Researchers at Microsoft AI propose LLM-ABR, a machine learning system that utilizes LLMs to design adaptive bitrate algorithms. Alibaba-Qwen releases Qwen1.5 32B, a new multilingual dense LLM. Plus, OpenAI introduces improvements to the fine-tuning API and expands its custom models program. Also, navigating the challenges and opportunities of synthetic voices with OpenAI's Voice Engine.
Sources:
https://www.marktechpost.com/2024/04/06/researchers-at-microsoft-ai-propose-llm-abr-a-machine-learning-system-that-utilizes-llms-to-design-adaptive-bitrate-abr-algorithms/
https://www.marktechpost.com/2024/04/06/alibaba-qwen-releases-qwen1-5-32b-a-new-multilingual-dense-llm-with-a-context-of-32k-and-outperforming-mixtral-on-the-open-llm-leaderboard/
https://openai.com/blog/introducing-improvements-to-the-fine-tuning-api-and-expanding-our-custom-models-program
https://openai.com/blog/navigating-the-challenges-and-opportunities-of-synthetic-voices
Outline:
(00:00:00) Introduction
(00:00:49) Researchers at Microsoft AI Propose LLM-ABR: A Machine Learning System that Utilizes LLMs to Design Adaptive Bitrate (ABR) Algorithms
(00:04:42) Alibaba-Qwen Releases Qwen1.5 32B: A New Multilingual dense LLM with a context of 32k and Outperforming Mixtral on the Open LLM Leaderboard
(00:07:45) Introducing improvements to the fine-tuning API and expanding our custom models program
(00:12:27) Navigating the Challenges and Opportunities of Synthetic Voices
view more