Are you trying to solve the "hallucination problem" with LLMs? Check out the new Infosys blog series, "RAG Demystified." Part 1 breaks down the fundamentals of Retrieval-Augmented Generation (RAG), explaining how this powerful framework helps overcome LLM limitations by providing accurate, contextually relevant responses. A must-read for anyone who wants to build reliable AI solutions. Explore more, here: infy.com/46hH3QG #iCETS #ArtificialIntelligence #LLM #FutureProofingBusinesses #iCETSMarketing #iCETSPerspective Shyam Doddavula | Prakash C Pandurangan | Chetana Amancharla | Bhumika Singhal | Karthikeyan S. | Ronica Sharma | Soundharya Nalla
Learn how to solve the "hallucination problem" with LLMs using RAG. Read the Infosys blog series "RAG Demystified"
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Did you know you can save up to 50% of costs on AI models just by using Batch API calls? 💡 Batch is perfect for large-scale tasks that don’t need an immediate response. Think: Weekly reports Monthly analysis Bills or invoices Any task that can wait a few hours How it works: 👉 You pass in a JSONL file where each line is a request. 👉 The model processes it in bulk (can take up to 24 hours). 👉 You get back a JSONL file with the outputs. This is recommended for bigger, non-urgent workloads and works with both Gemini and OpenAI.
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Did you know you can save up to 50% of costs on AI models just by using Batch API calls? 💡 Batch is perfect for large-scale tasks that don’t need an immediate response. Think: Weekly reports Monthly analysis Bills or invoices Any task that can wait a few hours How it works: 👉 You pass in a JSONL file where each line is a request. 👉 The model processes it in bulk (can take up to 24 hours). 👉 You get back a JSONL file with the outputs. This is recommended for bigger, non-urgent workloads and works with both Gemini and OpenAI.
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Struck on the impact of explosion of data. With Cirata Symphony, Cirata can support the 88 pct of organisations that are overwhelmed by their data #ArtificialIntelligence #Analytics #Data
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📊 Looking to automate and scale your NLP tasks effortlessly? The n8n Hugging Face integration is your gateway to workflow automation on steroids! 🚀 1️⃣ **Enhanced Productivity**: Automate workflow processes, reducing manual effort and streamlining operations. 2️⃣ **Scalability**: Handle large volumes of data across various sectors with ease, from healthcare to finance. 3️⃣ **Flexibility**: Leverage Hugging Face models without repetitive coding. ✅ Key Takeaway: This integration connects n8n's powerful automation with Hugging Face's advanced machine learning models, unlocking remarkable efficiencies. Full explanation 👉 [Read full breakdown](https://lnkd.in/gctYvPrg) #NovamindLabs #SharadLamba #n8n #WorkflowAutomation #AutomationTools #AIForBusiness #Productivity
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📊 Looking to automate and scale your NLP tasks effortlessly? The n8n Hugging Face integration is your gateway to workflow automation on steroids! 🚀 1️⃣ **Enhanced Productivity**: Automate workflow processes, reducing manual effort and streamlining operations. 2️⃣ **Scalability**: Handle large volumes of data across various sectors with ease, from healthcare to finance. 3️⃣ **Flexibility**: Leverage Hugging Face models without repetitive coding. ✅ Key Takeaway: This integration connects n8n's powerful automation with Hugging Face's advanced machine learning models, unlocking remarkable efficiencies. Full explanation 👉 [Read full breakdown](https://lnkd.in/gSfWsQnq) #NovamindLabs #SharadLamba #n8n #WorkflowAutomation #AutomationTools #AIForBusiness #Productivity
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One of the most popular nodes in n8n- The Merge node. It lets you combine data from two or more previous nodes in several powerful ways: 1️⃣ Append – Like a SQL UNION, it simply stacks the data together. 2️⃣ Combine – Perform different SQL-style joins (Left, Inner, Outer, etc.). 3️⃣ By Position – Matches items based on their index. 4️⃣ SQL – Write your own custom merge logic. 💡 I just released a new video showcasing 16 practical examples of how to use the Merge node effectively. Check out the video in the comments below! What n8n videos should I work on next? #ai #n8n #aiautomation
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I find that many people have yet to try the new(ish) Snowflake PROMPT function. It constructs a structured object that many Cortex AISQL functions, such as AI_COMPLETE, can interpret. Here's an example of setting up a greeting and confusing a completion model with it. Link to the docs in the comments.
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Explore related topics
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