Top New Features in SAP HANA Cloud | Q2 2026 Release Highlights

Top New Features in SAP HANA Cloud | Q2 2026 Release Highlights

Video by SAP via YouTube
Top New Features in SAP HANA Cloud | Q2 2026 Release Highlights

Discover what’s new in SAP HANA Cloud Q2 2026 in under 7 minutes.

Join Thomas Hammer, Lead Product Manager of SAP HANA Cloud, as he walks through the key innovations in our Q2 2026 release, including custom database object knowledge graphs, new database object discovery and data retrieval tools, knowledge graph engine innovations, larger SAP HANA Cloud database instances on AWS, deeper SAP AI Core integration, and more.

See how SAP HANA Cloud automatically creates a semantic knowledge graph from your database metadata, making it easier to discover, understand, and query enterprise data. Learn how the new Database Object Discovery and Data Retrieval tools use natural language to identify relevant data, generate SQL, and retrieve results, reducing the need for deep database expertise.

Thomas also explores the latest Knowledge Graph Engine innovations, including support for transforming knowledge graphs into property graphs and federated SPARQL queries across distributed SAP HANA Cloud environments. Together, these capabilities provide a stronger foundation for semantic search, graph analytics, retrieval-augmented generation (RAG), and AI-driven applications.

The release also introduces support for SAP HANA Cloud database instances with up to 24 TB of memory on AWS, helping organizations run larger, mission-critical in-memory workloads. In addition, deeper SAP AI Core integration brings AI-powered predictions and large language model capabilities directly into SQL workflows, making it easier to build intelligent, data-driven applications.

Finally, discover additional innovations, including the new Performance Class Advisor, automated SQL Plan Advisor enhancements, Apache Iceberg REST catalog support for lakehouse scenarios, and replication support for SAP S/4HANA CDS view entities.

Chapters:
0:00 – Intro
0:56 – Custom Database Objects Knowledge Graph
1:25 – Database Object Discovery & Data Retrieval Tools
2:30 – Knowledge Graph Engine Innovations
3:22 – Larger SAP HANA Cloud database instances on AWS
4:06 – Deeper SAP AI Core Integration
5:24 – Further innovations

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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 across finance, procurement, HR, supply chain, and customer experience. Learn more at https://www.sap.com.

#SAPHANACloud #SAPBusinessDataCloud #DataAndAI #WhatsNewInSAPHANACloud

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MacBreak Weekly 1031

MacBreak Weekly 1031

Video by TWiT Tech Podcast Network via YouTube
MacBreak Weekly 1031

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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VR Dev Level Up Episode 1

VR Dev Level Up Episode 1

Video by Meta Developers via YouTube
VR Dev Level Up Episode 1

New series alert for developers building apps for Meta Quest 🎬

VR Developer Level Up, hosted by @dilmerv, is where we dive into what’s working across the Quest ecosystem. That includes tangible success stories with the numbers behind them, platform updates, and tool walkthroughs you can follow along with.

Ep. 1 covers four developer case studies, the latest agentic tools, and a hands-on Meta VR CLI deep dive.

đź”— Watch it at the link in the comments.

#VRDev #MetaQuest #VR #GameDev #AI

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What can Linux learn from macOS?

What can Linux learn from macOS?

Video by The Linux Experiment via YouTube
What can Linux learn from macOS?

Use secure and encrypted Cloud Storage with Proton Drive: https://proton.me/drive/TheLinuxEXP

Grab a brand new laptop or desktop running Linux: https://www.tuxedocomputers.com/en#

👏 SUPPORT THE CHANNEL:
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Timestamps
00:00 Intro
00:29 Sponsor: Proton Drive
02:15 macOS 26
02:50 Look and Feel
09:32 Menubar and dock
13:58 Window management
17:53 Settings
21:56 App Store & App Installs
27:45 macOS 27
29:53 Ecosystem & mobile apps
31:36 What can we learn
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#linuxdesktop #linuxvsmac #macos

