How do you say “catastrophic forgetting” in Cantonese?
@hardmaru
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Survey of Consciousness Theories and Potential for Conscious AI
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A nice survey of several prominent theories of consciousness, including recurrent processing, global workspace, higher-order, predictive processing, and attention schema theories. They claim there are “no obvious barriers to building conscious AI systems”. https://
arxiv.org/abs/2308.08708 -
Making AMD GPUs Competitive for LLM Inference with ROCm
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Making AMD GPUs competitive for LLM inference Worried about NVIDIA GPU shortage? This project aims to makes it possible to compile LLMs and deploy them on AMD GPUs using ROCm and get competitive performance. Article: https://
blog.mlc.ai/2023/08/09/Mak
ing-AMD-GPUs-competitive-for-LLM-inference
… Discussion: https://
reddit.com/r/MachineLearn
ing/comments/15ml8n0/project_making_amd_gpus_competitive_for_llm/
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Little Book of Deep Learning by François Fleuret Released
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Just received my Little Book of Deep Learning, by @FrancoisFleuret
. At only 150 pages, this will be a fun gem to browse through! The little book is also released under a creative commons license: https://
fleuret.org/francois/lbdl.
html
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Understanding: Human Intelligence vs Large Language Models
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Ingredients of Understanding A nice article by @dileeplearning about how human understanding is different from LLM “understanding” https://
dileeplearning.substack.com/p/ingredients-
of-understanding
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Breakthroughs in AI Don’t Always Require Moonshot Efforts
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A ‘moonshot’ is usually the last step involved in a breakthrough, and I’d argue that there are many breakthroughs even in AI that didn’t involve or require moonshot-style efforts.
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Google Brain’s flat structure enabled more impactful research than hierarchical moonshots
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This reminded me of how Google Brain worked when I joined. It was way less hierarchal than DeepMind. Researchers basically self-organized into 3-10 people projects, and given lots of freedom to pursue exploration. This led to more impactful research compared to ‘moonshots’ IMO.
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Edge Detection Limitations in Understanding Human Vision
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Why Edge Detection Doesn’t Explain Line Drawing “If human vision was just edge detection, then we would have already figured out how vision works a long time ago.” An excellent paper and blog post by @AaronHertzmann from 2021: https://
arxiv.org/abs/2101.09376 -
Running Deep Learning Models on M1 Mac mini
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I wonder if it'll still work if you start running deep learning models or an LLM on this M1 Mac mini.
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Imperfect approach with simplified tutorial link
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To some extent only. This approach is far from perfect. Here is a (simplified) tutorial from a while back: https://
github.com/hardmaru/slime
volleygym/blob/master/TRAINING.md
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