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EPISODE · Jun 20, 2024 · 6 MIN

How Amazon Bedrock Helps Build GenAI Apps in Python

from The New Stack Podcast · host Suman Debnath, Heather Joslyn

Suman Debnath, principal developer advocate for machine learning at Amazon Web Services, emphasized the advantages of using Python in machine learning during a New Stack Makers episode recorded at PyCon US. He noted Python's ease of use and its foundational role in the data science ecosystem as key reasons for its popularity. However, Debnath highlighted that building generative AI applications doesn't necessarily require deep data science expertise or Python. Amazon Bedrock, AWS’s generative AI framework introduced in September, exemplifies this flexibility by allowing developers to use any programming language via an API-based service. Bedrock supports various languages like Python, C, C++, and Java, enabling developers to leverage large language models without intricate knowledge of machine learning. It also integrates well with open-source libraries such as Langchain and llamaindex. Debnath recommends visiting the community AWS platform and GitHub for resources on getting started with Bedrock. The episode includes a demonstration of Bedrock's capabilities and its benefits for Python users. Learn More from The New Stack on Amazon Bedrock: Amazon Bedrock Expands Palette of Large Language Models Build a Q&A Application with Amazon Bedrock and Amazon Titan 10 Key Products for Building LLM-Based Apps on AWS Join our community of newsletter subscribers to stay on top of the news and at the top of your game/

Episode metadata supplied by the publisher feed · Published Jun 20, 2024

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Suman Debnath, principal developer advocate for machine learning at Amazon Web Services, emphasized the advantages of using Python in machine learning during a New Stack Makers episode recorded at PyCon US. He noted Python's ease of use and its foundational role in the data science ecosystem as key reasons for its popularity. However, Debnath highlighted that building generative AI applications doesn't necessarily require deep data science expertise or Python.

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