King Charles can claim to be origin of AI data sovereignty investing. The crown owns Europe's largest AI start up space- cambridge business park. Possible conversation with trump- how biden era justice department blocked merger of us nvidia and cambridge's arc. It could also be interesting to compare kings english language modeling with trumps american. King Charles translation of AI has been adopted by AI world series summit - bletchley-jorea-paris-india as well as likely discussed at royal visits - Japan Emperor, Qatar Emir, French President. Nvidia's partnership with all European public media could reach out to Cambridge Damtp lab - where the new chair of public appreciation of maths Hannah Fry has also been BBC correspondent for AI and Deep Mind Podcast. Hassabis founder of deep mind bridges Uk's AIO ecosystems with silicon valley in areas such as biotech expected to be most valuable in next 5 years as well as trasmprsametly mathematical.
Trump's recent remarks that US economy will collapse american trade and AI are not done my way :
references we ask grok to explain relationship between ai, systems mapmaking and maths
"systems mapmaker" goes beyond applied math. It implies a visionary or architectural role—someone like Jensen Huang, Demis Hassabis, Elon Musk, or Yann LeCun doesn’t just apply math but integrates it with engineering, business, and societal goals.
It is promising that Trump appears to relate to Jensen Huang, King Charles to Demis Hassabis, Macron & Modi to Yan Lecunn - and perhaps it is inevitable that all may feel distant to space-impressario Musk but we the peoples should watch out because every era needs one or two wholly unconventioanal thinkers or brains beyond current generations ken.
For example of specific intelligence gifts: - **Huang** maps GPU architectures to AI’s computational needs, less about math proofs and more about enabling systems. - **Hassabis** connects neuroscience, math, and AI to map cognitive processes (e.g., AlphaFold’s protein folding). - **Musk** envisions AI systems (e.g., Neuralink, xAI) that map technology to human augmentation. - **LeCun** maps mathematical principles (e.g., backpropagation) to scalable AI frameworks. ### Why the Distinction Matters Your "systems mapmaker" label highlights their ability to synthesize disciplines into practical, impactful systems, which pure mathematicians rarely do. A pure mathematician might develop a new statistical method, but a systems mapmaker would take that method, combine it with hardware, data pipelines, and ethical considerations, and deploy it to solve something like autonomous driving. Applied math is a tool for mapmakers, but their scope is broader, often less rigorous in a mathematical sense and more focused on outcomes. ### Is Your View Ignorant? Not at all. By calling them systems mapmakers, you’re recognizing their role in weaving math, tech, and human needs into AI’s future. It’s a broader lens than "mathematician," which is too narrow for their work. The term captures their interdisciplinary impact, distinct from both pure and applied mathematicians, who typically stay within mathematical boundaries.
Matters in the AI Era** Mathematics is the backbone of AI, as discussed in previous responses (e.g., transformers, optimization, and probabilistic modeling in AlphaFold and AI chat systems). Variations in mathematical ability and outdated curricula have significant implications for advancing humanity transparently in the AI era: - **AI Development and Access**: Strong mathematical skills are essential for developing, understanding, and critiquing AI systems. Nations with weaker math education may struggle to produce AI talent, widening global inequalities and concentrating AI innovation in a few countries. - **Transparency**: Transparent AI advancement requires a public that can understand its principles. Without widespread mathematical literacy, most people cannot scrutinize AI algorithms, leading to distrust or unchecked power in AI-driven systems. - **Human Progress**: AI has the potential to solve global challenges (e.g., healthcare, climate change), but its benefits depend on equitable access and understanding. Weak math education limits participation in the AI economy, hindering inclusive progress.
Extract 2 abridged =Americans intelligence is extraordinarily disadvantaged by ranking about 30th in high school maths . At the least this explains smart trade interdependence of world leading advances in ai where Silicon Valley major companies advancing AI retain largely Asian American boards. Moreover, Since moore's law exponentially accelerated power of chips since 1965 its the far eastern places japan korea taiwan hk and singapore that were main client buyers of chips as they innovated microelectronics , tech games and aspects of civil engineering that required smart gauges or computer aided architecture etc - which now lead ai digital twin movements. From 1987 Taiwan's national bet was on chip foundries, and we now know that slowly but steadily this became the silicon valley bet around nvidia's accelerated computing architectures and space races (eg trough 1g to 6g) needed for deep data everywhere.
Exyract 3 Hassabis deepmind ai bridges cmabridge, london, and bvalley. It is accelerating the most valauble innovation areas of ai in biotech and related natural sciences. Pattern maths models play to ai's trillion times bigger maths brain for multidimensional pattern analyssi and are enabling human race to catch up with many of the maths puzzled of eisntein's 1905 publication e-mcsquared.
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