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Advancements in Text Generation and Deployment of Large Language Models

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Manage episode 433947787 series 3550973
Indhold leveret af Simply News from Qurrent. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Simply News from Qurrent eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.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 episoder

Artwork
iconDel
 
Manage episode 433947787 series 3550973
Indhold leveret af Simply News from Qurrent. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Simply News from Qurrent eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.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 episoder

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