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Open Source News: Coworking, Security, and More

Open Source News: Coworking, Security, and More

Community Collaboration & Productivity Social Coworking sessions this week feature SORTEE, Vale and text linting, and debugging in R – great opportunities for open source contributors to connect and improve workflows. Swánga̱lyiatwuki-WikiWoordenboek Wiktionary project continues with Part 3, focusing on Indigenous language preservation through collaborative editing. A Reddit user shares how they gained over 1.7 … Read more

Open-Source AI Surge: Tools, Agents, and Policy Shifts

Open-Source AI Surge: Tools, Agents, and Policy Shifts

Top Stories Impacting Open-Source AI The open-source AI landscape is experiencing a significant boost from both policy shifts and innovative tool releases. White House restrictions on frontier AI models, like those from OpenAI and Anthropic, are inadvertently leveling the playing field for open-source alternatives, as highlighted by multiple sources. This regulatory environment is seen as … Read more

AI Distillation, OpenCV Cloud, and Linux News Roundup

AI Distillation, OpenCV Cloud, and Linux News Roundup

AI Distillation: Teaching Smaller Models Hugging Face’s latest live tutorial dives deep into model distillation, a technique where a smaller student model learns from a larger teacher model. The session covers four key axes—signal, data source, timing, and teacher identity—and explores methods like off-policy (training on teacher-generated data), on-policy (scoring student outputs live), and self-distillation … Read more

Advent Accelerates Deals with ChatGPT + Codex

Advent Accelerates Deals with ChatGPT + Codex

Video by OpenAI via YouTube
Advent Accelerates Deals with ChatGPT + Codex

ChatGPT + Codex are a one-two punch for investment firms.

"Having the ability to connect your deal folder with all of the context, and then be able to ask ChatGPT and Codex real time questions has been really impactful to our workflows," – Jasmine Azizi (Advent).

Financial firms hold a tremendous amount of context. ChatGPT acts like a brain layer so teams can spend more time focusing on the next big bet.

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COOL: The Official Cloud Version of OpenCV

COOL: The Official Cloud Version of OpenCV

Video by OpenCV via YouTube
COOL: The Official Cloud Version of OpenCV

Cloud Optimized OpenCV Library (COOL) delivers a high-performance build of OpenCV, enabling faster computation of core computer vision operations such as resize, adaptive gaussian, contour detection functions. This optimized edition is designed for accelerated computer vision workloads on AWS Graviton and ARM-based environments, helping developers achieve improved efficiency for AI, ML, and image processing applications. On this episode we welcome Frantz Lohier from AWS to show you the awesome performance benefits of COOL, at a price that any company can afford.

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.

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Thumbnail by Natalia de la Rosa natdlrs.com

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Training Agents 2: Live tutorial on model distillation for training custom agents.

Training Agents 2: Live tutorial on model distillation for training custom agents.

Video by Hugging Face via YouTube
Training Agents 2: Live tutorial on model distillation for training custom agents.

In this live session, we’ll cover how to transfer capability from a teacher model to a smaller student through distillation. We’ll work through supervised fine-tuning on teacher-generated data, then on-policy and online methods where the teacher scores the student live, then self-distillation where the model teaches itself. Each one runs in TRL.
What we’ll cover:

– What distillation is, and the four axes that organize it: signal, data source, timing, and teacher identity
– White-box vs black-box: distilling from open weights vs strings
– Off-policy distillation: generate from the teacher, then SFT on the outputs
– On-policy distillation: sample from the student, score with the teacher in the loop
– Distillation as reinforcement learning: the KD distance as a dense, token-level reward
– Self-distillation: the model as its own teacher, and when that beats a stronger one

Repo: https://github.com/burtenshaw/training-agents

This is part of the Training Agents series: using coding agents to design, run, monitor, and review post-training experiments, while training models to become better agents.

#TRL #HuggingFace #PostTraining #AIAgents #Distillation

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