Xavier Alvarez’s Post

📣🗺️ Excited to launch our LLM Infrastructure Stack Market Map companies and trends developed by Aleix.   Click below to view the map and read the article 👇 https://lnkd.in/dTKNjZED   We dive into 1) defining and breaking down the layers of the stack, 2) market map with +280 LLM Infra companies, and 3) trends we see and its rising stars.   🙏 Much gratitude to all those who contributed insights and critical map reviews including Daniel & Francis (Argilla), Antoni (StackAI), 👋 👋 Johannes (Kern AI), Sohrab (orq.ai), Carlos (Alinia AI), Stephen M. (Klu.ai) Timo H. (SuperDuperDB), and Alex (Sentify)   📩 Building in this space or have any comments? We’d love to hear from you at tech@criteria.com   If you’d like to be added to the map fill out this 2' form 👇 https://lnkd.in/dfKJ3z5W   🌟 Rising stars: SciPhi, LiteLLM (YC W23), Alinia AI, Giskard, Deasie, Argilla, Automorphic, Haven (YC S23), RunPod, HippoML, Cerebrium, Commonbase, Lakera, PromptArmor (YC W24), Flower Labs, FEDML, Confident AI, Parea AI (YC S23), Patronus AI, Log10.io, StackAI, FinetuneDB     #GenAI #AI #GenerativeAI #LLMOps #LLM #SLM #LLMinfra #techstack #datalabeling #syntheticdata #finetuning #LLMtraining #federatedlearning #dataorchestration #LLMobservability #LLMmonitoring #LLMintegration #LLMdeployment #LLMApi #LLMorchestration #vectordatabase #vectorsearch #datapipeline #syntheticdata #datamanagement #LLMsecurity #ResponsibleAI #EthicalAI #LLMinference #GPUServerless #promptengineering #expertimenttracking #promptinjection

Very interesting event on June 11th, 2024 in Zurich with Microsoft Product Teams and high level experts on “Leading in the era of AI with Intelligent Apps and Cosmos DB”. The event offers learning about the impact of generative AI on industries, how to redefine your app strategy with AI, and how to harness the power of intelligent apps for your business. Do grab the opportunity to meet Technical Decision Makers, Software Architects, and Engineering leaders to discuss how to create highly differentiated apps or modernize existing ones, that are scalable, performant, flexible, and intelligent and take advantage of generative AI’s capabilities. More in the post by my friend Franziska-J. Klebôn

Product Group & GBB Deep Dive June 11: with AI Infused Applications growing in strategic importance for many enterprises the question of how to scale those and make them globally available at low latency becomes seminal. Once you talk to your Application Development Team or Squad they might ask you whether there is a scalable no-SQL offering that ticks all of the below boxes: - can store Vectors - can be used via API's as fully managed NoSQL database service, you can access and query your data in Azure Cosmos DB as if it were a document, key-value, graph, or column-family database (supported through Gremlin-, PostgreSQL-, NoSQL-, MongoDB-, Cassandra-, Table-APIs) - have global replications for low latency support of your local application instance, while still supporting CRUD actions (remaining ACID globally!)   There is - and we are super proud to have our Product Group fly to #Switzerland to share their knowledge and learn from users and enterprises building the future on this stack - #CosmosDB. We have limited spaces left. Register now for our in person event on June 11th “Leading in the era of AI with Intelligent Apps and Cosmos DB” at https://lnkd.in/ex9DpwAP Joseba, Sebastian, Loris, Hans, João, Davide, Natalia, Michele, Francesco, Alberto, Rafael, Andreas, Paula, Dominique, Francesco, Richard, Patrick, Denis, Simon, Malin, Christian, Rene, Florian, Tine, Claudio, Konstantinos, Christin, Alberto, Evgeny, Sasa, Manuel, Sevgi, Zoran, Shalini, Mark, Igor, Ploutarchos, Engin, Liviana, Patrik #AI #IntelligentApps #LLMs #NoSQL

Generative AI is evolving fast, but building an intelligent AI application still requires the right tools and strategy. The latest blog in our Unleashing AI with PostgreSQL series breaks down how Postgres is helping developers move from traditional databases to advanced AI data platforms. From vector search to large language model integration, this post dives into how Postgres is at the core of AI-driven innovation. Key takeaways: ✅ The steps for building generative AI applications, from data capture to fine-tuning LLMs ✅ How vector databases and AI data platforms differ—and why it matters ✅ Ways AI data platforms reduce complexity and speed up development ✅ How PostgreSQL, with extensions like pgvector, powers these workloads and accelerates time-to-market ✅ To learn how Postgres can fuel your AI journey, read the full blog here ➡️ https://bit.ly/3XtbtLo #EDBPostgresAI #JustSolveItWithPostgres #AIPlatform #VectorDatabase #PostgreSQL #OpenSource #LLMs #GenAI

