Differences between robotics and Artificial Intelligence
#AI #AIio #BigData #ML #NLU #Futureofwork @briansolis @Xbond49 @VitalikButerin @DataScienceCtrl @Benioff @johnnosta @IrmaRaste @Tiffani_Bova http://
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MACHINE LEARNING
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Differences between robotics and Artificial Intelligence explained
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Stanford CS224N: New 2023 Deep Learning NLP Lectures Available
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[New Lectures] Stanford CS224N: Natural Language Processing with Deep Learning Stanford NLP course is arguably one of the best Deep NLP courses on the web. The new lectures from 2023 iteration are public now. The course covers fundamental techniques and topics related to deep
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Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization
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An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization Shwartz-Ziv et al.: https://
arxiv.org/abs/2303.00633 #ArtificialIntelligence #DeepLearning #MachineLearning -
TinyML and Efficient Deep Learning for Resource-Constrained Devices
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TinyML and Efficient Deep Learning Computing MIT 6.5940 (
https://
efficientml.ai) “This course will introduce efficient AI computing techniques that enable powerful deep learning applications on resource-constrained devices. Topics include model compression, pruning, -
Pre-training evidence debated; reversal learning skepticism noted
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evidence for it in pre-training is just experiment 2 on celebrity parents — seems plausible but less clear than the SFT case imho. idk; LLMs generalize in pre-training in ways that become more impressive if reversal learning is known impossible so my prior is low
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AI Revolutionizing Online Gaming in India
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Artificial Intelligence in revolutionising online #gaming in #India! https://
hindustantimes.com/ht-insight/fut
ure-tech/artificial-intelligence-in-revolutionising-online-gaming-in-india-101695369679203.html?utm_source=twitter
… #gamedev #GameFi #game #Robotics #robot #OpenAI #bots #KillerRobot #roboticsainews #opensource #Python #tech #technology #cobot #humanoid #ML #Algorithms #Robotech #RobotDesign -
GPT-3 API knowledge update: “engine” vs “model”
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AFAIK GPT-3 always knew the basics of its own API but its knowledge was dated; seems it still is (“engine” instead of “model”). What changed here?
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Reversal curse: fine-tuning on A is B doesn’t instill B is A
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“reversal curse” — fine-tuning on “A is B” does not at all instill “B is A.” fantastic intuition builder for what SFT actually does. tuning doesn’t normally make a model conversant in new facts beyond their recitation — SFT isn’t “know this,” it’s “be this.”
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Keras 3 Installation: pip Package and Source Build Options
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The new keras isn't distributed via pip yet — until the official Keras 3 release. Either use the keras_core package from pip or build the new keras from source (it's a single command)