Jak fyzická AI kombinuje velké modely, simulace a digitální dvojčata pro bezpečné, rychlé a škálovatelné nasazení robotů ve výrobě, stavebnictví a autonomní dopravě.

Fyzická AI v průmyslu: simulace a digitální dvojčata mění robotiku

Co bude dál v robotice? Jak fyzická AI, simulace a digitální dvojčata mění průmysl

By combining decades of real-world data with advanced AI, simulation and digital twins, teams are rapidly training, validating, and deploying intelligent robotics at scale.

Physical AI is reshaping how intelligence moves from data into the real world with leaders like AgiBot, Franka Robotics, Caterpillar, and PlusAI driving the transformation. 

From construction and manufacturing to autonomous operation, this fusion of simulation and AI is unlocking new capabilities for industrial machines and redefining what robotics can do in the physical world.

Explore NVIDIA Robotics: https://nvda.ws/4rYamRr
Build with NVIDIA Isaac: https://nvda.ws/4cx3llY
Unlock world foundation models with Cosmos: https://nvda.ws/4cw5uhN
Learn more about Physical AI: https://nvda.ws/4qJBSRF 

Thumbnail Image Courtesy of Caterpillar

What’s Next in Robotics?

Naučte se, jak Lyria 3 v Gemini generuje plně aranžované soundtracky z textu nebo nahrávky. Praktické tipy na prompty, nastavení parametrů a použití v videích, podcastech a hrách.

Vytvořte soundtrack za pár sekund s Lyria 3 v Gemini

Lyria 3 | Generování hudby přichází do Gemini

Create custom soundtracks in Gemini 🎼Describe your vision or upload from your camera roll and watch a track come to life in seconds. The soundtrack to your imagination is just a prompt away. Explore the new music generation feature in Gemini. 

https://gemini.google.com      

#Lyria #Lyria3 #GoogleGemini

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Lyria 3 | Music Generation comes to Gemini

Proč 'cost per token' nahrazuje FLOPS a jak extreme co‑design (hardware, síť, software) snižuje náklady na inference u LLM a MoE modelů.

Snižte cost‑per‑token: Extreme co‑design pro efektivní tokenomics a škálovatelnou AI

Extreme Co-Design pro efektivní tokenomics a škálovatelnou umělou inteligenci

As AI moves into the era of real-time reasoning, performance alone is no longer enough. The true measure of AI at scale is efficient tokenomics—how much it costs to generate each token of intelligence.
Reasoning models like mixture-of-experts (MoE) architectures generate massive volumes of tokens, improving answer quality but placing simultaneous pressure on compute, memory, networking, storage, and software. In this new paradigm, the hidden costs of communication and routing matter just as much as raw FLOPS.

This video explores why extreme co-design—engineering the entire stack as one unified system—is the key to lowering cost per token and maximizing AI ROI.  

You’ll learn:
- Why cost per token is becoming the defining metric for reasoning AI
- The networking and communication challenges behind MoE inference
- How rack-scale systems like GB200 NVL72 deliver breakthrough token efficiency
- How Blackwell and Ruben integrate silicon, interconnect, networking, and software to power AI at scale

Featuring insights from NVIDIA, Signal65 Microsoft Azure, and CoreWeave, this discussion makes one thing clear: End-to-end system design is the most powerful lever for delivering efficient tokenomics and scaling reasoning AI.

Extreme Co-Design for Efficient Tokenomics and AI at Scale

Jak Codex provádí self‑verification: spouští testy, nasazuje aplikaci a kontroluje logy, aby refaktoring nezpůsobil ztrátu observability a zkrátil rutinní práci.

Codex ověří kód a ochrání observability při refaktoringu

Codex zkontroluje svou práci za vás

Javi walks through a logging refactor and shows why Codex's self-verification is a step change: the model runs the app, finds the right session, and proves logs still flow.

Takeaways:
- Codex can validate its work by running tests and launching the app.
- It excels at broad refactors that touch many files.
- The model can find session IDs and query tools on its own.
- Verification collapses a risky manual loop into minutes.

When the agent can prove correctness, you can move faster with less risk.

