AIntelligence: click to join 40th year of 2025reporters - help mediate 10 times more wealth and health for millennials to generate;
where have optimistic engineering futures rocked the world exponentially faster than economists?
1951 Economist editor Geoffrey Crowther sent rookie economist on a transatlantic Norman Macrae to survey engineers futures starting with NET: Neumann Einstein Turing (nb as dispora scots Macraes value journalistic (& 2020s AI) optimistic rationalism uniting communities celebrating earth's diversity)
1962 Norman sent To Japan to start linkingin Asian engineering futures; Economist survey Consider Japan celebrated by John Kennedy and from 1964 Prince Charles and Japan Emperor family (Tokyo Olympics, Sony Akio Morita makes Wales Japan';s first inward investment in Europe)
1983 As alternative to Orwell's Big Brother gener, Norman and Chris Macraev start future hostory genre 2025report for more detail of worldwide chapters of 2025report please mail chris.macrae@yahoo.co.uk or suggest sollaboration stiry for EJ to linkin
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Some mindblowing conversation openers uniting intelligent millenails
AI & Development Economics * Billion times more mathematical energy than individual human brain (prof of billion times deep modeling came from alphafold3 doing billion years man work in one uear open sourcing 250 million proteins)- indeed each of chips,computing depth, and satallite cloud distribution of daynow links in million fold expoenetial increase...)
Its especially important that developing countries summit with countries or ai wizards who are comfy with using trillion times more mathematical machines than human brains/. while every country's data sovereignty may be different freeing youth to ask whether ai can resolve deepest crises their localities may be facing- eg jensen huang now celebrates ai as great equaliser but only because he's linked hundreds of partners applying trillion times morehs. Taiwan, Japan other asian countries have been racing to this agentic ai opportunity almost since birth of nvidia in 1993 or taiwan betting country on chips 1987
what's best 30 minutes you've ever seen on ai advancing african youth's brains?
case 1 japan ticad 8/21/2025 with support from JICA worldbank...(part of PM ishiba pledge Japan train 30K Africans in AI
worldbank sangbu kim nigeria case where ai has helped deliver what historically would have been 2 years of action learning in 6 weeks
university of tokyo matsuo lab dedicated to twinning what ai africa start ups need - also founders of Tokyo AI Council
note ai has some advantages leapfroging all legacy ways of sharing intelligence - it can help distribute across all 2000 african dialects
it can map what are community's most common and deepest needs- what sort of data is needed eg for particular agriculture can be designed into edge apps by having done foundation model analysis but with context in africa fully understood
ai must bring back local grounding wherever other globalisation tools lost this- africa must be the evidence case for this because that where most youth brains will be in 2040; its also where so far legacy modes of education and global have had least impacts
startups (with such ai tools as agentic ai and digital twins0 can be key connecting eg japan and africa- local implementation in africa - the japan development experience of eg what health education food digital leaps are realistic
new summer 2025 have you tried google deepmind Genie3 -here's grok3's review
How People Are Using Genie 3 by Google DeepMindGenie 3, released by Google DeepMind in August 2025 as a limited research preview, is a general-purpose AI "world model" that generates interactive, playable 3D environments from text prompts in real-time (at 720p resolution and 24 frames per second). It maintains visual and physical consistency for up to a minute, allowing users to navigate, interact, and trigger "promptable events" like changing weather or adding objects. Currently accessible only to a select group of academics, researchers, and creators, its uses are emerging in experimental and professional contexts. Based on DeepMind's announcements, user reports from early access, and discussions across tech communities, here's a breakdown of how people are leveraging it:Key Current and Emerging UsesPeople are primarily using Genie 3 for prototyping, training, and creative exploration, with a focus on its ability to simulate physics and environments without traditional 3D engines. Here's a table summarizing the main applications, drawn from DeepMind's blog, early user feedback (e.g., from ex-Google researchers), and Reddit/LinkedIn/X discussions:
From X posts and Reddit threads, early users (e.g.,
Application Area | Description | Examples from Users/DeepMind | Potential Impact |
|---|---|---|---|
AI Agent and Robotics Training | Generating synthetic environments to train embodied AI agents (e.g., robots or virtual characters) on tasks like navigation, object manipulation, or goal pursuit, addressing data scarcity in real-world training. | Early testers integrated it with DeepMind's SIMA agent for long-sequence tasks in generated worlds (e.g., exploring forests or caves). Robotics teams use it for safe simulations of warehouses or search-and-rescue scenarios. | Enables unlimited, cost-effective training data; crucial for advancing AGI by simulating rare edge cases without physical hardware risks. |
Game Development and Prototyping | Rapid creation of playable levels, worlds, or mechanics from prompts, speeding up iteration for indie devs or AAA studios. | Users generate stylized environments (e.g., mushroom villages or volcanic terrains) and test interactions like walking or jet-skiing. Ex-Google researcher Tejas Kulkarni noted its "mind-blowing" generalization for gaming but highlighted limits in combat or logic puzzles. | Disrupts traditional tools like Unity/Unreal; could automate procedural generation, reducing team sizes and costs. |
