The global indexing of human thought + a dash of GPT3 = generative engines.
LLMS
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Symmetry Reduces Parameters Through Parameter Tying
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Symmetry can also exponentially reduce the number of parameters by parameter tying.
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Analysis of GPT-4 rumors and model capabilities
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GPT4 > ? https://
thealgorithmicbridge.substack.com/p/gpt-4-rumors
-from-silicon-valley
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How Artificial Intelligence Perceives The Mission District
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What does the Mission look like to an artificial intelligence? – Mission Local Read more here: https://
ift.tt/PBG1jz8 #ArtificialIntelligence #AI #DataScience #100DaysOfCode #Python #MachineLearning #BigData #DeepLearning #NLP #Robots #IoT -
Efficiently Scaling Transformer Inference Techniques
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Efficiently Scaling Transformer Inference Pope et al.: https://
arxiv.org/abs/2211.05102 #ArtificialIntelligence #DeepLearning #MachineLearning -
Hybrid AI Systems More Practical Than Full LLM Retraining
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I love the dramatic futurism here! But it's more likely they will be hybrid systems. You don't want to retrain a LLM everytime a Wikipedia page is changed, or a news item is published. (Plus, Google would be in the best place to deliver this new system, incrementally.)
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When We Realize We’re Just Stochastic Parrots
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what happens when we realize we were just stochastic parrots all along?
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LangChain 0.0.12 Release with AI21Labs and Manifest Integrations
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LangChain version 0.0.12 Two super exciting integrations! @AI21Labs integration (from a friend of @YuvalinTheDeep
) Integration with @HazyResearch
's manifest library (with help from @laurel_orr1
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Build Train Evaluate GPT Models NVIDIA NeMo Megatron
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Learn how to construct, train, and evaluate a GPT model using NVIDIA NeMo with Megatron on Jupyter Notebooks in a new free, hands-on lab from NVIDIA LaunchPad. Get started: https://
nvda.ws/3tm9ABs -
Model Capabilities Emerge with Scale: Sentiment Classification Study
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This is a wonderful study on the emergence of model capabilities with scale. It is remarkable to see sentiment classification working with 1 data point, and fascinating to see the effectiveness of chain of thought prompting growing with scale.