Nissim Halabi

Title: Nissim Halabi: Innovator in Voice Notification and Data Search Technologies

Introduction

Nissim Halabi is a prominent inventor based in Ramat Gan, Israel. He has made significant contributions to the fields of data search and voice notification technologies. With a total of 3 patents to his name, Halabi continues to push the boundaries of innovation in his field.

Latest Patents

One of Halabi's latest patents is a "System for nearest neighbor search of dataset." This invention improves low latency search for nearest neighbors in a dataset containing a large number of entries by utilizing an error correction code (ECC) for partitioning data into clusters and retrieval. During the initialization and preprocessing phase, a d-dimensional space with clusters corresponding to ECC codewords is specified. Entries in the dataset are embedded into this space and associated with respective codewords, each codeword specifying a cluster. An index associates the codewords, clusters, and entries. During a query of the dataset, a query entry is processed to determine a query embedding in the d-dimensional space. The query embedding is used as input for a list decoder of the ECC, which provides a set of nearest codewords representing candidate clusters that may contain nearest neighbors. The dataset entries associated with these candidate clusters are then searched to determine query results comprising specific entries.

Another notable patent is for "Adaptive targeting for proactive voice notifications." This invention describes devices and techniques for adaptive targeting of voice notifications. In various examples, first data representing a predicted likelihood that a first user will interact with first content within a predefined amount of time is received. A first set of features, including those related to past voice notifications sent to the first user, is determined. A second set of features, including those related to interaction with the first content when past voice notifications were sent, is also received. A first machine learning model generates a prediction that a voice notification will increase the probability that the first user interacts with the first content based on the first data, the first set of features, and the second set of features. Audio data comprising the voice notification is then sent to a first device associated with the first content.

Career Highlights

Nissim Halabi is currently employed at Amazon Technologies, Inc., where he continues to develop innovative solutions that enhance user experience and data processing capabilities. His work at Amazon has allowed him to explore cutting-edge technologies and contribute to significant advancements in the industry