Chapters:
00:00 Why Codex has been a step change
00:18 Self-verification: run tests and launch the app
00:52 The task: a logging refactor across many files
01:10 The risk: do not break observability
01:28 How this used to be verified manually
01:35 Ask the model to verify logs end-to-end
01:50 It finds the session ID and queries logs MCP
02:03 Proof: logs still pipe, task done fast

Codex checks its work for you

Deep research v ChatGPT nyní běží na GPT‑5.2: cílené prohledávání aplikací/domén, sledování průběhu v reálném čase, fullscreen reporty a přesnější citace. Postupné nasazení uživatelům.

Deep research v ChatGPT přechází na GPT‑5.2 — rychlejší a přesnější rešerše

Aktualizace deep research v ChatGPT: Deep research nyní poháněno GPT-5.2

Deep research in ChatGPT is now powered by GPT-5.2.

Now in deep research you can:
- Connect to apps in ChatGPT and search specific sites
- Track real-time progress and interrupt with follow-ups or new sources
- View fullscreen reports

Rolling out starting today.
https://chatgpt.com/features/deep-research/

Updates to deep research in ChatGPT

Objevte fun-first strategii Allie K. Miller: jak AI nasadit hravě a efektivně — ne jen pro úsporu času, ale pro lepší práci, nové možnosti a rychlé experimenty.

Fun-first přístup k AI: praktický návod od Allie K. Miller

The Fun-First Framework for AI Adoption s Allie K. Miller

Allie K. Miller has a rare superpower: she makes the cutting edge of AI feel clear, practical, and genuinely fun. Recently named to TIME’s list of the most influential people in AI, Allie has become one of the internet’s most trusted guides—breaking down new models, tools, and workflows for millions, from curious beginners to seasoned builders. In this episode, she joins Cameron Adams to unpack what’s coming next: agentic browsers, “AI-first” reinvention, and why productivity alone can be a trap. Along the way, she shares a simple prompt structure that unlocks better outputs, how to turn fear into agency, and why creativity is often the fastest on-ramp to adoption. Plus: a delightfully weird prediction about how we’ll perceive the world.

Cam's notes on Substack: promptedwithcam.substack.com

Timestamps: 
00:00 - Introduction
01:45 - The Prompt
04:07 - Creative All Hands
13:39 - Use AI to simulate future scenarios when convincing teams to change.
15:30 - Let small teams move ahead instead of waiting for company-wide adoption.
17:37 - Use AI to enable work that was previously impractical to do manually.
20:23 - Use creative AI tasks as an entry point before work use cases.
23:32 - Encourage skeptics to try AI even if they expect to dislike it.
24:40 - Ask permission before introducing AI into group conversations.
26:21 - Try this prompt structure: who you are, your objective, then context.
28:07 - Add goals, fears, constraints, and resources to improve AI responses.
31:29 - Photograph handwritten notes or post-its and upload them as AI context.
43:29 - Use AI to analyze patterns across multiple past conversations.
52:10 - Turn one detailed input into multiple formats like decks or videos.
1:01:08 - Design Reveal
1:02:48 - Key Takeaways

Links
Subscribe to the Prompted Newsletter: https://promptedwithcam.substack.com/ 
Cam on LinkedIn: https://www.linkedin.com/in/themaninblue/ 
Allie on LinkedIn: https://www.linkedin.com/in/alliekmiller/ 

Link to Allie, Tisha and AI’s Creative Collaboration: https://promptedpodcast.com/episode-9

The Fun-First Framework for AI Adoption with Allie K. Miller

Praktický postup pro PM: jak pomocí Codex skills rychle najít příčinu selhání v Buildkite, nainstalovat token a vyřešit PR selhání bez zbytečného pingování vývojářů.

Codex pro produktové manažery: rychlá diagnostika CI bez rušení inženýrů

Jak produktoví manažeři používají aplikaci Codex

Alexander Embiricos (a Product Manager on the Codex team) shows how he uses Codex skills to make a small product change, diagnose a Buildkite failure, and improve the skills so the next PR goes faster.

Takeaways:
- Skills are a shortcut for repeated workflows like Buildkite logs.
- When a skill fails, fix the root cause and update the skill.
- The real win is compounding: the codebase gets easier over time.

This is the loop: ship the fix, then teach the workflow.

Chapters:
00:00 PM context: careful before tagging engineers
00:16 A confusing button and a quick team check
00:32 Delete the button, then hit a PR failure
00:46 Use the Buildkite skill instead of digging through logs
01:09 Install the Buildkite token
01:20 Update the skill so it works next time
01:53 Inductive loop: feedback - fix - improve the skill
02:06 Compounding payoff: Codex gets better over time

How PMs use the Codex app

Rozhovor s Asadem Awanem o tom, jak ChatGPT zavádí reklamy bez ovlivnění odpovědí: technické a vizuální oddělení, ochrana soukromí a ad‑free pro předplatitele.

