Community & Events Social Coworking and Office Hours – Code Linting in R: Join a collaborative session focused on code linting in R, where participants can share tips and best practices for cleaner code. In Search of the Region – Organizing Wiki Village Ganggyeong: A community-driven effort to document the region of Ganggyeong on Wiki … Read more
Open Source AI: The Week’s Biggest Moves This week, open-source AI made giant leaps—from the moon to your USB drive. IBM and NASA teamed up to release an open-source AI model for lunar exploration, proving that space tech isn’t just for billionaires anymore. Meanwhile, a mysterious free AI model has developers buzzing, and Alibaba’s screen-reading … Read more
The New Frontier: AI Agents Meet Open Source Infrastructure The latest news digest from OpenWorld.news paints a picture of an open source ecosystem racing to adapt to the AI era. From OpenAI’s new Agents API to GPU-centric infrastructure talks at KubeCon, the message is clear: the tools and platforms that power AI are evolving rapidly, … Read more
The Agents API brings a hosted version of the Codex harness to your applications. See how to build an agent that investigates production incidents, connects to tools through MCP, follows a runbook, and delivers a shareable report with evidence and suggested next steps.
At PyTorch Conference North America, Ricardo Noriega de Soto, Tech Lead for the vLLM Omni team and Alexander Brooks, Principal Machine Learning Engineer at Red Hat, will demonstrate how extending vLLM’s prefix caching mechanism to multistage pipelines boosts inference speeds while reducing GPU memory overhead.
Join us in San Jose on October 20th to learn practical strategies for optimizing complex AI workloads: https://hubs.la/Q04v4SL60
Video by CNCF [Cloud Native Computing Foundation] via YouTube
AI workloads are pushing GPU, memory, and electricity costs to unprecedented levels.
At KubeCon + CloudNativeCon Japan 2026, Takao Indoh shared why infrastructure is rapidly evolving from CPU-based architectures to dynamic, GPU-centric environments.
Watch the full talk on YouTube or explore more session recordings from KubeCon + CloudNativeCon Japan 2026: https://youtube.com/playlist?list=PLOZCGaPFoeIM&si=enU-o0Aj4hvhicwx
Stop guessing why your models fail and start using AI metadata to build trustable, automated systems.
Most autonomous systems struggle because they lack the necessary context to make decisions humans trust. This video explains why machine learning evidence is the bridge between raw data and reliable performance.
Learn how to structure your pipelines to guarantee reproducible results and consistently deliver accurate AI outputs in production.
Drop a comment with your biggest data infrastructure challenge.
Video by Open Data Science and AI Conference via YouTube
AI security is no longer just about preventing harmful outputs.
As AI agents gain access to tools, data, memory, and production systems, security has to move beyond the model itself.
In this episode of the ODSC AI X Podcast, host Dan Gerlanc speaks with David Campbell, previously Head of AI Security at Scale AI, about the evolving risks of agentic AI and what it takes to secure AI systems in production.
They discuss AI red teaming, persistent prompt injection, least privilege, observability, system-level security, and why autonomous cyber defense may become essential as AI agents grow more capable.
00:00 Intro: AI Security, Red Teaming & Autonomous Cyber Defense
01:13 AI Security Lessons from Google, Uber & DoorDash
03:05 AI Coding Risks, Bugs & the Engineering Skills Gap
08:06 Building and Scaling Distributed Systems at Uber
14:13 Why Go Works for AI Coding Agents
16:00 AI Red Teaming & Jailbreaking Frontier Models
21:08 Automating AI Jailbreaks & Adversarial Testing
26:10 AI Agent Security: From Model Risks to Real Cyber Threats
31:06 Persistent Prompt Injection & Agent Security Risks
33:07 Least Privilege, Permissions & Human Oversight for AI Agents
37:00 Why AI Guardrails Aren’t Enough: Observability & System Security
40:03 Autonomous Cyber Defense & the Future of AI Security
Visit our website and choose the nearest ODSC AI event to attend and experience all our training and workshops: https://odsc.ai
To watch more videos like this, visit https://aiplus.training
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Support us on Patreon and get an ad-free RSS feed with some early episodes. https://www.patreon.com/LateNightLinux
A BGP hijack involved some basic errors, Microsoft teaches people to ignore warnings in Windows, Zoom appears to be reading the clipboard on X11, why a non-US open certificate authority is feasible in theory, and keeping a NAS powered on as little as possible.
Start getting data from your A/B test in minutes with Flagsmith’s new Experimentation feature, which turns your existing feature flags into full experiments—with warehouse-native analysis built in.
Read the docs and start experimenting: https://docs.flagsmith.com/experimentation
00:00 Intro
00:24 The demo: an e-commerce checkout test
01:16 Setting up your data warehouse in two clicks
01:55 Creating your first experiment
02:28 Configuring the rollout and traffic split
02:51 Defining a conversion metric
03:52 Launching the experiment
04:32 The code: two new SDK methods
05:35 Reading the results: win probability and credible intervals
Flagsmith Experimentation enables you to run data-driven releases without leaving your feature flag platform.
Try Flagsmith for free: https://www.flagsmith.com/
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