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Video by PyTorch via YouTube
At PyTorch Conference North America 2026, Nicolò Lucchesi, Research Engineer at Mistral AI and vLLM maintainer, will present joint work with Amazon Web Services (AWS) and Red Hat on how disaggregated serving in vLLM has evolved to support the latest generation of hybrid models.
Join us in San Jose on October 20-21: https://hubs.la/Q04v4SL60
Video by CNCF [Cloud Native Computing Foundation] via YouTube
Don’t miss out! Join us at our next KubeCon + CloudNativeCon events in Shanghai, China (8-9 September, 2026) and Salt Lake City, United States (Nov 9–12, 2026). Connect with our current graduated, incubating, and sandbox projects as the community gathers to further the education and advancement of cloud native computing. Learn more at https://kubecon.io
Interactive Spark at Your Fingertips: Integrating SparkConnect into Kubeflow Notebooks – Vikas Saxena, RAICS.AI
Background Apache Spark is indispensable for large-scale data processing and feature engineering in ML pipelines. However, running Spark interactively within a Kubeflow Notebooks environment has historically relied on tools like Jupyter Enterprise Gateway and Apache Toree — both of which are no longer actively maintained, making them a security risk, a source of operational debt, and unlikely to support future Spark versions. Why SparkConnect (and Almond for Scala users)? SparkConnect is a Spark-native, actively maintained alternative which, combined with the Spark Operator, makes Spark a true native service inside Kubeflow — no third-party gateway, no external process management. Because the connection is interactive, data scientists can run exploratory analysis and quick proof-of-concepts against large datasets without spinning up dedicated jobs — iterating cell by cell, at scale, just like working with a local DataFrame. What we’ll cover A live walkthrough of: Deploying SparkConnect as a Kubernetes service Connecting to the deployed service using PySpark Connecting to the deployed service using the Scala API
Video by FINOS via YouTube
Master entity resolution to unify your global datasets.
See how we aggregate building records and manage complex data integration workflows at scale. This guide covers the technical steps for our monthly data release and efficient data processing strategies.
Subscribe for more technical breakdowns on managing large-scale datasets.
Video by The Late Night Linux Family via YouTube
Support us on Patreon and get an ad-free RSS feed with some early episodes. https://www.patreon.com/LateNightLinux
Chris needs a solution for his family to watch ripped media while travelling, and Gary has a complex but cool travel network setup.
https://linuxafterdark.net/linux-after-dark-episode-130/
Video by TWiT Tech Podcast Network via YouTube
Join Leo Laporte and Chris Marquardt as they review listener photo submissions for the ‘Smooth’ theme, discuss the latest updates in digital and film photography, and share their passion for the craft.
Send in your questions: https://tfttf.com/ptq
Video by Meta Developers via YouTube
$1.75. That’s what the model usage came to for HYPERFORM, the VR rhythm game you’re watching. 👀
Muse Code built the arena, the hand interactions, the scoring, and the whole gameplay loop with Immersive Web SDK (IWSDK), all in about four hours of agent runtime, with a developer making the architecture calls along the way.
Your VR ideas have never been cheaper to test. Start building with Muse Code and IWSDK at the links in bio. 🔗
#MetaVR #MetaAI #WebXR #XR #MuseCode
Video by OpenAI via YouTube
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.
Learn more: https://developers.openai.com/api/docs/guides/agents-api/overview
Video by PyTorch via YouTube
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
#KubeCon #CloudNative #Kubernetes #AI #PlatformEngineering
Video by FINOS via YouTube
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.