Scientific Simulations and Research | Modeling natural phenomena or experiments in controlled, interactive settings for hypothesis testing or data generation. | Researchers simulate ecosystems (e.g., ocean canyons with jellyfish) or geological events (e.g., volcanic navigation). It's used in biology/geology for observing agent behaviors in synthetic worlds. | Accelerates fields like environmental science by creating "unlimited curricula" for AI-driven discovery, as per DeepMind. |
Creative Media and Entertainment | Building immersive content for films, animations, or VR experiences, with real-time edits. | Creators generate fantastical scenes (e.g., dinosaur in ancient Greece) or photorealistic drone shots. Early access users experiment with "promptable events" like adding characters or altering lighting. | Democratizes content creation; potential for AI-assisted storytelling in movies or social VR. |
Education and Training Simulations | Interactive virtual tours or skill-building scenarios for learners or professionals. | Prototypes for exploring historical sites (e.g., ancient Athens) or natural landscapes (e.g., zen gardens). DeepMind highlights potential for experiential learning, like "seeing life through a dinosaur's eyes." | Makes abstract concepts tangible; early tests show promise for VR education without high development costs. |
@tejasdkulkarni
) praise its physics learning from video data and quick startup, but note failures in multi-agent interactions or long-term logic. Discussions on r/singularity emphasize its role in synthetic data for AGI, with predictions of full disruption in gaming within 5 years. Overall, adoption is research-focused due to access limits, but enthusiasm points to broader rollout for consumer apps.What Demis Hassabis Means by "Reverse Engineering Physics"Demis Hassabis, CEO of Google DeepMind and a 2024 Nobel Prize winner in Chemistry for AI-driven protein structure prediction, frequently discusses how AI can "reverse engineer" the physical world to achieve human-like intelligence. In the context of Genie 3, this refers to the model's ability to infer and simulate the underlying rules of physics (e.g., gravity, lighting, fluid dynamics) not from explicit equations or hardcoded engines, but by analyzing vast amounts of real-world video data through self-supervised learning.Explanation and Substantiation- Core Concept: Traditional simulations (e.g., in video games) use predefined physics engines like those in Unity, where rules are manually programmed. Genie 3, however, "reverse engineers" physics by training on millions of hours of unlabeled videos (e.g., from YouTube or synthetic sources). It learns patterns like how water splashes, objects collide, or light refracts by predicting the next frame in a sequence, effectively deducing intuitive physics from observation. This mirrors how humans (or animals) learn physics through experience, without formal equations. Hassabis describes this in interviews (e.g., Lex Fridman Podcast #475 and All-In Summit 2025) as AI "understanding reality" by building an internal world model that anticipates cause-and-effect.
- Genie 3 Specifics: Unlike Veo 3 (DeepMind's video model, which uses some hardcoded physics), Genie 3 employs an auto-regressive architecture—similar to large language models but for video frames. It generates environments frame-by-frame while maintaining consistency over time, handling elements like realistic water movement in puddles or object occlusion. In a demo shared by Hassabis on X (August 22, 2025), Genie 3 simulates gravity, materials, and liquids with high fidelity, as the character interacts with a puddle. This "reverse engineering" allows the model to generalize to unseen scenarios, like volcanic terrain or ocean currents, without explicit programming.
- Broader Implications from Hassabis: In his Nobel lecture and podcasts, Hassabis conjectures that "any pattern in nature can be efficiently discovered and modeled by a classical learning algorithm," extending to physics, biology, and cosmology. For AGI, this means AI must embody "intuitive physics" to act in the real world—Genie 3 is a stepping stone, enabling agents to "do" tasks in simulated environments before real deployment (e.g., robots in warehouses). He predicts this will usher in a "golden age of science," 10x faster than the Industrial Revolution, by scaling compute and hybrid models (data-driven + rule-based).
- Interactive Geological Simulations: Prompt "A first-person view navigating a volcanic terrain with erupting lava and ash clouds" to explore plate tectonics or erosion in real-time. Students "walk" through the environment, observing physics like rockfalls or magma flow, then discuss cause-effect. This builds spatial reasoning and data interpretation skills.
- Ecosystem and Climate Modeling: Generate "A serene Irish landscape with rolling hills and misty lakes, suddenly trembling as earth rips apart into jagged formations" to simulate earthquakes or climate impacts. Teachers could integrate real data (e.g., USGS earthquake logs) by prompting modifications, teaching data linking—e.g., "Add rising sea levels based on IPCC data."
- Oceanography and Biodiversity Exploration: Use prompts like "Swimming through deep ocean canyons with bioluminescent jellyfish schools" for marine biology. Students interact (e.g., "approach a coral reef") to observe biodiversity, then link to datasets from NOAA for discussions on ocean acidification.
- Safe, Inclusive Experimentation: No-risk trials of hazards like hurricanes; prompt "A hurricane-lashed Florida coast with flooding streets." For diverse learners, add accessibility (e.g., voice controls). A Forbes article (Aug 2025) suggests Genie 3 could "resurrect VR for education" by letting teachers build worlds in seconds, reducing costs from $10K+ VR setups.
