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Source channel @githubtrending · Post #14993 · Jul 24

#jupyter_notebook Retrieval Augmented Generation (RAG) helps large language models (LLMs) answer questions using up-to-date or private information by connecting them to external data sources, unlike fine-tuning which retrains the model on specific data. RAG is useful when you need current, dynamic information without costly retraining, making it ideal for tasks like customer support or knowledge management. Fine-tuning is better for deep expertise in a specialized field but requires more data and effort. Using RAG lets you get accurate, relevant answers quickly by combining the model’s language skills with fresh, specific data, improving usefulness and reliability. https://github.com/langchain-ai/rag-from-scratch

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Venture Village Wall 🦄

@venturevillagewall · Post #3912 · 01/18/2025, 10:00 AM

$51M Raised Across Multiple Startups Ten innovative startups secured funding in January 2025, totaling $51 million. Highlights include: - Merit Systems: $10M for an open-source economy. - Botika: $8M, leading in AI-generated fashion models. - Underdogs: $6.13M, focused on training entrepreneurs. - TrustUp: $5.18M in health tech innovation. - Elcogen: $5M in efficient fuel cell manufacturing. - Convergence Medical Robotics: $5M for medical robotics solutions. - Constelli: $3M in signal processing for defense. - Immunocure Discovery Solutions: $3M in AI drug discovery services. - Naco: $2.58M for nano coatings in fuel cells. - TalentMapper: $2.44M for talent management solutions. Read more: Merit Systems | Botika | Underdogs | TrustUp | Elcogen | Convergence Medical Robotics | Constelli | Immunocure Discovery Solutions | Naco | TalentMapper #StartupFunding#OpenSource#AI#FashionTech#Education#HealthTech#FuelCells#Innovation#SignalProcessing#DrugDiscovery#NanoTech#HydrogenEnergy#MedTech#VC