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Vector Embeddings
within Conversational
AI
wednesday.is
Presented by: Saurabh Suman
2
Content
What we’ll be covering
Introduction to Vector Embeddings
Why Embeddings?
Importance in ConversationalAI
Challenges
Conclusion & Q&A
wednesday.is
Introduction to
Vector
Embeddings
Representing words as numbers
Converting words/phrases into vectors
Machines understand numbers, not words
wednesday.is
Why
Embeddings?
Text is vast and deep
Machines find it challenging to navigate,
embeddings act as a compass
Enables mathematical operations on words
wednesday.is
Why
Embeddings?
wednesday.is
Why
Embeddings?
wednesday.is
Importance in
ConversationalAI
Enhanced Understanding
Personalised Interaction
Seamless Conversations
Conversing naturally with users
wednesday.is
Types of
Embeddings
Word2Vec
GloVe
FastText
BERT & Transformers
wednesday.is
Types of
Embeddings
Word2Vec
wednesday.is
Types of
Embeddings
GloVe
wednesday.is
Challenges
Handling Out-of-Vocabulary Words
Cultural and Social Biases
Language Nuances and Idioms
Resource Constraints for
Lesser-Known Languages
Dynamic Meanings
Scalability and Efficiency
Interoperability
wednesday.is
Conclusion &
Q&A
Vector embeddings: The language of machines.
Pivotal in enhancingAI communication
and understanding.
Diverse techniques, each with unique strengths.
Central to modernAI applications,
yet challenges remain.
Apromising future with continuous evolution.
Thank you for your time!
wednesday.is

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Vector Embedding using AI