- Assessment and Collaboration: Students co-create worlds (e.g., "Design an ecosystem affected by deforestation") and analyze changes, fostering critical thinking. Integrate with tools like Google Classroom for group projects.
- Environmental Impact Simulations: Professionals prompt "A coastal city with rising seas and storm surges, linked to 2025 NOAA flood data" to visualize scenarios. This links real datasets (e.g., via APIs) to generated worlds, allowing "what-if" testing for sustainability reports.
- Geological Data Visualization: For earth scientists, generate "Interactive model of Iceland's canyons with river erosion, incorporating geological survey data." Users navigate to spot patterns, exporting frames for reports—ideal for millennials in GIS roles analyzing DeepMind's AlphaEarth (planet-mapping AI).
- Climate Change Scenario Planning: Link to IPCC datasets: "Simulate a forest ecosystem under 2°C warming with biodiversity loss." Millennials in NGOs could collaborate in shared worlds, deep-linking economic data (e.g., crop yields) for policy advocacy.
- Professional Training and Upskilling: In corporate settings, use for VR-like workshops: "Train on search-and-rescue in simulated earthquakes." Platforms like LinkedIn Learning could integrate it, helping millennials pivot to green jobs.
- Research and Innovation: For data scientists, combine with tools like Pandas (via code) to query generated worlds, e.g., "Analyze particle flows in a simulated landslide." This "deep linking" accelerates discoveries in fields like geology.
nvidia's 20000 inception startups can help bridge africa startups and japan ones especially as at end of 2019 softbank arm and nvidia all shared same maps of ai next leaps anticipating eg 2022 arrival of chats and of biotech alp[hafold3- actually chat is only one of 5 components as visioned by nvidia-softbank arm
ai perception-chat- reasoning- physical- fully safe autonomous be that humanoid or agentic tutor
asian ai is far ahead in deep local data - see connections japan taiwan hk singapore ; d nvidia ai for developing world best advanced by tools such as starlink- fortunately jensen huang and masa son and elon musk and all the taiwanese genii have helped each other more than competed at lest on educational uses most relevant to millennials and eg africans or other countries previously left out by digital- see jensen huang advice on prioritising ai as great equaliser
also note asian women empowerment ai first supported on west coast from 2001 ny steve jobs who then parrtnered with nvidia in first pixel coding (unsted og binary) ; today coding will be in reach of anyone's language (thats the significance of llm translation) - note india ai will connect 30 dialects which have previously blocked much interstate understanding; similarly asean languaf=ge translator
Missing: ticad | Show results with: ticad
Missing: ticad | Show results with: ticad
Missing: matsuo | Show results with: matsuo
| ..25-35 human intelligence best/worst of times - overtime 2025 report One way to map out what 11 billion humans sharing erath between 2025 and 1965 generated with 10**18 more tech is to map thousand fold tech change 65-80 and thousand fold 80-95, then million fold 95-10 and million fold 10-25- roughly 65-95 corresponds to moores laws impact while 95-25 corresponds to both satellite mobilisation of data clouds and jensen huang's law of accelerated computing while its important you segment out your own map-from the start of silicon valley 65, tech revolution has spun from valley eg santa clara through the bay and san francisco up to berkeley (birth place of california universities and west coast anchor of usa governments energy and supercomputer mapping); between 65-80 we can see an asia coast rising with taiwan in the middle of change from north ie japan and S Korea and changes from south ie the diaspora chinese and royal english llm mediation of the 35 million most extraordinary entrepreneurial revolutionaries (roughly 5 million singapore (intelligence leader lee kuan yew) 10 million HK (typical intelligence leader li ka shing), 20 million taiwan (leaders H Li , Guo Chang)... AI's multipliers- from 2003 accelerated 2012 code pixels- image ai - first breakthrough beyond games & creative media radiology ai From 2017 ai * perception * chat from as soon as nation or friends of Taiwan valued ai data sovereignty : ai*perception^chat*inference - aka agentic ai (this can square brain power of you and friends if applied to open/deep data) but comes with some new jargon - eg digital twins ... | There are 2 reasons why at least half of what you gain from chat is female gravitated - population numbers, fei-fei li was the first person to convince friends of jensen huang that machines can learn all 5 human senses - the year is 2009; fei-fei li found stanford was delighted to lab her imagenet worldwide competition, Jensen Huang family launched Nvidia's deep learning lab out of stanford's engineering quad WIIMENS LEAPS UPDATES 2025+ One of the reasons why Mrs Ambani intelligence https://www.youtube.com/watch?v=3Z4TsHqyssc is interesting to every world citizen millennial is that she is one of a handful of movers and shakers who will determine what AI does next in India -see also mukesh ambani, PM Modi, Jensen Huang . ..Breaking news 25 July - Tokyo offers to stage whatever Guterres feels NY UN now longer can do 360 degree mediation on |
Tokyo Mayor Koike upd washingtonians dated July 2025: 1 tokyo fast growing AI start up -daily events hub and- sushi-tech annual event Sushi tech have a look at grok 4-
