Chandan Singh’s Post

The Role of AWS Vector Databases in Generative AI Applications https://lnkd.in/e4pjj9ua #aws #database #genai #vectodb #postgresql #bedrock #memorydb #neptune #documentdb #opensearch

SQLSatOC: Generative AI Use Case Leveraging Amazon RDS for SQL Server as a Vector Store by Camilo Leon This session covers how RDS SQL Server can be leveraged as a Vector Data Store while implementing a Generative AI Similarity Use Case. This session includes a live demo. https://buff.ly/3vEOXoO #sqlsatoc #ai #aws #rds #sqlserver #verctorstore

The #Next #level #DevOps using MLOPS When you work with #MLOPS or machine learning operations, a critical part is the input data because them must to meet the format requirements for the right train of #AI models; in these sense clean, transformation and format stages are auto applied using the called #Datapipelines. Some examples of these datapipelines are built using #GCP #Dataflow or #AWS #Glue or Apache #Nifi among others. Which another tools could you hear about this stage?

Over at InfoWorld I took a look at how graph databases can be used to deliver even more grounding to your LLMs, focusing on Neo4j's new Azure-hosted offering and how it can help build graphs from your data. MSR's work on GraphAG is looking to be quite a useful tool here. #azureai #llm #graphdatabases #neo4j #graphAG #RAG #azure #microsoft https://lnkd.in/gUwrQUES

Make time to see Lino Tadros' session at the next GenAI Conference today. Lino will dive deep into Embeddings and Vectorization fundamentals. Attendees will gain crucial insights into the importance and applications of these technologies. The session will explore multiple embedding models and vectorization databases, including ChromaDB, FAISS, Pinecone, Azure AI Search, and Azure PostgreSQL. Tadros will demonstrate practical applications using Semantic Kernel and Langchain. Attendees will walk out with essential knowledge for leveraging embeddings and vectorization in their projects. https://buff.ly/4egmg22

Redis has acquired Speedb, setting a new standard for data storage and application performance. Learn how this could transform generative AI applications: https://ow.ly/XZ8O50R0b4u

We just wrapped up an incredible session with Vaibhav Mehra and Shekhar Bharat Singh on the Gen AI capabilities of MongoDB!   Our team is now buzzing with ideas and ready to unleash cutting-edge AI solutions. Stay tuned for the innovation wave!   #GenAI #MongoDB #InnovationUnleashed #TeamEvolution #AISession #UNext #UNextLearning 

Hello Everyone! I had the incredible opportunity to attend AWS Data Day, where the focus was on the transformative power of generative AI. The sessions were insightful and packed with valuable knowledge on leveraging Amazon Web Services for cutting-edge AI applications. Here's a glimpse of what was covered: 👉Build Generative Applications with Foundation Models - Amazon Bedrock: We delved into the essentials of creating generative AI applications using Amazon Bedrock. 👉Generative BI with Amazon QuickSight: The session highlighted how generative AI can enhance business intelligence through Amazon QuickSight. 👉Managing the AI Trust Challenge - Building a Solid Data Foundation: We explored the critical aspects of trust and data integrity in AI applications. 👉Ease of Data Security, Mobility, and Management in the Age of Generative AI: Best practices for ensuring data security and management in a rapidly evolving AI landscape were discussed. 👉Accelerate Your Generative AI Applications with In-Memory Services: We gained insights into speeding up AI applications with in-memory services. 👉Best Practices for Querying Vector Data for.Generative AI Apps: Techniques for effectively querying vector data to support generative AI projects were shared. The event featured an impressive lineup of speakers, including Biswajit Das , Ippokratis Pandis, Santosh Ameti , Abhinav Pandey, Michael Armentano ☁ , Vipul Jain , Nilesh Kulkarni, Varun Seth, Shirish Kulkarni, Andrew Bowles, Suraj Sharma, GopalaKrishnan Subramanian, and Devinder Singh. A special thanks to Amazon Web Services (AWS) for organizing this event and to CloudifyOps for providing the opportunity. #AWSDataDay #AWS #CloudifyOps #Data #GenAI #Databases #AmazonBedrock #AmazonQ #Cloud #DevOps

How to upload AI images to AWS S3 in Next.js? AWS S3 buckets are a great solution for storing different files such as images generated by OpenAI's DALL·E models. The most important part is to set the response type to b64_json when generating the image with the OpenAI's API. This will return a base 64 string that can later be put in a Buffer and a Readable stream. The image will be hosted on the S3 bucket at the specified key. In this example we used a unique uuid generator. It's important to store this key in the database to be able to retrieve the image later. 👇 <AWS_BUCKET_NAME>.s3.amazonaws.com/<KEY> ➜ Code: https://lnkd.in/dRtQQUPb #NextJS #AWS #AI 

🚀 Exciting Innovation in Search AI! 🚀 Search AI Lake and Elastic Cloud Serverless are here! A cloud-native architecture for real-time, low-latency search. 🌐 - Organizations will benefit from: Seamless Search: Search AI Lake can dive into vast amounts of unstructured data without needing metadata or tables, making it ideal for AI training, security, and observability workloads. - Scalability: By decoupling storage from compute, Elastic promises enormous scalability, making this tool perfect for training large language models (LLMs). - Advanced Search Capabilities: Supports traditional, vector, hybrid, and faceted search, enhancing applications like GenAI training and Retrieval Augmented Generation (RAG). - Interoperability: Uses the Elastic Common Schema (ECS) format and the Elasticsearch Query Language, enabling federated searches across diverse data sources. - Real-Time Processing: Built on the robust foundation of ElasticSearch, known for its real-time data processing and open-source roots. 👉 Learn more in @techzine article here: https://gag.gl/CogELL Join the conversation and share your thoughts on how this innovation could impact your data strategies! 💬 #DataInnovation #SearchTechnology #AITraining #BigData #ElasticSearch #GenAI #TechNews