Updated: Jul 1
The webinar was presented by Gad, the CTO and founder of TensorOps, a consulting company that helps organizations build better AI practices, in collaboration with Superwise - an advanced ML Monitoring platform. This webinar is part of our search relevance series, including the article from Claudio Lemos about optimizing search results in Elasticsearch.
In the webinar we discussed the basics of search and its importance for different industries, and how LLMs (large language models) have revolutionized the search experience. we emphasized the importance of having a good search engine for e-commerce businesses and highlighted how machine learning can be used to improve the relevance of search results.
We also discussed the challenges of determining search relevance and the need to use multiple signals to estimate relevance, including click-through rates (CTR) and user behavior and feedback. He also mentioned the concept of drift, where the data coming into the model during inference may differ from the data used during training, leading to potentially less accurate results.
We concluded the first part of the presentation by discussing the implementation of a machine learning model in terms of architecture and emphasized the need for explicit data labeling, which requires a labeling tool and human input.
The webinar provided insights into the importance of search and how machine learning can be used to improve search results, and highlighted the collaboration between TensorOps and Superwise in this field.