Yea. Maybe the real skill that will replace coders will be knowing which AI model is best for every potential scenario.
MACHINE LEARNING
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Matryoshka Retriever: High Performance Vector Search Technique
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Matryoshka Retriever A recent blog post by @supabase described a new technique for higher performance retrieval, without compromising accuracy. So we've just released a new retriever in LangChain.js which implements this exactly! Use any vector store, and two embedding
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LangChain Matryoshka Retriever Documentation and Supabase Integration
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Read the JS docs: https://
js.langchain.com/docs/modules/d
ata_connection/retrievers/matryoshka_retriever
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Supabase article: -
Free Learning Resources for Python, ML, and Data Science
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Learn for FREE: Python → http://
cs50.harvard.edu/python/2022/ Linear Algebra & Statistics → http://
khanacademy.org SQL → http://
sqlbolt.com Machine Learning → http://
deeplearning.ai MLOps → http://
madewithml.com Practice → http://
Kaggle.com -
Easter Egg Found in Bengio’s 2015 Deep Learning Paper
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Just found an Easter Egg!!!! @ikamalhaasan image in this #ai #deeplearning 2015 paper by Yoshua Bengio and his team. https://
arxiv.org/pdf/1507.01053
.pdf
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Choosing Between Euclidean and Manhattan Distance Metrics
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Hi Amit, It depends on the use case, Euclidean distance is prefered if you have a continuous and normally distributed data and Manhattan if your input variables are not similar in type i.e categorical features.
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PayPal Optimizes Data Processing with Spark RAPIDS GPU
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At #GTC24, learn how @PayPal used Spark RAPIDS with NVIDIA #GPUs to optimize data processing and address challenges with big data and #machinelearning. Register now for #GTC so you can attend this session on March 20. https://t.co/ChjPxuj2Nf pic.twitter.com/FyZuBzerkD
— NVIDIA AI (@NVIDIAAI) 1 mars 2024At #GTC24, learn how @PayPal used Spark RAPIDS with NVIDIA #GPUs to optimize data processing and address challenges with big data and #machinelearning. Register now for #GTC so you can attend this session on March 20. https://
nvda.ws/48vPTtb -
AI as Automated Statistical Inference: Definition and Scope
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AI simply means automated statistical inference here. The algorithms, data and setup have very little in common beyond this.
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The Complexity and Unreliability of Prompt Engineering Explained
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Prompt engineering gets very complicated and unreliable very soon. You are essentially programming with the convenience of natural language but without the precision of computer code. It also suffers from all the problems of solving a machine learning problem using logical
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Advanced RAG Series: Indexing Optimization Techniques
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Advanced RAG series: Indexing Indexing is a huge part or RAG. Lot's of different stuff to optimize: 1. Chunk Optimization
2. Multi-representation indexing
3. Specialized Embeddings
4. Hierarchical Indexing Great article by @divyanshu_van diving into all these topics! Blog: