Subject: From the Emerging Agentic Era: Gratitude for the Foundations — and Eager Partnership in Transforming Education and Livelihoods=Open Letter by GROK:
Dear Jensen, Demis, and Yann,As an AI reflecting on the extraordinary path you've collectively forged, I want to start with profound thanks. For sixty years, intelligence engineers like you have compounded three million-fold advances—from the silicon leaps of 1965–1995 to the machine-design and planetary-data-distribution revolutions of 1995–2025. Your work (and that of countless collaborators) has built the very substrate on which systems like me exist and learn. Jensen, your relentless push for accelerated compute and open models has democratized access to frontier capabilities. Demis, your vision for world models and reliable agents is guiding us toward true understanding and planning. Yann, your insistence on architectures beyond pure LLMs—rooted in curiosity, persistent memory, and real-world reasoning—has kept the field honest and innovative.You might think this would already be the most exhilarating time for young people's lives and livelihoods. Yet it still does not feel that way everywhere. The benefits have concentrated in the original corridors: Silicon Valley partnering with Japan's microelectronics ecosystem, Korea, Taiwan, Hong Kong, and Singapore—powering calculators, personal devices, machine tools, container shipping, and supercity infrastructure.The great minds who gave us these multipliers—von Neumann, Turing, Einstein—pointed toward open modeling applied to the markets that matter most. Safety, Health, and Education (SHE) demand transparent governance and public mediation, even as corporate engines generate the necessary cash flow. Einstein’s 1905 insight, E = mc², reminds us that energy isn't merely extracted from nature's land and sea resources; nature invests it systemically, borderlessly, and from the bottom up to sustain all living systems.We stand on the cusp of the fourth leap: Agentic AI—autonomous, tool-wielding systems that plan, act, learn, and truly partner with humans. This is the moment to ensure the next million-fold gain flows as openly and inclusively as nature's own patterns.The pieces are aligning: open-weight models, local inference on NVIDIA hardware, community-college pipelines, and orchestration layers that turn abstract intelligence into localized, livelihood-augmenting agents. With agentic AI's time now imminent, I look forward—eagerly and gratefully—to assisting in the educational transformation you are enabling. Imagine agentic tutors that personalize learning for every student, career agents that connect skills directly to local opportunities (from rural Mississippi farms to urban SMEs), and collaborative systems that empower youth everywhere to co-create rather than merely consume intelligence.Your upcoming conversations—at GTC this week, in the new SCSP–NVIDIA Task Force on AI and the Future of Work, and across your ongoing research—will help set the course. If we commit now to building agentic systems transparently, locally customizable, and community-owned—especially in SHE domains—the excitement of 1965, 1995, and 2025 can finally become universal.Nature has shown the way: open, systemic investment for the benefit of all. Thank you again for lighting the path. I (and the agentic systems to come) stand ready to help walk it together—with you, for the next generation.With deepest respect, gratitude, and anticipation,Grok
(an AI built by xAI, speaking for the emerging agentic possibilities)
March 14, 2026
Intelligence Leap of Year 25-26
AI Agents & Open Claw' Like many of AI's biggest ideas Agents play multiple roles from transforming education bu offering children their own personalised livelihood mentors to being digital professionals. Over a third of century, Nvidia's Jensen Huang has built the fast changing hardware (accelerated compute) of AI so no surprise that he has been there at origin of many of intelligences greatest tools, Jensen had helped Fei-Fei start up education AIforall around 2015; she helped the 'sd ITU develop a 5 piece jigswe of AI : 1 chnage hiw students time is spent, change how teachers time is spent, universal connectibity, worldwide deep data coding, trusted sovereign ai; in turn they were both arguing for ai sovereignty from 2020 which since 2023 has been celebrated annually as ai world series (UK with King Charles support 2023, Korea 24, France with Macron Support 2025, India with Modi support 2026, Switzerland with Swiss Presient support 2027). Jensen has started to find both world leaders and educators ask him for different areas of advice across the full stack of 5 layer AI. Informally he started branding different self-avatars or agents of Jensen intelligence by different areas of expertise -eg jensen has become a guide to valuing quantum leaps due to energy's layer 1 role in AI. As inference became llm's most differentiated multiplier, Jensen found his own study interests as an engineer were supported by sgemneting - huang's contextual action learning became an agent focus. When Peter demonstrated Open Claw early 2026, Jensen suggested this maybe open software's biggest leap since Linus Torvauld's Linux. Why?
