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Advancements in Text Generation and Deployment of Large Language Models

12:50
 
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Manage episode 433947787 series 3550973
Simply News from Qurrent에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Simply News from Qurrent 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Researchers develop a Python library for Minimum Bayes Risk (MBR) decoding, revolutionizing text generation. MLC LLM offers a universal deployment engine for large language models (LLMs), simplifying the deployment process. LLMs enhance OCR post-correction, improving accuracy in text recognition systems. Amazon unveils a new era in code suggestion tools with multi-pass refinement. Explore the latest advancements in text generation and the deployment of large language models in AI.
Sources:
https://www.marktechpost.com/2024/08/13/mbrs-a-python-library-for-minimum-bayes-risk-mbr-decoding/
https://www.marktechpost.com/2024/08/13/mlc-llm-universal-llm-deployment-engine-with-machine-learning-ml-compilation/
https://www.marktechpost.com/2024/08/13/large-language-models-llms-for-ocr-post-correction/
https://www.marktechpost.com/2024/08/12/outperforming-existing-models-with-multi-pass-refinement-this-ai-paper-from-amazon-unveils-a-new-era-in-code-suggestion-tools/
Outline:
(00:00:00) Introduction
(00:00:55) MBRS: A Python Library for Minimum Bayes Risk (MBR) Decoding
(00:03:13) MLC LLM: Universal LLM Deployment Engine with Machine Learning ML Compilation
(00:06:09) Large Language Models LLMs for OCR Post-Correction
(00:08:58) Outperforming Existing Models with Multi-Pass Refinement: This AI Paper from Amazon Unveils a New Era in Code Suggestion Tools
  continue reading

104 에피소드

Artwork
icon공유
 
Manage episode 433947787 series 3550973
Simply News from Qurrent에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Simply News from Qurrent 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Researchers develop a Python library for Minimum Bayes Risk (MBR) decoding, revolutionizing text generation. MLC LLM offers a universal deployment engine for large language models (LLMs), simplifying the deployment process. LLMs enhance OCR post-correction, improving accuracy in text recognition systems. Amazon unveils a new era in code suggestion tools with multi-pass refinement. Explore the latest advancements in text generation and the deployment of large language models in AI.
Sources:
https://www.marktechpost.com/2024/08/13/mbrs-a-python-library-for-minimum-bayes-risk-mbr-decoding/
https://www.marktechpost.com/2024/08/13/mlc-llm-universal-llm-deployment-engine-with-machine-learning-ml-compilation/
https://www.marktechpost.com/2024/08/13/large-language-models-llms-for-ocr-post-correction/
https://www.marktechpost.com/2024/08/12/outperforming-existing-models-with-multi-pass-refinement-this-ai-paper-from-amazon-unveils-a-new-era-in-code-suggestion-tools/
Outline:
(00:00:00) Introduction
(00:00:55) MBRS: A Python Library for Minimum Bayes Risk (MBR) Decoding
(00:03:13) MLC LLM: Universal LLM Deployment Engine with Machine Learning ML Compilation
(00:06:09) Large Language Models LLMs for OCR Post-Correction
(00:08:58) Outperforming Existing Models with Multi-Pass Refinement: This AI Paper from Amazon Unveils a New Era in Code Suggestion Tools
  continue reading

104 에피소드

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