Reklamy v ChatGPT: jak zachovat důvěru, soukromí a design

Epizoda 13 – Myšlení za reklamami v ChatGPT

How should advertising work in an AI product? Asad Awan, one of the ad leads at OpenAI, walks through how the company is approaching this decision and why it’s testing ads in ChatGPT at all. He explains how ads are built to stay separate from the model response, keep conversations with ChatGPT private from advertisers, and give people control over their experience.

Chapters
00:00:29 — Mission and principles
00:04:01 — Separation between ads and answers
00:07:31 — Who will see ads
00:08:52 — Internal input and decision-making process
00:11:06 — Controls and how ads will work
00:15:53 — Guardrails for sensitive conversations
00:17:33 — Skepticism about ads
00:20:26 — Helping small businesses
00:24:13 — Future of ads

Episode 13 - The Thinking Behind Ads in ChatGPT

Codex představený na Super Bowl 2026 s heslem „You Can Just Build Things“ mění vývoj — praktický průvodce, koho osloví, jak funguje a co můžeš začít stavět dnes.

OpenAI Codex: Jak AI umožní každému stavět produkty

OpenAI Super Bowl 2026: Codex — Můžeš prostě stavět věci

We build the tools. You build the future. Start building with Codex. 

https://openai.com/codex/

OpenAI Super Bowl 2026 | Codex | You Can Just Build Things

Jak kombinovat Git worktrees a Codex pro paralelní vývoj: izolace kontextu, delegování PR, lepší výsledky s Figma a praktické tipy na řešení chyb.

Codex a worktrees: delegujte úkoly a dokončujte více PR současně

Multitasking s aplikací Codex: jak delegovat práci a zůstat produktivní

Joey demonstrates multitasking with Codex worktrees: delegate a drag-and-drop feature in one worktree while continuing local work, then review and apply both PRs.

Takeaways:
- Worktrees let you delegate tasks and keep moving in parallel.
- Keep local momentum while Codex works in the background.
- Use quick questions and comments to correct issues mid-flight.
- The mindset shift is from line-by-line edits to architecture and flow control.

Parallel workflows turn waiting time into progress.

Chapters:
00:00 Work trees enable parallelism
00:20 Example feature: reorder pinned tasks
00:33 Kick off drag-and-drop in a work tree
00:52 Keep working locally while Codex runs
01:27 Spot a bug: the branch is created twice
01:53 Provide Figma context and check other PRs
02:06 Multiple PRs finish in parallel
02:23 Apply the drag-and-drop changes
02:40 Review the result
02:47 Mindset shift: architecture over individual lines
03:04 Context switching and good stopping points

Multitasking with the Codex app

Reportáž o tom, jak Red Gerard díky ranému tréninku, kreativitě a mentální odolnosti vyrostl v olympijského šampiona ve freestyle snowboardingu. Praktické lekce pro závodníky i trenéry.

Cesta Reda Gerarda k olympijskému zlatu: trénink, technika, hlava

Jak se Red Gerard stal tak dobrým? | Google + Team USA

Red Gerard, Team USA’s youngest snowboarder to win a gold medal at the Winter Olympics, is back for more. But how did he get so good, so young? Get the story by searching with AI Mode.


The use of Olympic Marks, Terminology and Imagery is authorized by the U.S. Olympic & Paralympic Committee and LA28 pursuant to Title 36 U.S. Code Section 220506

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How did Red Gerard get so good? | Google + Team USA

Podrobný rozbor ikonických triků Chloe Kim: switch double cork 1080, frontside 1080 v halfpipe, amplitude, graby a jak rozhodčí hodnotí risk vs. reward.

Chloe Kim — rozbor ikonických triků: switch double cork 1080 a frontside 1080

Jaké jsou ikonické triky Chloe Kim?

Team USA snowboarder Chloe Kim has already made history, but she isn’t done yet. Go further and search with AI Mode to dive deeper into her tricks, records, and more.


The use of Olympic Marks, Terminology and Imagery is authorized by the U.S. Olympic & Paralympic Committee and LA28 pursuant to Title 36 U.S. Code Section 220506

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