Videos

Video by Open Data Science and AI Conference via YouTube

Want to learn more about AI in person? Check out ODSC AI West 2026, coming to Burlingame this October 27th-29th: https://hubs.li/Q04cYsmk0

#DataScience #AI #ArtificialIntelligence #ODSCAI

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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

Reports of desktop Linux adoption numbers are probably exaggerated, the Steam Frame seemingly gets closer, Valve’s European logistics partner leaks people’s data, Proxmox gains Arm64 support, GNOME Boxes makes some changes, and a quick KDE Korner. With guest hosts Chris from Linux After Dark, and Sean from Hybrid Cloud Show.

https://latenightlinux.com/late-night-linux-episode-398/

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Video by SAP via YouTube

Danish wholesaler Lemvigh-Müller transformed manual document handling with SAP Business AI. The company automatically processes incoming business documents, including orders, delivery notes, and invoices received as PDFs and emails, reducing manual work and helping teams focus on execution rather than paperwork.

Discover how a 200-hour AI project became a scalable foundation for broader business process automation.

0:00 – Why Supply Chain Efficiency Matters
0:27 – About Lemvigh-Müller
0:36 – SAP Business AI Automates Document Processing
1:06 – From Manual Work to Intelligent Dashboards
1:21 – Scaling Automation Across Business Processes
1:38 – How to Start Small and Succeed with AI

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Video by TWiT Tech Podcast Network via YouTube

MacBreak Weekly covers all things Apple: Leo, Andy Ihnatko, Jason Snell, and Christina Warren analyze every bit of news from the most interesting company in tech. From AI to Vision Pro, iPad to iPhone, these Apple experts know-all and tell-all.

You can find more about TWiT.tv and subscribe to our full shows at https://podcasts.twit.tv
Join our community at Club TWiT: https://twit.tv/clubtwit

About us:
TWiT.tv is a technology podcasting network located in the San Francisco Bay Area with the #1 ranked technology podcast This Week in Tech hosted by Leo Laporte. Every week we produce over 30 hours of content on a variety of programs including Tech News Weekly, MacBreak Weekly, Windows Weekly, Security Now, Intelligent Machines, and more.

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Video by Meta Developers via YouTube

Bad reviews shouldn’t be your crash detection system. 🔍😵‍💫

We added automatic quality alerts for Meta Quest that monitor crash rates, frame rates, startup time, and star ratings after every release. Subscribe once, catch problems before your players do.

That’s just one of seven updates covering pricing, free trial conversion, audience analytics, and more.

🔗 Explore the expanded toolkit at the link in the comments.

#MetaQuest #VR #VRDev #GameDev #XR

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Video by The Linux Foundation via YouTube

AI spending is accelerating faster than most organizations can track it, and the billing data coming from model providers and cloud platforms is not yet granular enough to tell teams where the money is actually going. Without a common framework, engineering and finance teams are flying blind on one of the fastest-growing line items in their budget.

In this exclusive interview with Swapnil Bhartiya at TFiR, Mike Fuller, Member of the Technical Staff, Tokenomics Foundation, breaks down how organizations can gain visibility into AI token spend, connect costs to business outcomes, and build governance before budgets spiral.

Key Topics Covered:
– Why token cost applies to both API-based inference and on-premises model deployments, including hardware procurement, energy, cooling, and lifecycle management
– How the Tokenomics Foundation structures AI value across three domains: production, consumption, and monetization, and where the biggest efficiency opportunities sit today
– The critical gap between cloud billing data and observability telemetry, and why teams must pair both data sets to understand cost at the team, application, and operation level
– Practical first steps for organizations already mid-journey on AI adoption, including scoping internal productivity AI versus customer-facing product AI separately
– Why optimizing token consumption can degrade output quality, and how the industry needs new tooling and best practices to balance cost and performance without compromising results

Read the full story and transcript at www.tfir.io

#Tokenomics #FinOps #AIInfrastructure #TokenCost #LLMOps #AIGovernance #GenAI #CloudCost #LinuxFoundation #OpenSource #AIStrategy #FinOpsFoundation #AIOperations #MachineLearnignOps #TechLeadership

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Video by OpenProject | Open Source Project Management via YouTube

The release brings various features and improvements for you.

0:00 – Introduction
0:20 – New organizational management capabilities
1:47 – Resource management (Enterprise add-on)
3:17 – Backlog and sprints improvements
3:55 – PM²/PMflex enhancements
4:51 – Wiki improvements

Find out more about all features and improvements in our release notes: https://www.openproject.org/docs/release-notes/17-7-0/

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Video by OpenAI via YouTube

Model ML is solving the “last-mile problem” in finance, carrying asks from research to analysis to a finished PowerPoint deck or Excel workbook with traceable sources.

When Model ML tested GPT‑5.6 Sol in its Composite, the results “blew every metric out the water,” says Co-founder and CEO Chaz Englander:

⚡ 21% fewer tokens per PowerPoint deck than Fable 5
✅ A 16.6 percentage-point lead over Opus 5 on decks ready for substantive review
📊 36% fewer tokens per Excel workbook than Opus 5

Watch Englander walk through Model ML’s evaluation process, then read the full story about how they use the model in production here: https://openai.com/index/model-ml/

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Video by Hugging Face via YouTube

Prompt caching can cut the input cost of long AI agent sessions dramatically—but only when your harness preserves reusable prompt prefixes. This video explains what prompt caching actually stores, why agent costs compound across turns, how provider behavior differs, and the implementation mistakes that invalidate your cache.

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🔗 *Links*
– Written tutorial: https://alejandro-ao.com/tutorials/prompt-caching/
– Tau coding agent: https://github.com/huggingface/tau
– Pi coding agent: https://github.com/badlogic/pi-mono
– Hugging Face Inference Providers: https://huggingface.co/docs/inference-providers/index
– OpenAI prompt caching: https://platform.openai.com/docs/guides/prompt-caching
– Anthropic prompt caching: https://docs.anthropic.com/en/docs/build-with-claude/prompt-caching
– Gemini context caching: https://ai.google.dev/gemini-api/docs/caching

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👋 *Connect with me*
– My website: https://alejandro-ao.com/
– X (Twitter): https://x.com/_alejandroao
– LinkedIn: https://www.linkedin.com/in/alejandro-ao/

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🤓 *Topics Covered*
– How prompt caching works
– AI agent token cost reduction
– Cache-friendly agent harness design

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⏱️ *Timestamps*
0:00 Why long AI agent sessions get expensive
0:45 What prompt caching actually caches
5:55 Provider pricing and cache discounts
9:19 Prompt caching best practices
15:40 Summary and cache monitoring

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Video by CNCF [Cloud Native Computing Foundation] via YouTube

CNCF Ambassador Hrittik Roy started by building student communities. Now he’s helping teams optimize for the AI wave.

#Shorts #CNCFAmbassadors #CloudNative #AI

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