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Details

In this session, we are going to talk about:

  • How Gen AI actually works behind the scenes – from user prompt to tokenization, embeddings, vector databases, and similarity algorithms
  • What embeddings are and how semantic search really functions in modern AI systems
  • The difference between cosine similarity and Euclidean distance and why it matters for business applications
  • The architectural components of Gen AI systems, including vector databases and NL2SQL pipelines
  • The tradeoffs between Cloud AI solutions and On-Prem AI deployments
  • How major Gen AI platforms compare in terms of scalability, control, cost, and enterprise readiness
  • Why “Scale First” thinking is critical when implementing AI in large organizations

This session provides executives with the strategic clarity needed to make informed AI decisions, avoid common architectural mistakes, and align Gen AI initiatives with long-term business growth.

Language- Hebrew
Speaker: Omid Vahdaty
Omid is the Founder and CTO of Jutomate, a company that provides services and solutions in data, cloud, and AI.
He is an expert in data architecture, product innovation, and strategic engineering thinking, with over 20 years of experience across startups, global enterprises, and government organizations.

Related topics

Artificial Intelligence
Cloud Architecture
Google Cloud
Data Science

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