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September 12th, 2023 - Frontiers in AI: From Pint-Sized Powerhouses and Pruned Datasets to Multilingual Mastery and Image Restoration

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Manage episode 376764872 series 3485608
Content provided by Marcus Edel. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Marcus Edel or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
  continue reading

Chapters

1. Intro (00:00:00)

2. Textbooks Are All You Need II: phi-1.5 technical report (00:02:20)

3. DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior (00:04:42)

4. When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale (00:05:59)

5. MADLAD-400: A Multilingual And Document-Level Large Audited Dataset (00:07:21)

6. FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning (00:08:32)

7. Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs (00:10:01)

75 episodes

Artwork
iconShare
 
Manage episode 376764872 series 3485608
Content provided by Marcus Edel. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Marcus Edel or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
  continue reading

Chapters

1. Intro (00:00:00)

2. Textbooks Are All You Need II: phi-1.5 technical report (00:02:20)

3. DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior (00:04:42)

4. When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale (00:05:59)

5. MADLAD-400: A Multilingual And Document-Level Large Audited Dataset (00:07:21)

6. FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning (00:08:32)

7. Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs (00:10:01)

75 episodes

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