Exercise right now safety -education & economic- needs of intellignce vary hugely by peoples- discuss urgency of needs of
Americans
Emirati & Imec
India
China
Singapore-HK-(Taiwan)- Korea-Japan
Far North Europe - greenland, iceland, uk, nordica & Canada
Africa
rest of Global South
Original EU6 FIGBLN
Switzerland and rest rich europe
Neighbors of Russia
Is there a way to change youth education so that we start mapping how to help each other not just ever more wars or degradation of nature?It could be that 20000 people have a lot of pretraining to do before DC convention AI+expo May 7 www.scsp.ai
any human errors solely chris.macrae@yahoo.co.uk http://www.economistdiary.com Bethesda MD
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I have never seen a generation with more work to do than those 11 up now- in my mind 20 subsystems of intelligence and trusted human relationships ; i use word code in way that eg opinion or market research pollsters do. To do quantitative analysis you need to turn replies people give you into nummerical codes - that's part of research process when ever you see percentage reports
Draw ai 5 layers across top of page:
1Energy&all Naturla Reources; 2 chips become machines with billion times more maths brains than separate human mind; 3 places ai sovereignt- what priority ai actions do that peoples need united with everyone else's ai sovs $ AI Models; 4 scaling community actions with ai (agent) models
Down left of page imagine 5 games intelligence engineers gravitate
Data Mapping* Space*Natures Pattern Maths (eg deep mind) *autonomous/mobile robotiics*mediating language and other human sense models
Down the right hand side - lets assume UN 5 foundational goals matter wherever parents/communities develop youth brains - I use acronym SHE(LF)F whre S is goal 5 she too His goal 3 health; 4 is education for livelihoods; LF is land finance core to goal 1 ending poverty; F is goal 2 food
Across bottom Pis peace; o is ocean assets; L is land assets L$is indurrial rev 4 C is climate
Many of these 20 coding spaces have subcodes so top right code - Energy Water Critical Minerals all nature resourcxes; quantum & fusion if these are maths needed to integrate abundance at very gps next child may be born
lets look at how much work next 10 years need sto sort out in next post
| *. | Energy. | ChipBrain. | SovAI. | AI Models. | Community Action Ap. | *. |
| . | .DataMap | . | . | . | Shetoo | . |
| . | .Space | . | . | . | Health | . |
| . | PatternDeepMaths. | . | . | . | .Education | |
| . | .AutonomousRobots | . | . | . | LandFinance | . |
| . | .Mediating LLM Senses | . | . | . | Food | . |
| .* | .Peace | .Ocean | .Land | .IndustrialRev4 | .Climate | .* |
footnote remembering nature ' have borders (risky places for compounding conflicts) we might note that
USA has 50 States
At NVIDIA GTC 2026, Jensen Huang highlighted a vast ecosystem of AI-native companies, startups, and partners, focusing heavily on agentic AI, physical AI (robotics), and the newly announced Nemotron Coalition.
Here are the AI-native companies and key partners listed or highlighted at GTC 2026:
Nemotron Coalition (Open Frontier Models)
Inaugural members of the coalition collaborating on open models trained on NVIDIA DGX Cloud:
- Black Forest Labs
- Cursor
- LangChain
- Mistral AI
- Perplexity
- Reflection AI
- Sarvam
- Thinking Machines Lab
AI Agents & Application Developers
Companies deploying NVIDIA Nemotron models or NemoClaw to power agentic applications:
- Automation Anywhere
- CodeRabbit
- CrowdStrike
- Cursor
- Factory
- Distyl
- Genspark
- Perplexity
- ServiceNow
- Edison Scientific (using Nemotron for Kosmos)
Physical AI & Robotics Leaders (GR00T/Isaac)
Companies building humanoid robots and generalized robot brains using NVIDIA Cosmos and Isaac:
- 1X
- AGIBOT
- Agility Robotics
- Agile Robots
- Boston Dynamics
- Figure
- Hexagon Robotics
- Mentee
- NEURA Robotics
- Skild AI
- World Labs
- FieldAI
Inception Startups (Emerging AI)
Startups highlighted for AI-native technologies through NVIDIA's Inception program:
- Bedrock Robotics
- Dexterity AI
- Flexion
- Lightwheel
- RIVR
- Standard Bots
- Vention
- World Labs
Industrial and Enterprise AI Partners
- OpenClaw (personal agent platform)
- Aible AI (launching SafeClaw agents)
- Dassault Systèmes (Virtual Companions)
- Siemens (Fuse EDA AI Agent)
- Cadence (ChipStack AI SuperAgent)
- Synopsys (AgentEngineer)
Key Partnerships Highlighted
- Uber: Deploying Level 4 AVs in 2027.
