Video by SAP via YouTube
Cow milk, country air, or eight arms? 🤔 Spoiler: It’s SAP. https://sap.to/6054BBjMu0
Kuhmilch, Landluft oder acht Arme? 🤔 Spoiler: Es ist SAP. https://sap.to/6054BBjMu0
@TSGHoffenheim1899 #SAPSportsOne #SAP
Video by Michael Tunnell via YouTube
Fedora 44 continues Fedora’s fast-moving approach with updated desktops, installer networking improvements, gaming-related improvements, and more.
Follow for more #Linux and #OpenSource news
Full episode at https://thisweekinlinux.com/343
#tech #podcast #technology
Video by TWiT Tech Podcast Network via YouTube
Security engineer Andy Nguyen’s PS5-Linux project allows original PS5 models on older firmware (3.xx/4.xx) to boot Linux. This transforms your console into a powerful x86-64 machine, capable of running distros like Ubuntu and Arch Linux, and even Steam. A gamer’s dream, if your firmware is outdated! #PS5Linux #GamingPC #TechHacks #LinuxGaming #ConsoleModding
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Video by Meta Developers via YouTube
See what happens when AI plugs into your Meta Quest development workflow ⬆️
This is MCP (Model Context Protocol).
It’s the open standard that connects your favorite AI assistants like Claude and Cursor to device logs, performance traces, documentation, 3D assets, and more. Your AI picks the right tool and pulls the data. 💫
🔗 Tap the link in the comments to get started with MCP
#VR #AI #Developer #VRDev #GameDev
Video by The Linux Foundation via YouTube
Sponsored by Harness
AI has supercharged coding speed, but it has exposed critical weaknesses in the downstream delivery pipeline. The Harness State of DevOps Modernization 2026 report shows that, while AI-assisted developers are shipping code 45% faster, 69% of frequent AI users report more frequent deployment problems, and average incident recovery times have climbed to 7.6 hours. This is the "Velocity Paradox.”
The culprit? A fragmented pipeline where application code moves at machine speed, while database schemas and infrastructure remain trapped in manual, siloed workflows. To survive the AI era, organizations must move toward a unified pipeline that treats the database as a first-class citizen of Continuous Delivery.
In this session, we’ll discuss how to:
– Standardize Across Environments: Deploy application and database changes consistently from dev to staging to production, with the visibility and governance required to scale safely.
– Scale with Agentic Workflows: Move beyond basic scripts. Use AI-driven agents to safely author schema migrations and automate the complex troubleshooting that currently inflates MTTR.
– Implement "Golden Paths" for Data: Enable developer self-service while enforcing rigid security and compliance using OPA (Open Policy Agent) "baked into" the pipeline.
– Bridge the Trust Gap: Learn how to apply "trust but verify" guardrails to AI-generated code and database changes to reduce the 51% increase in code quality issues seen by high-velocity teams.
Video by The Linux Cast via YouTube
The guys are back, this time to talk about their most controversial opinions. We’re right, you’re wrong!
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[show notes]
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Just a reminder that the live stream will go unlisted directly after the stream. The edited version will be posted on Saturday night. Live stream replays can be had by joining us on Patreon: https://patreon.com/thelinuxcast
Docker and DevOps Docker on Windows: A fresh guide explains running Docker containers on Windows, covering WSL2 integration and best practices for hybrid environments. Docker in Plain English: A beginner-friendly article breaks down images, volumes, and containers, demystifying Docker’s core concepts. Open Source Systems & Security ReactOS Gets Unified Installer: The open-source Windows-compatible OS now … Read more
Insight Analysis This week’s open-source news highlights a vibrant ecosystem where innovation spans AI, legal tech, decades-old code preservation, and user-friendly tools. A major theme is the rise of open-source AI models challenging proprietary giants, exemplified by NVIDIA’s Nemotron 3 Super topping AI benchmarks and Deepinfra’s $107M funding for inference cloud services. This signals growing … Read more
The open source ecosystem is advancing on multiple fronts this week, from enterprise AI infrastructure to desktop Linux releases and community governance. A common thread emerges: the push for independent control—whether over AI models, data, or operating systems—is driving innovation across the stack. Enterprise AI: Sovereignty and RAG Two stories highlight the maturing of open … Read more
Video by H2O.ai via YouTube
How h2oGPTe grounds LLMs in enterprise data using multimodal RAG, hybrid search, and autonomous agent workflows.
LLMs don’t inherently know your internal products, policies, or customer history. h2oGPTe bridges this gap by ingesting 50+ file formats—including documents, audio, and video—using multi-engine OCR and native enterprise connectors for SharePoint, S3, and Azure. Hybrid retrieval combines semantic similarity and BM25 with Reciprocal Rank Fusion and cross-encoder reranking for precise, citation-backed answers. Agentic workflows extend RAG further by enabling autonomous retrieval, reasoning, and tool execution.
Technical Capabilities & Resources
➤ Document Ingestion & Transformation: 50+ format support with multi-engine OCR, table preservation, and enterprise connectors.
🔗 https://docs.h2o.ai/enterprise-h2ogpte/guide/collections/supported-file-types
➤ Built-in & External Vector Storage: Includes Vex embedded vector database plus integrations with external vector providers.
🔗 https://docs.h2o.ai/enterprise-h2ogpte/architecture/vector-database
➤ Advanced Hybrid Search: Combines semantic similarity, BM25, Reciprocal Rank Fusion, and cross-encoder reranking.
🔗 https://docs.h2o.ai/enterprise-h2ogpte/guide/chats/chat-settings#generation-approach
➤ Agentic Workflows: Autonomous agents that iteratively retrieve, reason, and trigger tool execution for complex queries.
🔗 https://docs.h2o.ai/enterprise-h2ogpte/guide/agents
