Tweet Teratas untuk #VectorDatabases
PostgreSQL with pgvector offers a cost-effective and simplified alternative to dedicated vector databases for many AI applications.
#vectordatabases #postgresql #pgvector #databaseconsolidation
PostgreSQL is a rising star in AI! Vector search is now in-database, simplifying development & reducing reliance on standalone solutions.
#vectordatabases #postgresql #aiinfrastructure #databaseconvergence
https://t.co/G0GNIQKSw9
Agentic RAG is becoming the new standard for AI by 2026, offering smarter, adaptive retrieval for production-ready systems.
#agenticrag #retrievalaugmentedgeneration #vectordatabases #aiagents
Mem0 is now AWS Agent SDK's exclusive memory provider, making advanced vector memory easier for AI & improving their contextual understanding.
#aiagents #vectordatabases #aws #memorymanagement
🔎 Vector in Databases is a free virtual summit for AI/ML engineers, backend developers, and data professionals interested in vector search and its role in building AI applications.
📅 23rd October 2026 📍 Online
#DevITEvents #VectorDatabases #VectorSearch
By 2026, AI developers must adopt Agentic RAG and GraphRAG for grounded enterprise AI, moving past basic vector search for robust, adaptive systems.
#agenticrag #graphrag #vectordatabases #llmorchestration
Software Engineer (AI-Native Platform & Integrations) Talent network Remote
#SoftwareEngineer #AIEngineering #PlatformEngineering #RemoteJobs #USAJobs
#LLMOps #MLOps #RAG #VectorDatabases #AIInfrastructure #PromptEngineering #ModelEvaluation #AIObservability #LangChain #ModelServing #APIIntegration #APIDevelopment #RESTAPI #Integrations #SystemIntegration #WorkflowAutomation #EnterpriseIntegration #Webhooks #AutomationEngineering #IntegrationEngineering
Location requirements
United States
About Mercor’s talent network
This is an open application for future contract opportunities that match your background and interests.
Once you complete your profile and pass our AI interview, you'll be eligible for relevant projects as they become available. We match experts to opportunities on a rolling basis. Role Overview
We’re building an AI-native platform that replaces spreadsheet-driven operations with real-time dashboards and agentic workflows. This engineer will own core product delivery end-to-end: platform foundations, integrations, analytics surfaces, and the pilot launch.
What you’ll build
AI-native platform (core entities, workflows, permissions, multi-tenant foundations)
Omni-tool integration layer (connectors to common tools; event ingestion; sync; actions)
Real-time analytics dashboard (live metrics, drill-downs, exports)
MCP-compatible agentic integration architecture (tool registry, permissions, runtime, observability)
Pilot launch support with hands-on technical execution (shipping, debugging, iteration with real users)
Responsibilities
Ship production features across backend + frontend.
Design and implement a scalable integrations framework
Build real-time analytics experiences
Architect an agentic tool-use layer compatible with MCP-style patterns
Set up strong engineering hygiene: testing, observability, on-call readiness for the pilot.
Iterate quickly and pragmatically.
What we’re looking for
Strong, practical software engineering skills; you can ship end-to-end and unblock yourself.
Experience building SaaS products with APIs, data models, and production constraints.
Deep comfort with integrations (OAuth2, webhooks, API pagination, rate limiting, sync semantics).
“Vibe coding” mindset: you use AI tools effectively (Copilot/ChatGPT/etc.) to move fast without sacrificing correctness—good taste around tests, interfaces, and guardrails.
Familiarity with MCP-style tool interfaces and/or building tool servers.
Clear communicator who can explain tradeoffs and keep stakeholders aligned.
https://t.co/6q3rdnQcKV
NYU/Matterstack's AskChem ends LLM citation hallucinations in chemistry, hitting 100% verifiable sources by grounding GPT-5.5.
#RAG #scientificAI #hallucination #vectordatabases
https://t.co/zCaxemFGFw
@JustHireMeAi Officially has 2000+ downloads across @windows @Apple @Linux
Thanks a lot everyone!
Website: https://t.co/jJetHsLg1Z
Github: https://t.co/Xf2luWGOFi
#OpenSource #AgenticAI #AIAgents #RAG #GraphRAG #Python #FastAPI #ReactJS #TypeScript #Tauri #VectorDatabases #JobSearch #CareerTech #Automation #PrivacyFirst
💡 #TipIA para Empresas:
Evita que la memoria de tu Inteligencia Artificial se vuelva lenta y costosa. 🤖📈
Implementa Semantic Memory Compaction y configura tu sistema para que resuma y guarde solo los datos clave de chats pasados. 🛡️💼
#IA #VectorDatabases #Ciberseguridad #Execudata #Pymes #DataEfficiency
Today's Log:
- Solved 5/14 Hard Array Problems from Strivers A2Z sheet
- Continued learning embeddings and vector databases
- Started building CODEXA, my next AI project
#DSA #Python #embeddings #vectordatabases #AI #codexa
Day 7 of #60DaysOfLearning2026
Built a Mini-FAISS Engine from scratch!
• Custom IVF index using raw NumPy
• Vector Space Partitioning & ANN search
• Decoupled search speed from DB size (skips 50% of data)
#LSPPDay7 #VectorDatabases #LearningWithLeapfrog @lftechnology
Wrote a two-part series on HNSW, the vector index behind fast similarity search. Mental model in part 1, Rust implementation in part 2.
Part 1: https://t.co/2TzAhXy1nq
Part 2: https://t.co/THaTCVtaca
#Rust #VectorDatabases #HNSW
Day Progress 🚀 | Day 75/365
🏋️♂️ Gym – Shoulders
🤖 Studied Gen AI
• Learned about Vector Databases
⚛️ Revised React interview questions
💻 Worked on LeetCode Clone – Frontend
Learning, building, and staying consistent 💪
#365DaysOfCode #React #Frontend #GenAI #VectorDatabases
Just added advanced clustering to Vector Inspector!
https://t.co/Kwrd5XHfec #machinelearning #DataScience #ai #vectordatabases #hdbscan
Modern AI isn’t just getting smarter it’s rewriting the data layer. Vector databases are evolving to be faster, more secure, and radically more efficient to keep up.
#AI #VectorDatabases #DataInfrastructure #GenAI
#Day25 of Strike DSA + GenAI By @rohit_negi9
Today's Learning:-
Vector databases aren’t magic.
They’re DSA + graphs + geometry in action.
ANN & HNSW power modern AI search.
Fast > perfect — that’s real-world AI.
#GenAI #VectorDatabases #AIEngineering #LearningInPublic #StrikeDSA
Vector database design is a make or break factor in enterprise AI. Embeddings, chunking, metadata, security, and scale decide retrieval quality. Many LLM failures are really retrieval failures. Architecture matters more than models.
#AI #VectorDatabases #RAG #AIArchitecture
A lot of people think vector databases are “AI magic.”
They’re not. They’re smart engineering.
At the core, a vector database does three simple things:
#VectorDatabases #RAG #LLM #AIEngineering #SemanticSearch
Explore how #RetrievalAugmentedGeneration & #SemanticCaching can reduce #FalsePositives in AI-powered apps.
Insights come from a production-grade #CaseStudy testing 1,000 queries across 7 bi-encoder models.
📰 Read now: https://t.co/3mhpqjsuhB
#AI #LLMs #RAG #VectorDatabases
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