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Video by OpenAI via YouTube
GPT-Live-1 is now available in the API.
Bring ChatGPT’s natural back-and-forth to your app, with voice agents that listen while they speak and work with the models and harness you choose.
Learn more here: https://openai.com/index/introducing-gpt-live-1-in-the-api/
Video by H2O.ai via YouTube
Connecting an agent to a new tool used to mean custom integration work every single time. MCP is the standard that removes that.
Terms covered:
– MCP (Model Context Protocol): a standardized way for AI models to communicate with external tools and data sources. One standard, many integrations.
– MCP Runner: the runtime component that manages those connections and makes sure the interactions happen reliably at scale
In practice: a healthcare organization connects an agent to patient records, scheduling and compliance tools through the same protocol. A financial services firm links market data, risk systems and reporting without rebuilding the connection layer each time.
MCP defines how agents talk to the world. The MCP Runner makes those conversations happen.
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AI Fundamentals Glossary | H2O.ai University
Full playlist: https://www.youtube.com/playlist?list=PLAWKlIKS-66E
Free courses and certifications: https://h2o.ai/university
#MCP #AIAgents #AgenticAI #AIGlossary #H2Oai
Video by OpenCV via YouTube
Pengyuan Li of IBM Research returns to OpenCV Live, following his August 2025 appearance where he introduced Granite Vision, IBM’s lightweight open vision-language model built for enterprise document understanding. This time the focus shifts from the model to the workflow: how Granite Vision pairs with Docling, IBM’s open-source document conversion toolkit, to turn PDFs, scans, tables, and charts into structured data that downstream applications and LLM pipelines can use. Expect a look at recent work, including chart-to-data extraction integrated into Docling, along with practical guidance for anyone building document processing systems.
OpenCV is a 501(c)(3) registered non-profit in the United States. See how you can support open source CV & AI: http://opencv.org/support/
Watch along for your chance to win during our live trivia segment, and participate in the live Q&A session with questions from you in the audience.
Become a paid member of the channel to help us make more episodes https://www.youtube.com/channel/UCkrcW82Y2kbgU-U9RaYfgxw/join
Got a cool project of your own? Send it to us and you may be featured https://www.jotform.com/form/233105358823151
Thumbnail by Natalia de la Rosa natdlrs.com
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
