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MiniTorch: Open Source Deep Learning Framework for AI

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@miketamir

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25 October 2024 21h01

MiniTorch https://
bit.ly/4eIe7DV
#AI #MachineLearning #DeepLearning #LLMs #DataScience

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Meta FAIR releases new models, datasets and code details

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@aiatmeta

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25 October 2024 18h00

More details on all of the new models, datasets and code released by Meta FAIR last week

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Retrieving the Right Data from Multiple Sources in LLM Applications

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@abacusai

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25 October 2024 17h28

A major challenge in LLM applications is retrieving the right data from multiple sources based on the prompt. Here’s an informative guide on this.

AI and Machine Learning Tutorial with Bi/Cross-Encoders Deep Dive

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25 October 2024 15h35

If you enjoyed this tutorial: Find me →
@akshay_pachaar

Everyday, I write about AI and Machine Learning! Also, check our deep-dive on Bi/Cross-Encoders:

Combining Bi-Encoders and Cross-Encoders in RAG Systems

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25 October 2024 15h35

Combining Both in RAG Systems To get the best of both worlds: Retrieve: Use Bi-Encoders as embedding-model to efficiently retrieve top candidate documents. Rerank: Use Cross-Encoders to rerank these candidates for better accuracy. Check this out 7/n

CrossEncoders vs BiEncoders: Scalability Trade-offs in Similarity Scoring

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25 October 2024 15h35

Let's say you have 10,000 sentences, CrossEncoders would require computing similarity scores for about 50 Million sentence combinations (¹⁰⁰⁰⁰C₂), which can take hours while bi-encoder would do it in seconds. But we have a great use for cross encoders… 6/n

Bi-Encoders in RAG: Efficiency and Scalability Benefits

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25 October 2024 15h35

Bi-Encoders in RAG Bi-encoders are a great choice for embedding models! Why • Efficiency: Pre-compute embeddings for all documents and store them in a vector store.
• Scalability: Then use fast ANN to search over millions of vectors 4/n

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Introduction of Claude 3.5 Sonnet with enhanced coding performance

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@godofprompt

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25 October 2024 8h35

5/ Introducing Claude 3.5 Sonnet i'm excited to share that Claude 3.5 Sonnet delivers significant gains in coding—an area where it already led the field. Sonnet scores higher on SWE-bench Verified than all available models—including reasoning models like OpenAI o1-preview and