Lizz Q.

Thanks for your participation in our session! I felt delighted to spread out my knowledge on this Multicloud adventure. Thank you to #OracleCloud for giving us this space for the community and talk about our use case in this huge event #OracleCloudWorld22 #ocw22 Las Vegas,🇺🇸

Top 12 GitHub AI Repositories These repositories were selected based on their overall popularity and GitHub stars.

CPU vs GPU vs TPU

Understanding Database Types

La mítica base de datos MySQL se está apagando… Lleva más de 4 meses sin recibir ni un solo commit en su repositorio público de GitHub. Mala señal. La pausa coincide con los despidos de septiembre en Oracle dentro del equipo. No significa que vaya a desaparecer. Está en millones de servidores y seguirá funcionando durante años. Pero sí es una señal clara de algo más profundo: MySQL ya no compite como comunidad open source, sino como producto puramente comercial. Menos transparente, con otras prioridades. El sorpasso de PostgreSQL ya es inevitable.

@piyascode9 Agent

99% of the AI agent tutorials on YouTube are garbage. I’ve built 47 agents with n8n and Claude. Here are the 3 prompts that actually work (and make agent-building simple). Bookmark this post 🔖 Bonus: comment "Agent: and I’ll DM you AI agent system prompt + full guide ↓

System Performance Metrics Every Engineer Should Know

The World of the Databases this decade is 🔥

Top 20 System Design Concepts You Should Know

If you want to become good at system design (in 3 weeks), learn these 15 case studies:

Cloudflare is much more than just a CDN and DDoS protection service. Let’s do a quick comparison of Cloudflare, AWS, and Azure.

The Evolution of LinkedIn’s Generative AI Tech Stack Over the past two years, LinkedIn has undergone a rapid transformation in how it builds and ships AI-powered products. What began with a handful of GenAI features, such as collaborative articles, AI-assisted Recruiter capabilities, and AI-powered insights for members and customers, has evolved into a comprehensive platform strategy that now involves multiple products. One of the most prominent examples of this shift is Hiring Assistant, LinkedIn’s first large-scale AI agent for recruiters, designed to help streamline candidate sourcing and engagement. Behind these product launches was a clear motivation to scale GenAI use cases efficiently and responsibly across LinkedIn’s ecosystem. Early GenAI experiments were valuable but siloed because each product team built its own scaffolding for prompts, model calls, and memory management. This fragmented approach made it difficult to maintain consistency, slowed iteration, and risked duplicating efforts. As adoption grew, the engineering organization recognized the need for a unified GenAI application stack that could serve as the foundation for all future AI-driven initiatives. Note: This article is written in collaboration with the engineering team of LinkedIn. Special thanks to Karthik Ramgopal, a Distinguished Engineer from the LinkedIn engineering team, for helping us understand the GenAI architecture at LinkedIn. All credit for the technical details and diagrams shared in this article goes to the LinkedIn Engineering Team. Read the full article here: blog.bytebytego.com/p/the-evolutio…

@svilmune Redwood included ?

Wow great, OCI Console gets dark mode!

“When mistakes are cheap, you can move fast and fix what doesn't work. When mistakes are expensive, you overthink everything and still choose wrong” From Brain Food

@svilmune You deserve it 👏

This is awesome news! I've been in the ACE Program for some time and appreciate all the hard work they do to raise knowledge on Oracle! What's encouraging is the amount of new ACEs recently, it's great to see people interested on these technologies and sharing their learnings!

Empezando el #AIPromptday25 en Barcelona. De la mano @SeniorManager

An undergrad student broke a 40-year-old belief in computer science. Since 1985, it was believed that hash tables, when nearly full, must check many spots to find or add data. Andrew Krapivin discovered a new way to organize data inside a hash table that avoids this slowdown. Instead of checking slots randomly or in order, his method uses a more efficient structure to guide the search. This reduces the worst-case time from O(n) to (log n)² steps, even when the table is almost full.

25 Papers That Completely Transformed the Computer World. 1. Dynamo - Amazon’s Highly Available Key Value Store 2. Google File System: Insights into a highly scalable file system 3. Scaling Memcached at Facebook: A look at the complexities of Caching 4. BigTable: The design principles behind a distributed storage system 5. Borg - Large Scale Cluster Management at Google 6. Cassandra: A look at the design and architecture of a distributed NoSQL database 7. Attention Is All You Need: Into a new deep learning architecture known as the transformer 8. Kafka: Internals of the distributed messaging platform 9. FoundationDB: A look at how a distributed database 10. Amazon Aurora: To learn how Amazon provides high-availability and performance 11. Spanner: Design and architecture of Google’s globally distributed databas 12. MapReduce: A detailed look at how MapReduce enables parallel processing of massive volumes of data 13. Shard Manager: Understanding the generic shard management framework 14. Dapper: Insights into Google’s distributed systems tracing infrastructure 15. Flink: A detailed look at the unified architecture of stream and batch processing 16. A Comprehensive Survey on Vector Databases 17. Zanzibar: A look at the design, implementation and deployment of a global system for managing access control lists at Google 18. Monarch: Architecture of Google’s in-memory time series database 19. Thrift: Explore the design choices behind Facebook’s code-generation tool 20. Bitcoin: The ground-breaking introduction to the peer-to-peer electronic cash system 21. WTF - Who to Follow Service at Twitter: Twitter’s (now X) user recommendation system 22. MyRocks: LSM-Tree Database Storage Engine 23. GoTo Considered Harmful 24. Raft Consensus Algorithm: To learn about the more understandable consensus algorithm 25. Time Clocks and Ordering of Events: The extremely important paper that explains the concept of time and event ordering in a distributed system Over to you: I’m sure we missed many important papers. Which ones do you think should be included? -- Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): bit.ly/bbg-social

Strong words "Confidence is something your learn by doing" by Jesica Wulf #IWD25 in the event with the @wtmbcn #WTMBarcelona #WTMVueling

Hablando de IA en el #IWD25 "Liderazgo en la Era de la IA: Adaptabilidad, Conciencia y Power Skills" con nuestra tremenda ponente Daniela Vargas. "Nuestras emociones son las que se quedan en nuestra memoria, la IA son datos" #WTMBarcelona #WTMVueling

Who is interested about Kafka? We have the third talk about that. Coming from Gemma Minihan "Product Manager at Aiven- Kafka Made Simple: A Beginner's Guide to Event" #Aiven #IWD25 #wtmbarcelona #WTMvueling