Video by CNCF [Cloud Native Computing Foundation] via YouTube
Don’t miss out! Join us at our next KubeCon + CloudNativeCon events in Yokohama, Japan (29-30 July, 2026), and Shanghai, China (8-9 September, 2026) 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
Video by Meta Open Source via YouTube
Pyrefly presets give you a simple way to set the strictness of your Pyrefly settings without having to configure every setting manually.
More details: https://pyrefly.org/en/docs/configuration/#preset
#pyrefly #python #opensource #pythonprogramming
Video by FINOS via YouTube
Jerome Andrews (Director of Open Innovation Initiatives at DTCC) and Greig Cowan (Head of AI & Data Science at NatWest) announce the launch of the FINOS AI Fund. Alongside Gabriele Columbro, they unveil an industry-backed governance framework designed to shift AI out of isolated sandbox prototypes and into a unified, executable, and compliance-vetted production stack.
🗽 Catch Us in New York! Ready to explore the next generation of pre-competitive financial AI? Join industry leaders at OSFF New York on November 4–5, 2026.
🎟️ Register Now: https://hubs.ly/Q04n_bZL0
🔥 20% OFF DISCOUNT CODE: 26YTOSFFNY20C
🕒 Timestamps:
0:00 Welcome: Coalescing the High-Performance Compute (HPC) Roster
1:26 AI Overload vs. The Sovereign Open Source Reality
2:32 Commercial AI Mega-Rounds and the Kubernetes Moment for AI
4:03 Introducing AI at FINOS: Bringing Banking Requirements to the Stack
5:19 The Three-Pronged Strategic AI Initiative
6:47 Governance-as-Code: Mapping Fragmented Regulations to Core Repos
8:55 Moving Past Specification: Turning Domain Use Cases into Specs
10:46 Glimpse into the Future: Spec-Driven Development via Trader X
11:46 Catalyzing the Community: Announcing the Founding Members of the AI Fund
13:06 Executive Board Scope: Pre-Competitive Investment & Adoption Paths
14:39 DTCC Keynote Kickoff: Why Market Infrastructures Demand Standardization
16:22 Cost Fragmentation: Stop Re-Solving the Same Problem Over and Over
17:15 Neutrality Advantage: Lowering the Temperature Between Buy-Side & Sell-Side
19:35 Translating Hackathon Prototypes into Hardened Solutions
21:40 NatWest Keynote: Baking Governance-as-Code into Runtime Pipelines
22:53 The Missing Integration Layer: Turning System Policy into Trust
23:29 Critical Control Questions: Authority, Boundaries, and Recovery Scenarios
25:56 Releasing Scarce Skills: Redirecting Top Engineers Away from Duplicate Compliance
26:52 Composable Continuous Control Planes & Execution Use Case Teaser
📊 The Problem: The Duplicate Compliance Engine
The financial sector is locked in an AI overload phase, where millions are burned independently inventing the exact same compliance checklists, threat intelligence pipelines, and cost-reporting metrics in isolation. These critical skills are incredibly scarce. Forcing data scientists and risk engineers to build proprietary versions of non-differentiating observability frameworks ties up vital talent and significantly slows down actual customer innovation.
🏗️ The Solution: The FINOS AI Fund Control Plane
Founding members DTCC, Morgan Stanley, RBC, and NatWest have pooled capital and technical expertise to formalize a neutral, open industry core:
The Continuous Control Plane: Fusing architectural blueprints (CALM), multi-cloud profiles (CCC), and workflow automation (Flux Nova) into a modular, live runtime checker.
Neutral Collaboration: Creating a secure forum where buy-side and sell-side firms can align on pre-competitive safety rails without intellectual property or commercial conflicts.
Specification-Driven Development: Turning complex regulatory codes (like OSFI standards or the EU AI Act) into open executable software parameters instead of dusty compliance text files.
⚙️ Why This Matters for Financial Engineering
Hardening Prototypes: The fund provides the direct investment and framework infrastructure necessary to bridge the gap from flash-in-the-pan hackathon proofs-of-concept to long-running, hardened banking applications.
Bounded Multi-Agent Systems: Establishing deterministic, code-enforced leashes directly inside system runtimes to track token consumption and step-intervene if an AI model encounters operational anomalies.
🌐 More about FINOS: https://www.finos.org/
📧 Join our newsletter: https://www.finos.org/sign-up
🎙️ Listen to our Open Source in Finance Podcast: https://www.youtube.com/@FINOS/podcasts
LinkedIn: https://www.linkedin.com/company/finosfoundation
#FINOS #OSFFNewYork #AIFund #AIGovernance #SovereignAI #FinTech #HPC #FluxNova #DataScience #RiskEngineering
Video by Open Data Science and AI Conference via YouTube
In this episode of the ODSC Ai X Podcast, host Dan Gerlanc speaks with Scott Askinosie, Senior Principal AI Engineer at Steel Engine, an AI workspace for building AI agents.
In this conversation, Scott explains why production agent failures are often less about model capability and more about the systems, governance, and workflows around the AI. The episode explores how companies can move from pilots to production-ready agentic systems, why deterministic workflows and observability matter, and why humans and agents will likely work together as part of the same operating system.
