لماذا تدفع 300$ شهرياً مقابل RAG "خامل"؟ بناء أنظمة الـ RAG لا يعني بالضرورة فواتير باهظة. تعلم كيف تشحن Serverless RAG Pipeline على AWS بمواصفات تقنية مذهلة: التكلفة: تنخفض من مئات الدولارات إلى 2$ فقط. الأداء: Scale to Zero (لا تدفع إلا مقابل ما تستخدمه). الخصوصية: بياناتك بالكامل داخل حسابك في AWS. الشمولية: معالجة النصوص، الصور، الفيديو، والصوت. استخدم مشروع RAGStack-Lambda لتوفير تكاليف البنية التحتية دون التنازل عن القوة. الدليل العملي هنا: freecodecamp.org/news/how-to… #الذكاء_الاصطناعي

I don’t think this is necessary to make it work—you would need only need the knowledge graph to be a RAGstack and a way to tell the LLM where on the knowledge stack to start a given conversation/lesson.

🚀 Just dropped: MultiMind SDK — Your All-in-One Framework for Model-Agnostic LLMs 🔥 Fine-tuning, RAG, model conversion, multi-model routing, & more! 🧠 Built for devs who want control flexibility 💡 Open-source, modular, production-ready 📖 Read it here 👉 medium.com/@multimindsdk/mul… ⭐ Star us 👉 github.com/multimindlab/mult… 💙 Support 👉 opencollective.com/multimind… #MultiMindSDK #LLMDev #OpenSourceAI #MLOps #ModelConversion #FineTuning #RAGstack #BuildInPublic #PythonDev #AIInfra #WeekendBuilder

Coding from the clouds ☁️⛰️ Building MultiMindLab powered by @multimindsdk — where AI meets no-code 🚀 #multimindlab This view might be unreal, but the tech we’re launching is even wilder. #WorkFromAnywhere #DigitalNomadDev #MultiMindAI #NoCodeAI #LLMDev #BuildInPublic #OpenSourceAI #TechInNature #WeekendBuilder #RemoteLife #SideProjectSaturday #MultiMindsdk #LLMDev #ModelConversion #OpenSourceAI #RAGstack #PythonDev #BuildInPublic #WeekendBuilder #NightOwlDev #AIRevolution2025

🚀 Just shipped: Flow-based automatic schema inference for @qdrant_engine in @CocoIndex. No manual setup — 100 lines → production-ready AI pipelines. 🌟Repo: github.com/cocoindex-io/coco… 👀Read more: cocoindex.io/blogs/schema-in… Framework handles following automatically for you: ✅ Collection creation ✅ Vector size inference ✅ Schema sync on updates All backed by a high-perf Rust stack. #VectorDB #AIInfra #DevTools #Python #RustLang #DataEngineering #RAGstack #Qdrant #LLMinfra #OpenSource #Embeddings #DataPipelines #MLOps #AIstartup #CocoIndex

Build a Deep-Research Agent in a Day. Yes, really. The Gemini team just dropped a fully open-sourced, production-ready stack for autonomous research. Fork it. Deploy it. Iterate. 🔗 GitHub: lnkd.in/gP533554 What you get out of the box: → A polished UI (React Tailwind shadcn) → A Gemini-powered backend with FastAPI LangGraph → Real-time answer streaming → One-command dev setup with Docker Compose → Trace viewer to watch every step of reasoning Why it matters: → No more blank-slate agents → No more weeks of hacking a workflow → Every node is modular — just swap your own search API or internal docs Build your own: → Research copilots → Domain-specific RAG agents → Autonomous researchers with built-in reflection and citation This stack thinks before it speaks — and tells you where it learned it from. The catch? → It ships with Google Search only → Reflection happens in-prompt → Looping caps at a fixed number of rounds But all of this? Easily modifiable. If you’ve got a weekend and a use case, You’ve now got a working agent. No excuses. #AIEngineering #LangGraph #GeminiAgents #OpenSourceAI #ResearchTools #RAGStack #PaystackStyle #BuildFaster