Built on top of Postgres vector, pgai (tech preview) enables Postgres to run LLMs and directly manage, process, search and retrieve AI data such as text documents or images to accelerate AI application development. To learn more and enroll in the tech preview, visit: https://lnkd.in/gk-JsHez #postgres #pg #enterprisedb #pgai #GenerativeAI #vectordb #LLM #RAG

What is the prerequisite for AI? It's data, your most valuable asset! Learn how the Aiven platforms enables you to prepare your data assets and evolve your technologies to be ready for the #AI era. Three main pillars: - Perform Retrieval Augmented Generation (#RAG) directly from your operational data layer - using #PostgreSQL, #OpenSearch and #ClickHouse - Provide real-time and governed data to your AI - using #ApacheKafka to stream data from where it resides to where it is needed - Write performant code and resolve CloudOps issues faster - using Aiven AI database optimizer, powered by EverSQL by Aiven to understand and resolve performance bottlenecks Detailed scenarios, integrations and practical examples are available in the new "Aiven for AI" page https://lnkd.in/dnTf6uy3

I posted about Vector databases about a year back, highlighting their importance for building Gen AI models. I want to revisit the state of the market. Vector databases have become essential in handling and searching through high-dimensional data, especially for machine learning, Gen AI, and data analytics applications. They're designed to efficiently store, manage, and retrieve vector embeddings, commonly used in similarity search tasks. Here's an overview of some of the top vector databases in the market today: - Milvus: It is highly optimized for both search latency and throughput. It uses novel indexing and storage techniques to enhance search efficiency. It is designed for cloud-native environments, supporting horizontal scalability and easy integration with Kubernetes. Pinecone: This company focuses on providing highly accurate similarity search results with low latency and offers tunable parameters to balance accuracy and speed. It provides a managed service that scales automatically with demand. - Weaviate: It employs a unique combination of inverted indexing and vector search to improve performance. It also supports GraphQL for complex queries. It offers easy scalability, with support for distributed deployments and a Kubernetes operator for orchestration. Interestingly, it supports a RESTful query interface, making it versatile for different use cases. - Elasticsearch with Vector Search plugin: While primarily a text search engine, its vector search capabilities have been enhanced with plugins, offering competitive search performance. It inherits Elasticsearch’s robust scalability features, making it suitable for large-scale deployments. FAISS: It was developed by Meta AI and is highly optimized for similarity search, especially on large datasets. It excels in batch processing. It is primarily designed for single-node operations but can be integrated into distributed systems with additional effort. To effectively leverage vector databases when building Gen AI applications, it's crucial to align the database choice with your application's specific needs regarding performance, scalability, and ease of integration. Regardless of the choice, the key to harnessing the full potential of these databases lies in thoroughly understanding their features, properly indexing your data, and continuously monitoring performance to fine-tune your setup. Understanding and experimenting with these databases can significantly enhance your Gen AI capabilities, driving innovation and providing more accurate, efficient, and personalized user experiences. #GenerativeAI #VectorDatabases #DataIndexing #AIInnovation #TechTrends #AIApplications #Milvus #Pinecone #Weaviate #Elasticsearch #FAISS #AI

#EDBPostgresAI is the industry's first intelligent platform for transactional, analytical, and new AI workloads. Imagine the potential unleashed! Businesses can now leverage the prowess of Postgres to unlock the boundless frontier of AI initiatives. This is not merely an advancement, but a paradigm shift! A dismantling of the walls that confine data, a liberation that empowers businesses to new heights. It is the harmonious union of established brilliance – the venerable Postgres – with the electrifying potential of AI. EDB has prepared to weave the very fabric of a brighter future, a future where data sings a glorious symphony, yet unheard. Join the movement! Let us harness the power of EDB Postgres AI and usher in a new age of data-driven prosperity! https://lnkd.in/exc_iVdv #EDBPostgresAI #JustSolveItWithPostgres #PostgreSQL #AI . . . #PostgresData #DatabaseManagement #DataAnalytics #DataDrivenDecisions #DataManagement #DataScience #DataInsights #DataVisualization #DataEngineering #DataArchitecture