In-depth tutorials and resources for ML/AI system design, optimization, and implementation.

Joined August 2023
AWS Competition alert! WorldMind Evidence is designed for regulated industries such as pharmaceutical research, clinical trials, and regulatory submissions, where every claim must be verifiable and traceable to authoritative documentation. Check more: builder.aws.com/content/3AhF…
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Vector search doesn't always require new infrastructure. pgvector enables semantic capabilities in existing Postgres deployments—simpler ops, lower costs, fewer failure points. Specialized solutions matter at scale. Most projects aren't there yet.
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🤖 Pre-training: The expensive foundation phase where LLMs learn language 🎯 Fine-tuning: Specialized training for specific domains 🎓 Instruct-tuning: Teaching models to follow instructions better Understanding these training phases is key to working with LLMs models.
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Kokoro-82M is a new text-to-speech (TTS) model, delivering exceptional performance with only 82 million parameters. 🚀 🗣 The model achieves state-of-the-art performance with 82M parameters, outperforming 14x bigger models.
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💥 New query expansion models for RAG systems 💥 The collection addresses a common challenge in search and retrieval – bridging the gap between user queries and document content.
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We have another app in our collection
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Converting docs to Markdown and JSON? Every AI practitioner has encountered this situation: You possess thousands of documents in various formats—PDFs, Word files, Excel sheets, and web pages—that must be converted into a uniform format for your LLM training or AI workflow.
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Check out a new tool, which we released: monkt.com/ (Converting documents to Markdown and JSON at scale)
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Open-source tools like Microsoft’s MarkItDown (github.com/microsoft/markitd…), which provide solid foundations for document conversion. While these tools offer great processing capabilities, they present specific implementation challenges.
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