**Chat with a website using LLM** AllyCat (github.com/The-AI-Alliance/a…) can - crawl a website - extract, clean chunk content - save to vector db - query using LLM Session: 🗓️ May 1, 2025 ⏰ 9am PT / 12 pm ET / 4pm GMT 👉 meetup.com/ibm-developer-sf-… #allycat @thealliance_ai #ragstack

🧠💸 New blog: What should AI cost? We break down: – what you're really paying for (it's not just tokens) – how much is too much for a sector-specific LLM – when DIY saves you money (and when it doesn't) – why Excel is still undefeated in certain scenarios. Plus: a handy checklist for anyone buying, building, or budgeting for AI. 📖 Read it here: leadingai.co.uk/blog/what-sh… #AI #GenAI #TechForGood #DigitalTransformation #RAGstack #BuildOrBuy #AICosts #PromptEngineering #PublicInterestTech #ExcelSupremacy

Generative AI Welcome to the research report on Generative AI, where you can find round-up features on Generative AI and GPT for the year on all the exciting applications and integrations related to Generative AI technologies. You must be hearing a lot of Generative AI tools, frameworks, and integrations throughout the year about applications and deployments centered on large language models (LLMs), so I thought it would be a beneficial service for our 𝕏 readers to write an article dedicated to this topic. These innovative companies are leveraging the power of LLMs, fine-tuned on proprietary data, to create cutting edge AI applications. With the field of AI advancing incredibly and rapidly, I want to help our audience stay up-to-date on the latest developments in Generative AI. NVIDIA has launched a new Generative AI Foundry service on Microsoft Azure to enterprises and startups worldwide Enterprises and startups worldwide can now leverage NVIDIA's new Generative AI Foundry service, designed to accelerate the development and fine-tuning of custom generative AI applications. This service has been launched on Microsoft Azure, making it even more accessible for those who want to use it. The NVIDIA AI foundry service offers enterprises a comprehensive solution for creating custom generative AI models by bringing together NVIDIA's AI Foundation Models, NeMo framework and tools, and DGX Cloud AI supercomputing services. With this solution, businesses can create and fine-tune their own generative AI models and deploy them using NVIDIA AI Enterprise software to power applications such as intelligent search, summarization, and content generation. Some industry leaders already building custom models using this service include SAP SE and Amdocs. Hammerspace releases Reference Architecture for Generative AI and LLMs Hammerspace, a data management company, recently announced its new reference architecture for ample language model training. The architecture is designed to provide a scalable, cost-effective solution for organizations looking to train their large language models. With Hammerspace's solution, businesses can train models with hundreds of billions of parameters. This could be a game changer for organizations that rely heavily on natural language processing, such as those in the healthcare or finance industries. Hammerspace has recently unveiled its data architecture for training inference for Large Language Models (LLMs) in hyperscale environments. This architecture enables AI technologists to design a unified data architecture that delivers the performance of a super computing-class parallel file system while providing ease of application and research access to standard NFS. For AI strategies to be successful organizations require the ability to scale to a massive number of GPUs, as well as the flexibility to access local and distributed data silos in the environment. In addition, they need to be able to leverage data regardless of the hardware or cloud infrastructure on which it currently resides, while also uphold data governance policies through robust security controls. This is especially critical in developing Large Language Models (LLMs), which often require hundreds of billions of parameters, tens of thousands of GPUs, and hundreds of petabytes of types of unstructured data and structured data. Google Cloud to Transform Product Management with Generative AI Google provides Vertex AI and Palm APIs for product teams and application owners with a range of features that help speed up product discovery, enhance product-led growth campaigns, and provide customized app experiences to the audience. LangChain's OpenGPTs project is powered by Redis Cloud. Redis, Inc., and LangChain are continuing their collaboration to enable developers and businesses to leverage the latest innovation in the fast-evolving landscape of Generative AI with the OpenGPTs project powered by Redis Cloud. As part of this partnership, LangChain is utilizing Redis Cloud as the extensible real-time data platform for the OpenGPTs project, which includes the new LangChain Template for Retrieval Augmented Generation (RAG) using Redis. LangChain's OpenGPTs is an open source project that offers a more flexible approach to Generative AI. People can choose their models, retrieve data, and manage where data is stored, providing a unique user-controlled experience. Integrated with LangSmith for advanced debugging, logging, and monitoring, OpenGPTs offers even more capabilities. Snow CoPilot Generative AI Snow CoPilot Generative AI is an exciting new development from