A Needle in a Haystack: A Guide to Scale Up Your Billion-Vector Space
In this workshop, we will explore efficient methods and approaches for performing queries in a billion-dimensional vector space. In recent years, we have accumulated vast amounts of data and transformed them into meaningful embedding vectors using machine learning models.
As a result, there are now numerous use-cases where we need to find the closest match from a large set of high-dimensional vectors. However, exhaustive search is not feasible due to its high computational cost and time limitations.
To address this challenge, we will focus on techniques and practices implemented in the FAISS library. We will identify the basic indexes and provide solutions to make the billion-scale problem achievable.
As a result, there are now numerous use-cases where we need to find the closest match from a large set of high-dimensional vectors. However, exhaustive search is not feasible due to its high computational cost and time limitations.
To address this challenge, we will focus on techniques and practices implemented in the FAISS library. We will identify the basic indexes and provide solutions to make the billion-scale problem achievable.
Speaker
Kostas Eftaxias
Sr Data Scientist, Orfium
Connect with Kostas Eftaxias on:
From the Same Track
November, 2
12:50 -
13:10 EEST
Quick Session
Using AI to optimize 5G Networks
To tackle the flexibility and complexity of 5G networks, we need solutions that prioritize security, reliability, and resource allocation for customers. These solutions should be dynamic, robust, and trustworthy, while also reducing the environmental impact of the networks.
Artificial Intelligence (AI) and Machine Learning (ML) have gained global recognition as crucial tools for future networks. Christos Rizos, Head of Big Data, Analytics, AI, Orchestration at Intracom Telecom, will analyze how to strategically focus on AI & ML to drive innovation and maintain a competitive edge. The main objectives to be analyzed include:
1. Minimizing energy consumption and carbon footprint in 5G network deployments.
2. Proactively identifying and addressing performance and reliability issues.
3. Intelligently managing and mitigating interference.
3. Predicting and enhancing the Customer Network Experience.
4. Optimizing Network Planning.
Artificial Intelligence (AI) and Machine Learning (ML) have gained global recognition as crucial tools for future networks. Christos Rizos, Head of Big Data, Analytics, AI, Orchestration at Intracom Telecom, will analyze how to strategically focus on AI & ML to drive innovation and maintain a competitive edge. The main objectives to be analyzed include:
1. Minimizing energy consumption and carbon footprint in 5G network deployments.
2. Proactively identifying and addressing performance and reliability issues.
3. Intelligently managing and mitigating interference.
3. Predicting and enhancing the Customer Network Experience.
4. Optimizing Network Planning.
A.I. in Engineering
Intermediate
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