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The Future of Serverless Inference for Large Language Models

Unite.AI

On complementary side wrt to the software architect side; to enable faster deployment of LLMs researchers have proposed serverless inference systems. In serverless architectures, LLMs are hosted on shared GPU clusters and allocated dynamically based on demand. This transfers orders of magnitude less data than snapshots.

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Watch Our Top Virtual Sessions from ODSC West 2023 Here

ODSC - Open Data Science

You’ll cover the integration of LLMs with advanced algorithms in DataGPT, with an emphasis on their collaborative roles in data analysis. You’ll take a deep dive into DataGPT’s technology stack, detailing its methodology for efficient data processing and its measures to ensure accuracy and consistency.

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Training Sessions Coming to ODSC APAC 2023

ODSC - Open Data Science

Troubleshooting Search and Retrieval with LLMs Xander Song | Machine Learning Engineer and Developer Advocate | Arize AI Some of the major challenges in deploying LLM applications are the accuracy of results and hallucinations. Finally, you’ll explore how to handle missing values and training and validating your models using PySpark.

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How Mend.io unlocked hidden patterns in CVE data with Anthropic Claude on Amazon Bedrock

AWS Machine Learning Blog

The ability to process and understand natural language data at scale, combined with the predictive power of ML algorithms, could revolutionize threat intelligence gathering, enabling organizations to anticipate and proactively defend against emerging cyber threats. In his spare time Gili enjoys family time and Calisthenics.