Snow Software, a leader in AI technology intelligence. The AI-powered assistant is designed to help solve significant challenges in IT Asset Management (ITAM) and FinOps. Snow CoPilot would be the initial app in a series of AI capabilities developed in Snow Labs. It allows people to ask conversational questions and receive natural language responses, making the information they need accessible. Currently, Snow CoPilot is available for Software Asset Management (SAM) computer data in Snow Atlas, with more use cases being explored over time. Matillion brings no code AI to pipelines Matillion has announced its AI vision, which includes a range of GenAI functionality aimed at empowering every data practitioner, whether they are coders or non-coders. The company has introduced a low-code/no-code graphical AI Prompt component, which will enable data engineers to easily integrate prompt engineering within LLM-enabled pipelines, thereby increasing productivity and unlocking the potential of unstructured data. With this addition, Matillion aims to make AI more accessible and usable for all data professionals, regardless of their technical background. Thomas Reuters Generative AI Thomson Reuters has recently launched Generative AI-powered solutions that aim to transform the way legal professionals work. These solutions are designed to automate tasks and simplify workflows, allowing lawyers to focus on more high-value work, such as analysis and decision-making. Thomson Reuters' new Contract Express templates use AI to generate legal documents, while Westlaw Edge Quick Check enables lawyers to check their legal drafts for errors and inconsistency resolutions. The company's Practical Law Connect solution also uses AI to provide lawyers with relevant information and insights that can help them make more informed decisions. These generative AI-powered solutions are just the beginning of Thomson Reuters' efforts to improve legal workflows and deliver more value to its customers. Dataiku Onboards Databricks to Its Generative AI Dataiku recently announced that it has included Databricks to its LLM Mesh Partner Program. The collaboration between the two companies will help in the development of Generative AI-driven business transformations and enable enterprises to leverage the potential of LLMs. Martian Invents Model Router for Breakthroug LLMs Model mapping Martian recently emerged from stealth and introduced its Model Router, which is an orchestration layer solution that can route each individual query to the best LLM in real-time. Martian's Model Mapping technology helps to unpack LLMs from complex black boxes into a more interpretable architecture. This makes it the first commercial application of mechanistic interpretability. With its routing capability and unique technology, Martian is able to achieve higher performance. IBM Unveils watsonx.governance for Generative AI IBM has shared the insights that watsonx.governance would be available for businesses in early December. This tool aims to improve transparency around AI models by providing insights into the data used and the output generated. It is expected to help businesses achieve better control over their AI systems and ensure they are making informed decisions based on accurate information. Messagepoint Announces Generative AI Messagepoint makes an announcement of upgrading its Generative AI to provide better support for companies in creating customer-friendly communications. Their Generative AI now features translation services for over 80 languages that align with the ISO standard for plain language. The enterprise-grade Messagepoint's Generative AI allows customer servicing teams to translate and optimize content more efficiently while still retaining complete originlaity over outgoing messages. Uniphore Advances Enterprise AI With Next Gen Generative AI X Platform Uniphore has recently unveiled new advancements for its X Platform, which acts as a base for large enterprises to provide better customer and employee experiences, while also achieving improved efficiencies and a faster time-to-market. Among the new developments are the creation and application of Large Multimodal Models (LMMs), which come with pre-built guardrails to ensure successful integration of Generative AI, as well as the utilization of all data sources, such as voice, video, and text. Uniphore's suite of industry-leading applications now possesses unmatched capabilities. Rockset Adds Real-time Generative AI Machine Learning Rockset has recently announced the addition of native support for vector embeddings. This new feature will enable organizations to build high-performance vector search applications at scale in the cloud. With this update, Rockset has extended its real-time SQL-based search and analytics capabilities, which would allow developers to combine vector search with filtering and aggregations. LogicMonitor Introduces LM Co-Pilot, A Generative AI App LogicMonitor has announced LM Co-Pilot, its Generative AI-based tool that uses AI-powered recommendations to help users in their day-to-day operations. With the growing demand for observability tools that provide recommendations, LM Co-Pilot recognizes issues and offers solutions to empower IT and Cloud Operations teams to focus on innovation and customer satisfaction. This tool uses generative intelligence to provide insights that enhance