rmi
google-research
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rmi | google-research | |
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1 | 89 | |
51 | 31,440 | |
- | 1.5% | |
0.0 | 9.6 | |
almost 3 years ago | 8 days ago | |
Jupyter Notebook | Jupyter Notebook | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
rmi
We haven't tracked posts mentioning rmi yet.
Tracking mentions began in Dec 2020.
google-research
- Mastering ROUGE Matrix: Your Guide to Large Language Model Evaluation for Summarization with Examples
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Announcing xAI July 12th 2023
Our team is led by Elon Musk, CEO of Tesla and SpaceX. We have previously worked at DeepMind, OpenAI, Google Research, Microsoft Research, Tesla, and the University of Toronto. Collectively we contributed some of the most widely used methods in the field, in particular the Adam optimizer, Batch Normalization, Layer Normalization, and the discovery of adversarial examples. We further introduced innovative techniques and analyses such as Transformer-XL, Autoformalization, the Memorizing Transformer, Batch Size Scaling, and μTransfer. We have worked on and led the development of some of the largest breakthroughs in the field including AlphaStar, AlphaCode, Inception, Minerva, GPT-3.5, and GPT-4.
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OpenAI: AI systems will exceed expert skill level in most domains within the next 10 years!
How about Google Research https://research.google/
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Why Nobody Is Talking About Google muNet ?
Github
Github: https://github.com/google-research/google-research/tree/master/muNet
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Top 10 Best Vector Databases & Libraries
ScaNN (Scalable Nearest Neighbors, Google Research) → A library for efficient vector similarity search, which finds the k nearest vectors to a query vector, as measured by a similarity metric. Vector similarity search is useful for applications such as image search, natural language processing, recommender systems, and anomaly detection.
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Alternatives to Pinecone? (Vector databases) [D]
I'm curious if anyone has discovered a vector database that is compatible with the ScaNN method? (https://github.com/google-research/google-research/tree/master/scann)
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Train custom AI models on spreadsheet data with just a few clicks
For the purposes of demonstration, we trained OpenAI's Babbage model on Google's GoEmotions dataset which classifies emotions from 58k Reddit comments.
Hey u/habylab, you're right — I mentioned in my original comment that this was an example of training a model on the GoEmotions dataset from a spreadsheet.
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Run Clip on iPhone to Search Photos
Nice blog post.
I wonder if it's possible to speed up the search with something like https://github.com/google-research/google-research/tree/mast...
Also kind of surprising that something like this is not officially supported already! In my books that means this is a Good Idea
What are some alternatives?
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
fast-soft-sort - Fast Differentiable Sorting and Ranking
ML-For-Beginners - 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
faiss - A library for efficient similarity search and clustering of dense vectors.
Milvus - A cloud-native vector database, storage for next generation AI applications
TensorFlow-Examples - TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
ml-agents - The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
struct2depth - Models and examples built with TensorFlow
bootcamp - Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.
torchsort - Fast, differentiable sorting and ranking in PyTorch
ML-KWS-for-MCU - Keyword spotting on Arm Cortex-M Microcontrollers
Financial-Models-Numerical-Methods - Collection of notebooks about quantitative finance, with interactive python code.