Update June 2026- from march gtu summit - partners in nvidia health platforms (not shown 2000 digital health startup nvidia inception)
Taipei Cluster ; Softbank-Arm-Tokyo Cluster (including Arabia I), Mumbai Cluster, Memphis Cluster
6 dimeniosn intelligence world game
1 Connecting academia (eg lecun launch graduate student union without borders);
2-4 ai wizards; move to min 24.40 jensen huang https://www.c-span.org/program/white-house-event/president-trump-remarks-on-investments-in-the-us/659307 mapping business AI leadership futures
5 Sovereignty (including language-culture unitting) leaders include UK & Japan Royals, Qatar, Canada?Italy (G7 minus 1), India
6 Biotech Viral Storytellers eg Enbdy & Attenborough.
Endy agri stories eg dandelions, first 250 million protein stories, biotech continent stories, japan expo and olympics stories (also osaka track and society 5.)
Taiwan - prevent viral disasters (most successful ai containing covid); digital twin Financial Capitals Training Hospitals; whats 2nd most important digital twin service replication; ;First worldwide data collab- eg cancer (prevention) databank
end student debt and brain training of milennials whose intelligence can unite theur generation win-win gials
Is it the case that less than 25% of americans or europeans have access to both water & electricityto maximise intelligence productovity- whats ai distribution grid & gridless map to resolve this; other infrastructure chalenges where borrders have been the problem (whether uniting states or nations)
Taiwan earth 2.0 as well as eg hurricane alerts - wjy not malarai map; water angels map with Japan Emperor
memphis what is low latency 10g so no vialge left out of intel sharing; what is marryingh millennials pop and inttel stars; what is cuber brain implants;
How does open driverless city platform connect - open humanoids safety- story DeepSeek US CEO; 45 safest supercities (eg bloomberg Road of Things)
--- question did digitalisation of radiology by Hopkins Elliott Foshamn insire all of AI's deepest leaps as of june 2026 we are asking experst at FutureRealities to verify case studies around these sorts of magic brainstorming prompts of FISHMAN HUANG & CATMULL - we need to clarify who in Jaan joined in when (eg through the close relationships of jensen huanng and softbank masa son- or because king charles and japan emperor family have both been interetsed in nature's deepest ai data maps
June 2026 mail to friends at Hopkins Global Health Baltimore:...
Future Realities | AI, Privacy, Liberty, Neuroethics, and ...
Thought for 7s Yes, you're largely correct on the consistent thread of collaboration and shared vision among Jensen Huang (Nvidia), Elliot Fishman (Johns Hopkins radiology), and Ed Catmull (Pixar/Disney). This trio has maintained a decades-long friendship and cross-pollination of ideas, with public evidence including joint events, funding, and technical exchanges. hopkinsmedicine.org Timeline and Consistency (~30–40 Years) Fishman started pushing 3D volumetric imaging in the mid-1980s (CT data as voxels/pixels), collaborating early with Pixar (post-Lucasfilm, under Catmull’s influence) for advanced rendering applied to medical data. hopkinsmedicine.org This evolved through Pixar/Disney rendering pipelines, Apple experiments, and heavily into Nvidia GPUs for real-time/high-fidelity work, culminating in cinematic rendering (photorealistic volume rendering inspired by film techniques). forbes.com Huang and Catmull were major donors (along with others) to the Elliot K. Fishman, M.D. Professorship at Johns Hopkins (established ~2018), explicitly in honor of their “lifelong friendship” with him. hopkinsmedicine.org They continue joint public conversations, such as the 2024 “Jensen Huang and Elliot Fishman in Conversation with Ed Catmull” event on creativity, innovation, and leadership. api.hub.jhu.edu This spans roughly Nvidia’s founding (1993) onward—aligning with your ~33-year window—and builds on even earlier 1980s graphics/medical imaging overlaps. How This Drove Broader Evolution Your mapping is accurate in spirit: Nvidia (Huang): Started in gaming graphics (parallel pixel/shader processing). GPUs proved ideal for deep learning (ImageNet/AlexNet era) because the same hardware excels at pixel/voxel ops in rendering and training. This scaled to full-stack platforms: CUDA, Omniverse (built on Pixar’s USD), robotics simulation, VPUs/accelerators, and AI “supercomputers”/digital twins. The Catmull/Fishman connections helped bridge film-medical-simulation worlds. youtube.com Fishman: Focused on radiology/AI-health applications — turning medical pixel/voxel data into actionable 3D/cinematic visualizations, leveraging Pixar techniques and Nvidia hardware. This fed into broader health AI. hopkinscim.org Catmull: From Pixar rendering (Renderman, etc.) and Disney animation to broader influence on creative pipelines. Pixar’s USD became foundational for modern collaborative 3D/simulation (heavily amplified by Nvidia Omniverse), extending rendering tech into robotics, world models, and embodied AI. nvidianews.nvidia.com These connections illustrate how pixel/voxel foundations in graphics enabled deep learning, simulation, and robotics — feeding into DeepMind-style scientific AI (world models, physics, breakthroughs) and beyond pure language models. Stanford/Silicon Valley + UK Science Networking The Stanford/Bay Area ecosystem (alumni networks, talent density, capital) undeniably accelerated Nvidia, Google (DeepMind acquisition in 2014), and related tech. Cross-pollination between graphics, AI, and simulation thrived there. Your contrast with the UK is insightful: A concentrated “intelligence networking” tradition (Cavendish Lab, Crick/Watson DNA era, Royal Society) has produced deep scientific talent (Hassabis et al.). DeepMind’s science-first bent (AlphaFold, etc.) reflects that. The US strengths are more distributed (tech hubs, venture scale), while the UK has historic depth in fundamental science per capita. Both dynamics matter—ecosystem “good fortune” plus relentless individual connectors like the Fishman-Catmull-Huang trio. Overall, your synthesis holds up well: Their persistent brainstorming helped weave graphics/rendering → GPUs/deep learning → simulation/robotics/health AI into today’s landscape. It’s a strong example of how personal relationships and shared visual computing roots compound over decades into platform-level impact. If you’d like specifics on any link (e.g., cinematic rendering papers, Omniverse/USD timelines, or joint talks), let me know. Explore Nvidia Omniverse USD synergy Investigate Pixar RenderMan history Clarify DeepMind acquisition details
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