the observability experience. Flip AI Launches to Bring the ‘Holy Grail of Observability’ Generative AI to All Enterprises Flip AI has recently launched its observability intelligence platform, Flip, which is powered by a large language model (LLM) that can predict incidents and generate root cause analyses in mere seconds. Flip is already trusted by some of the largest financial institutions in the world, as well as a top media and entertainment company, among other global enterprises. With its advanced AI capabilities, Flip empowers enterprises to resolve issues and incidents more efficiently, leading to enhanced user experience and customer satisfaction. Monte Carlo Now Supports Apache Kafka and Vector Databases Monte Carlo recently unveiled several new product enhancements designed to address the issue of ensuring accurate and reliable data for companies' data and AI products. Monte Carlo's data observability platform has been enhanced with new integrations with Kafka and vector databases, beginning with Pinecone. These new capabilities will be particularly useful for teams working on generative AI use cases, as they will help ensure that the data used to power large-language models (LLMs) is reliable and trustworthy at every stage of the pipeline. Monte Carlo is the first data observability platform to offer data observability for vector databases, which are specifically designed to store and query high-dimensional vector data, often used in RAG architectures. Espressive Announces Barista Live Generative AI Espressive recently unveiled a new capability as Espressive Barista, called Live Generative Answers. This feature allows Barista to find answers to employee questions from a variety of sources both inside and outside an organization as well. Barista uses generative AI technology to understand the intent of the employee's inquiry and provide the best response possible. Additionally, Barista uses automation and other AI technologies to function as a virtual service desk agent, delivering high employee adoption rates. Espressive's approach has achieved the industry's highest employee adoption rates of over 80 percent on average. Rafay Launches Infrastructure Templates for Generative AI Rafay Systems has released a new set of infrastructure templates specifically designed for Generative AI (GenAI) use cases. These templates leverage the capabilities of Rafay's Environment Management and Kubernetes Management tools, as well as the best tools used by developers and data scientists to extract business value from GenAI. By bringing together these powerful capabilities, Rafay is providing enterprises with an easy and efficient way to explore the potential of GenAI. Cresta Raises Bar with New Generative AI Cresta, a leading provider of Generative AI for intelligent contact centers, has recently announced new AI enhancements that are designed to make data-driven decisions easier for contact center agents and leaders. These enhancements provide advanced and intuitive capabilities that enable more productive and effective customer interactions, representing a significant step forward in the accessibility of AI technology. Cresta's generative AI platform is already known for its ability to provide real-time guidance and support to contact center agents, and these latest enhancements take this capability to the next level. With these new AI enhancements, contact center agents and leaders would be able to make more informed decisions that drive better outcomes for customers and businesses alike. DataStax Launches RAGStack DataStax, a company known for providing scalable data solutions for Generative AI applications, has launched a new solution called RAGStack. This innovative out-of-the-box solution is designed to simplify the implementation of retrieval augmented generation (RAG) applications that are built with LangChain. RAGStack streamlines the process and reduces the complexity for developers who are building Generative AI applications with LLMs. By providing a tested and efficient set of tools and techniques, RAGStack simplifies the implementation of RAG. With RAGStack, developers can build better Generative AI applications with ease and confidence. Snowflake Puts Industry-Leading Generative AI and LLMs in the Hands of Enterprises with Snowflake Cortex Snowflake has recently announced new innovations that allow all enterprises to securely leverage Generative AI with their enterprise data, regardless of their technical expertise. With Snowflake Cortex (private preview), a new fully managed service, Snowflake is making it easier for organizations to discover, analyze, and build AI apps in the Data Cloud, thereby simplifying the process of securely deriving value from Generative AI. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode References Dilmegani, C. (2023, October 26). Top 100 Generative AI Applications / Use Cases in 2023. AIMultiple. Retrieved November 21, 2023, from research.aimultiple.com/gene……Gartner. (2023, November 21). What Impact will Generative AI Have on Search in Customer Support? Cover. Retrieved November 21, 2023, from get.coveo.com/lp/service/gar……Gutierezz, D. (2023, November 21). Retrieved November 21, 2023, from insidebigdata.com/2023/11/21……Lukan, E. (2023, November 16). 50 Generative AI Examples in 2023. Synthesia. Retrieved November 21, 2023, from synthesia.io/post/generativ

