Amin Ahmad - CTO, Vectara - Algolia / Elasticsearch-like search product on neural search principles

YouTube: https://www.youtube.com/watch?v=e2tZ6HD4I44Update: ZIR.AI has relaunched as Vectara: https://vectara.com/Topics:00:00 Intro00:54 Amin’s background at Google Research and affinity to NLP and vector search field05:28 Main focus areas of ZIR.AI in neural search07:26 Does the company offer neural network training to clients? Other support provided with ranking and document format conversions08:51 Usage of open source vs developing own tech10:17 The core of ZIR.AI product14:36 API support, communication protocols and P95/P99 SLAs, dedicated pools of encoders17:13 Speeding up single node / single customer throughput and challenge of productionizing off the shelf models, like BERT23:01 Distilling transformer models and why it can be out of reach of smaller companies25:07 Techniques for data augmentation from Amin’s and Dmitry’s practice (key search team: margin loss)30:03 Vector search algorithms used in ZIR.AI and the need for boolean logic in company’s client base33:51 Dynamics of open source in vector search space and cloud players: Google, Amazon, Microsoft36:03 Implementing a multilingual search with BM25 vs neural search and impact on business38:56 Is vector search a hype similar to big data few years ago? Prediction for vector search algorithms influence relations databases43:09 Is there a need to combine BM25 with neural search? Ideas from Amin and features offered in ZIR.AI product51:31 Increasing the robustness of search — or simply making it to work55:10 How will Search Engineer profession change with neural search in the game?Get a $100 discount (first month free) for a 50mb plan, using the code VectorPodcast (no lock-in, you can cancel any time): https://zir-ai.com/signup/user