Introduction The efficacy of semantic search relies on the accuracy of the underlying Knowledge Graph (KG). In high-velocity domains like on-demand food delivery or e-commerce, the catalog of entities like dishes, products, and merchants changes rapidly. Current methods for KG construction and maintenance face three critical challenges: Inaccuracy and hallucination from Large Language Models (LLMs): Automated models often infer relationships based on statistical text co-occurrence rather than semantic reality. For instance, an LLM might incorrectly classify “Pho” as a child of “Italian Noodle…
A few weeks ago, we spoke at OpenSearchCon India about how we make search fast and reliable at scale at Blinkit.I’m Harshit, from the Search Engineering team at Blinkit, and this year we got to speak at OpenSearchCon India at the Jio World Convention Centre in Mumbai. In this post, I’ll walk you through our talk, the conversations that followed, and what our team took away from being part of the OpenSearch community in a more active way this year.First Day : Keynote by BlinkitThe highlight of this year’s conference for our team was the opportunity to deliver a keynote session at…
The Importance of Offline Evaluation to Guide Model ChoiceIntroductionRecent advancements in open-source AI models make it challenging to justify the development of custom models, given the high quality of existing options. This also applies to embedding models, which are available in impressive quality.At OLX, we utilize a model called Item2vec to generate similar item recommendations. For more details, please refer to our blog post.Item2Vec: Neural Item Embeddings to enhance recommendationsIn this work, we developed an embedding model that not only improved recommendations but was also used…
Authored By Rohit Gupta & Siddhartha DevapujulaIntroductionMillions of users visit Myntra daily to upgrade their wardrobes and millions of items are listed on the platform at any given time. Users neither have the time nor the capability to scroll through this vast list of items. Even after applying category and attribute filters, usually the number of items is still in thousands. Hence it becomes critical that the top search results for any user are both relevant and personalized. Just like search, many other recommendation widgets across the platform face the same challenges.Fashion…
First and foremost, I express my gratitude for stopping by my corner of the internet! I trust that the content that follows will provide valuable insights and prove beneficial to individuals interested in the Machine Learning Engineer(MLE) internship opportunity at Strava or just general ML work.About meGreetings from Shuyi! Currently a fifth-year Ph.D. candidate in Statistics at ASU, I am thrilled to be embarking on an MLE Internship at Strava, Pearl in Ocean!Despite my passion for hiking and frequent search for routes, I hadn’t yet come across the Strava App (a missed opportunity indeed).…
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