RAG & Fine Tuning in GenAI with Snowflake

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AIM in partnership with Snowflake is hosting an exclusive webinar on 25th July from 6 PM to 8 PM titled “RAG & Fine Tuning in GenAI with Snowflake”. 

This event is designed to provide AI enthusiasts, researchers, and professionals with a deep dive into the advanced techniques of retrieval augmented generation (RAG) and fine tuning, crucial for developing AI applications.

Meet the Expert: Prashant Wate

Prashant Wate, Senior Sales Engineer at Snowflake India, will lead this insightful session. With extensive experience in AI and enterprise solutions, Wate will guide the participants through the intricacies of RAG and fine-tuning, demonstrating how these techniques can revolutionise your AI projects.

Register Now!

What You Will Learn?

Understanding RAG and Fine Tuning

This webinar will clarify the differences between RAG and fine-tuning, alongside how and when to use these methods effectively. Gain practical knowledge and explore real-world applications that will set the stage for advanced AI innovations in your organisation.

Enhancing Generative Models with RAG

RAG is a technique designed to reduce hallucinations (incorrect responses) in generative models by integrating private datasets and vector embeddings. This method significantly boosts the capabilities of generative models, ensuring they align with your enterprise requirements.

Optimising Models with Fine-tuning

Fine-tuning involves adjusting pre-trained LLMs on a specific dataset to improve their performance on targeted tasks. This process is essential for optimising models to better understand and respond to domain-specific queries, ensuring higher accuracy and relevance in the generated outputs.

Leveraging Snowflake’s Platform

Discover how Snowflake’s robust platform for data governance and management can be leveraged to develop and deploy end-to-end AI applications using RAG. 

With features like Snowflake Cortex, Streamlit, and Snowpark, you can achieve this without the need for additional integrations, infrastructure management, or data movement.

Why Attend?

This webinar is particularly valuable for developers from GCC companies who are eager to enhance their skills and knowledge in Generative AI. By attending, you will be equipped with the tools and techniques needed to drive advanced AI innovations in your organisation.

Register Now!

Secure your spot for the AIM Workshop on 25th July from 6 PM to 7:30 PM. 

Register today and take the first step towards mastering RAG and fine-tuning with Snowflake.



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Disclaimer

We strive to uphold the highest ethical standards in all of our reporting and coverage. We StartupNews.fyi want to be transparent with our readers about any potential conflicts of interest that may arise in our work. It’s possible that some of the investors we feature may have connections to other businesses, including competitors or companies we write about. However, we want to assure our readers that this will not have any impact on the integrity or impartiality of our reporting. We are committed to delivering accurate, unbiased news and information to our audience, and we will continue to uphold our ethics and principles in all of our work. Thank you for your trust and support.

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RAG & Fine Tuning in GenAI with Snowflake


AIM in partnership with Snowflake is hosting an exclusive webinar on 25th July from 6 PM to 8 PM titled “RAG & Fine Tuning in GenAI with Snowflake”. 

This event is designed to provide AI enthusiasts, researchers, and professionals with a deep dive into the advanced techniques of retrieval augmented generation (RAG) and fine tuning, crucial for developing AI applications.

Meet the Expert: Prashant Wate

Prashant Wate, Senior Sales Engineer at Snowflake India, will lead this insightful session. With extensive experience in AI and enterprise solutions, Wate will guide the participants through the intricacies of RAG and fine-tuning, demonstrating how these techniques can revolutionise your AI projects.

Register Now!

What You Will Learn?

Understanding RAG and Fine Tuning

This webinar will clarify the differences between RAG and fine-tuning, alongside how and when to use these methods effectively. Gain practical knowledge and explore real-world applications that will set the stage for advanced AI innovations in your organisation.

Enhancing Generative Models with RAG

RAG is a technique designed to reduce hallucinations (incorrect responses) in generative models by integrating private datasets and vector embeddings. This method significantly boosts the capabilities of generative models, ensuring they align with your enterprise requirements.

Optimising Models with Fine-tuning

Fine-tuning involves adjusting pre-trained LLMs on a specific dataset to improve their performance on targeted tasks. This process is essential for optimising models to better understand and respond to domain-specific queries, ensuring higher accuracy and relevance in the generated outputs.

Leveraging Snowflake’s Platform

Discover how Snowflake’s robust platform for data governance and management can be leveraged to develop and deploy end-to-end AI applications using RAG. 

With features like Snowflake Cortex, Streamlit, and Snowpark, you can achieve this without the need for additional integrations, infrastructure management, or data movement.

Why Attend?

This webinar is particularly valuable for developers from GCC companies who are eager to enhance their skills and knowledge in Generative AI. By attending, you will be equipped with the tools and techniques needed to drive advanced AI innovations in your organisation.

Register Now!

Secure your spot for the AIM Workshop on 25th July from 6 PM to 7:30 PM. 

Register today and take the first step towards mastering RAG and fine-tuning with Snowflake.



Source link

Disclaimer

We strive to uphold the highest ethical standards in all of our reporting and coverage. We StartupNews.fyi want to be transparent with our readers about any potential conflicts of interest that may arise in our work. It’s possible that some of the investors we feature may have connections to other businesses, including competitors or companies we write about. However, we want to assure our readers that this will not have any impact on the integrity or impartiality of our reporting. We are committed to delivering accurate, unbiased news and information to our audience, and we will continue to uphold our ethics and principles in all of our work. Thank you for your trust and support.

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