Great insights from Datastax sponsor talk about how datastax is building a GenAI stack using their RagStack, astra db etc 😊

DataStax Aims To Simplify Building AI Apps With RAGStack thenewstack.io/datastax-aims… #FrontEndDevelopment #AI #LargeLanguageModels #DataScience #AIEngineering @DataStax

DataStax Aims To Simplify Building AI Apps With RAGStack thenewstack.io/datastax-aims… @lorainelawson @DataStax #AI #Apps #RAGStack

Literally a packed house at @philnash talk about ColBERT and Ragstack! Also never expected to see Phil write Python 😅 @aiDotEngineer #AIEWF

Loving @philnash talking colBERT at scale with RAGstack #aiewf

David Leconte from @DataStax introduces RAGStack at #JOTB24

We are in #Sydney 🇦🇺 for #AWSSummit! 10-11 April at @ICCSyd 👍 See how developers build #GenAI apps in minutes! 🚀 JOIN 👉 hands-on workshop by @DataStax & @AWScloud where YOU will build a chatbot 🤖 using #RAGstack AWS Bedrock! 💪 Deets free rego ➡️ ow.ly/lfwZ50Ra7xi

DataStax Teams Up with Langflow to Make Building Generative AI Applications 100x Faster, Easier, and More Fun! Langflow, the popular open-source visual framework for building retrieval-augmented generation (RAG) applications, is now part of @DataStax ! ✅ Learn More - brij.guru/datastax This is a game-changer for generative AI development. @langflow_ai . makes it 100x easier and faster for any developer to build powerful AI applications. With its intuitive drag-and-drop interface, reusable components, and rapid iteration capabilities, Langflow empowers developers to: 🔶 Build RAG applications quickly and easily 🔶 Test, reuse, and share workflows seamlessly 🔶 Achieve fine-grained control for exceptional results 🔶 Deploy applications in hours, not weeks Here's why this acquisition is a win for developers and businesses: ✴️ Simplified Generative AI Development: The combined power of Langflow and DataStax creates a one-stop shop for generative AI application development. ✴️ Drag-and-Drop Visual Tools: Build applications with ease using Langflow's intuitive visual environment. ✴️ Flexible Deployment Options: Deploy your applications seamlessly with options like Astra DB integration. ✴️ Production-Ready Applications: Build enterprise-grade RAG applications using Python and a vast ecosystem of custom components. ✴️ Seamless AI Ecosystem Integration: Langflow integrates perfectly with frameworks supported by RAGStack, DataStax's out-of-the-box RAG solution. Check out the DataStax blog to learn how to get started: ⛓️ brij.guru/datastax

a full blown product to do this is not there, but the pieces are... you will need ... 1. a vector db 2. RAGstack 3. an agent API docs.datastax.com/en/opscent…

Excited to share our partnership with @Unstructuredio ! Dead simple to get data ready for GenAI in #AstraDB. dtsx.io/49wKH9G #DataSimplified #AI #RAGStack #RAG

Data is at the heart of AI, so having an infrastructure that focuses on data access, storage, processing, & learning are critical. With Astra DB & RAGStack, developers can deploy production-ready GenAI apps fast. See how customers have done it👇 datastax.com/resources/white…