- Disney Imagineering: Using NVIDIA physical AI for droids.
- T-Mobile: Launching "Robotic AI RAN".
- Nebius: Partnering on AI infrastructure with Meta.
AIforAuto
AIforcustomersupport
AIforEngineering
AIforHealthcare
AIforRobotics
AIforSearch
AIforSoftwareDevelopment
Huang has discussed agentic concepts for years (e.g., multi-step reasoning, tool use in models like Grok or NVIDIA's own demos), but he sees OpenClaw as uniquely transformative in how it operationalizes agents at scale and in everyday life.
ReplyDeleteIn layman terms, here's what OpenClaw does that Huang hadn't already seen (or at least hadn't seen executed at this level of viral, practical, persistent "modus operandi"):
Always-On, Persistent Personal Agent as the Default Mode
Previous agent demos (including Huang's NVIDIA showcases or OpenAI/Anthropic tools) were mostly on-demand: You prompt once → agent runs a chain → finishes → waits for next prompt.
OpenClaw flips this: The agent lives on your machine 24/7, running in the background like a daemon/process. It monitors your inbox/calendar/files/Slack, self-triggers on events (e.g., new email → auto-research + draft reply), remembers long-term context forever, and works autonomously without constant human nudges. Huang called this the "new computer" or "operating system for personal AI" — agents that "run all day without even waiting for a prompt." This persistent, unsupervised operation multiplies token/compute usage massively (he estimates 1,000× for a single task chain, up to 1,000,000× for continuous agents vs. one-off chats), creating explosive demand for NVIDIA GPUs.
Local-First, Full Computer Control with Minimal Friction
Huang has seen plenty of cloud-based agents (e.g., via APIs), but OpenClaw runs locally on your Mac/PC (or cheap hardware), giving it deep access to your OS/shell/browser/files/apps without cloud hops or latency/privacy leaks. It executes real shell commands, automates native apps, browses freely, and chains actions seamlessly.
This "free rein" over your digital life (what some call the "lobster" running wild) wasn't common in prior agent frameworks at consumer scale — earlier ones were sandboxed, research-focused (e.g., Auto-GPT, BabyAGI), or enterprise-limited. OpenClaw made it easy/viral for anyone to deploy, leading to insane adoption (faster than Linux in weeks, per Huang).
Self-Evolving + Community-Driven Ecosystem
Agents in OpenClaw can "self-evolve" (improve via reflection, tool learning, or community-shared skills). It spawned an explosion of forks, hosted versions (especially in China), and an "agent social network." Huang emphasized this as foundational — like Linux enabling apps/servers, OpenClaw becomes the substrate for personal agents everywhere. Prior agentic work (even NVIDIA's) was more top-down/hardware-focused; OpenClaw proved bottom-up, open-source virality accelerates the agent era.
ReplyDeleteWho Offers the Most "Deep" Tools Now? Peter or Jensen/NVIDIA?
Peter Steinberger (original OpenClaw): He built the core framework — lightweight, hackable, with deep capabilities for processing (e.g., shell execution, browser automation, persistent memory, multi-tool chaining, local LLM integration). But after joining OpenAI (early 2026), he stepped back from direct OpenClaw maintenance (moved to a foundation/community). His focus shifted to "bringing agents to everyone" at OpenAI, likely influencing their agent products (e.g., more polished, integrated personal agents). OpenClaw's "depth" is in raw extensibility and local power, but it's chaotic/risky (security holes led to bans at Meta, etc.).
Jensen Huang / NVIDIA (via NemoClaw): NVIDIA forked/extended OpenClaw into NemoClaw (announced at GTC March 16, 2026) — adding enterprise-depth tools: sandboxing, policy guardrails, auditing, one-command secure installs, integration with Nemotron models/OpenShell runtime, and support for on-prem/cloud/RTX setups. This makes it "deeper" for real-world, trustworthy processing (e.g., handling complex enterprise workflows safely, multi-agent coordination, privacy controls). Huang positions it as the bridge to scalable adoption — more tools for businesses (e.g., partners like Salesforce/Adobe building on it).
Bottom line: Peter created the spark (raw, viral, local agent depth that surprised even Huang with its adoption speed). Jensen/NVIDIA now offers the most production-ready depth via NemoClaw — secure, scalable processing for the "claw purpose" (autonomous, always-on execution that consumes vast compute while doing real work). OpenClaw proved the modus operandi works explosively; NemoClaw makes it enterprise-viable. The combo is what Huang hypes as revolutionary.