0:00 Introduction to Scott Askinosie and the episode
1:05 What breaks most often in production agent systems
3:13 Guardrails for agentic AI systems
3:55 OpenClaw, autonomy, and enterprise risk
5:13 Protecting PII and sensitive data in agent workflows
6:37 Why agents should not have direct access to passwords or keys
7:09 Use the simplest tool possible
8:02 Deterministic code, model routing, and governance
8:46 Why governance helps enterprises adopt agentic AI
9:41 Deterministic pathways, skills, and in-context learning
10:16 Orchestration as a governance layer
11:00 Lessons from OpenClaw failures and agent autonomy
12:38 Steel Engine and governance for enterprise agents
13:00 Using n8n, MCP, Airflow, and Flyte for agent workflows
14:00 Production trade-offs: cost, traceability, memory, and architecture
15:11 How AI accessibility is changing enterprise teams
16:20 From software engineers to vibe coders
17:00 Why internal AI teams are becoming more common
18:46 Build vs. buy for enterprise agentic systems
21:37 Why teams need to keep up with fast-changing AI tools
22:19 Why classical software engineering skills still matter
23:26 Learning with coding agents instead of just vibe coding
24:00 AI engineering vs. agentic engineering
24:57 Why AI will not simply replace all human work
27:29 Inference costs, layoffs, and the future of technical work
28:36 Will companies rehire engineers?
29:15 Why AI works better alongside humans
30:23 Why responsibility cannot be fully delegated to AI
31:00 Companies returning to AI after failed production rollouts
33:21 Observability and evaluations for production agents
34:16 Deterministic pipelines, step logging, and human review
34:36 Aviation use case: automating legacy workflows with agents
36:27 Favorite tracing and evaluation tools
36:49 Comet Opik, Langfuse, Grafana, and Datadog
38:00 Open models vs. commercial models in enterprise AI
39:43 What Scott is watching next in agentic AI
40:00 Mythos, Project Glasswing, and new model capabilities
40:31 Managing humans and agents together
41:00 Multimodal models, Gemini, OpenBrain, and personal AI memory
41:48 Closing thoughts
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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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
Follow-up on rebooting to update, portable power stations, glass storage, and objective news sources. Plus whether to use one ZFS pool per vdev, or just one large pool.
https://2.5admins.com/2-5-admins-307/
Video by SAP via YouTube
See how SAP Logistics Management and Joule help logistics teams detect delivery risks, resolve warehouse bottlenecks, and keep fulfillment on track.
In this demo, demand for event kits spikes just days before SAP Sapphire, creating pressure on outbound packing capacity. A logistics clerk uses SAP Logistics Management to identify delivery risks in real time, then consults Joule to assess the backlog, prioritize urgent shipments, and recommend a mitigation plan.
With SAP Embodied AI running on SAP Business AI Platform, Joule triggers an SAP Embodied AI Agent that translates delivery requirements and warehouse context into robot tasks. Through Cyberwave, autonomous robots are dynamically reassigned to restore packing capacity, reduce backlog, and support on-time fulfillment during peak demand.
The result is a closed loop from risk detection to execution: faster response, stabilized throughput, and more resilient logistics operations.
Streamline logistics with SAP Logistics Management: https://sap.to/6054BEJLVC
Chapters:
00:00 – Delivery Risk During Peak Demand
00:38 – Joule Recommends a Mitigation Plan
01:05 – SAP Embodied AI Triggers Robot Tasks
01:41 – Partner-Enabled Robot Training
02:21 – Closed-Loop Logistics Execution
Follow us on social:
LinkedIn: https://sap.to/6058BEJLn8
Instagram: https://sap.to/6059BEJLnD
Facebook: https://sap.to/6051BEJLn1
Threads: https://sap.to/6053BEJLnH
About SAP:
As a global leader in enterprise applications and business AI, SAP stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit: https://sap.to/6054BEJLny
#SAPBusinessAI #Joule #LogisticsManagement
Video by TWiT Tech Podcast Network via YouTube
We’re putting our remote streaming rig through its paces ahead of Black Hat USA 2026 — and doing it the TWiT way, with bagels in Leo’s kitchen. Tune in as we test gear, work out kinks, and see if we can toast a bagel and troubleshoot at the same time. No promises on either front.
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.
Video by Meta Developers via YouTube
Join us as we dive into Unity’s hands-first approach to XR development and show you how to build for it today. We’re welcoming Dilmer Valecillos @dilmerv, Developer Advocate at Meta, alongside Unity’s own Dave Ruddell, Alexandra Serralta, and Ketki Jadhav for a live technical deep dive into XR Hand Capture and XR Interaction Simulator.
#meta #unity #handtracking
Video by Rasa via YouTube
🤖 Everyone asks whether AI will replace researchers.
Aleks Bass sees a different future.
Instead of spending hours manually coding every interview and comment, AI can handle the repetitive work—giving researchers more time to validate insights, spot patterns, and ask better questions.
✨ More context.
📊 Better analysis.
🧠 Smarter decisions.
The future of research isn’t AI *instead* of humans.
It’s AI helping humans understand people better.
🎧 Watch the full conversation with Aleks Bass, CPTO of Typeform, on *The Dialogue Architects*.
#AI #CustomerResearch #QualitativeResearch #ProductManagement #Typeform
Video by The Linux Cast via YouTube
The LUG returns. If you want to join in – https://meet.thelinuxcast.org/lug
