Ah thanks for sharing! We included this in the newsletter for tomorrow but forgot to add it to the thread. The leak adds up, given the recent tanking of ChatGPTs performance
RESEARCH
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Stability AI Updates Stable Video Diffusion Model With Enhanced Motion
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Stability AI released the first update to its Stable Diffusion model, with enhanced motion and consistency in generations. Will 2024 be the year of open-source AI?
https://
x.com/i/status/17538
58278868545833/video/1
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MGIE: AI Image Editing via Natural Language Prompts
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Apple and UC Santa Barbara researchers introduced MGIE, an open-source AI system for editing images via natural language prompts.
— Rowan Cheung (@rowancheung) 8 février 2024
Image editing is about to get even easier: pic.twitter.com/0Txmnvm6NjApple and UC Santa Barbara researchers introduced MGIE, an open-source AI system for editing images via natural language prompts. Image editing is about to get even easier:
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Reddit Instruct Dataset Released for AI Research
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Huge thanks to @teknium for their work and to @Euclaise_ for providing the dataset! https://
huggingface.co/datasets/eucla
ise/reddit-instruct-curated
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Local Model Fine-tuning Tutorial and Data Formatting Guide
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If you are interested in learning more about fine-tuning models locally, consider following me. I will post a tutorial on how I did this fine-tuning, how I formatted the data, etc.
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Stanford AI Director Discusses AI FOMO and Risks at Davos
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As a panelist at Davos 2024, @StanfordHAI vice director @landay picked up on AI FOMO and real AI risks. Read his top insights from the event. #wef24 https://
stanford.io/3UyrnEj -
AI Ethics and Open-Source LLM Frameworks Future Trends
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From the evolving world of #AI ethics to the explosion of open-source #LLM frameworks, check out the latest episode of the #DataDriven Podcast w/ @devvret_rishi & @FrankDigsData to hear what's in store for the future. https://
pbase.ai/3Uwhg2G -
Parallel Batch Processing Optimization in Machine Learning
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what would that even mean? why would you not just combine “parallel” batches into a bigger batch?
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Weight Decay Impact on Model Training Speed
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what does increasing weight decay do in this case? I’d expect that to slow training down
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Autograd Backward Pass Implementation Progressing Successfully
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and here's a slightly less-zoomed backward pass. autograd is running, backward is happing, etc. etc. seems all fine and good to me