set of AI opportunities for cloud, on-prem, edge deployments, and more. His engine is capable of crafting state-of-the-art deep neural networks that can outperform top-notch open-source neural nets currently available on the market.