Since a #TimeSlider like in #GoogleStreetView w #GPegman becoming #AvatarAgentElectronicMedicalRecords would be incredibly helpful for #PhysicalDigital #RealisticVirtualEarthForGenetics #forAgingReversal & #forExtremeLongevity, #WUaSvirtualEarth @WorldUnivAndSch ...
Again, slightly different -
Since a #TimeSlider in #GStreetView w #GPegman becoming #AvatarAgentElectronicMedicalRecords would be #SUPER for #PhysicalDigital #RealisticVirtualEarthForGenetics #forAgingReversal & #forExtremeLongevity, & #WUaSvirtualEarth ,
to dev this scott-macleod.blogspot.com/2025/08/americ ~
initial limitations to developing Google Street View with time slider and with pegman a our avatar agent electronic health records - for aging reversal and longevity? -
*
Since a #TimeSlider in #GStreetView w #GPegman becoming #
https://x.com/WUaSPress/
Since a #TimeSlider in #GStreetView w #GPegman becoming #AvatarAgentElectronicMedicalRecords would be #SUPER for #PhysicalDigital #RealisticVirtualEarthForGenetics #forAgingReversal & #forExtremeLongevity, & #WUaSvirtualEarth @WorldUnivAndSch to dev this https://t.co/QP1qvixR9M ~ https://t.co/Hk643HivBG
— WUaSPress (@WUaSPress) August 9, 2025
https://x.com/WUaSPress/
Retweeting -
American Kestrel
Anahuac National Wildlife Refuge in Texas, USA.02/18/2023 #americankestrel #kestrel #falcon #birdphotography #naturephotography
No retweet -
Since a #TimeSlider in #GStreetView w #GPegman becoming #AvatarAgentElectronicMedicalRecords would be #SUPER for #PhysicalDigital #RealisticVirtualEarthForGenetics #forAgingReversal & #forExtremeLongevity, & #WUaSvirtualEarth @WorldUnivAndSch to dev this https://t.co/1jdIFjvPvP ~
— WorldUnivandSch (@WorldUnivAndSch) August 8, 2025
*
What are the initial limitations to developing Google Street View with time slider and Google Maps and at the cell view level and molecular view levels too in terms of genetics and for aging reversal genetic drug therapies and with Alpha Fold 3 server and with extreme longevity genetics with regard to the time slider to ?
Initial limitations include the rarity of extreme longevity phenotypes, the need for large and diverse sample sizes to find significant genetic associations, and the inherent complexity of integrating diverse and high-dimensional biological data with existing mapping technologies. Representing genetic pathways and drug therapies visually on a map-like interface, at both a "cell view" and "molecular" level, poses significant data modeling and visualization challenges. Furthermore, technical hurdles exist in processing and storing this massive, multi-scale data on servers
*
What are the initial limitations to developing Google Street View with time slider and Google Maps and at the Street view phenotype level, cell view, and molecular view level too in terms of genetics and for aging reversal
and with extreme longevity genetic drug therapies and especially through connecting our avatar agent electronic health records with Pegman and potentially via this sensor
eRapid: Multiplexed Electrochemical Sensors for Fast, Accurate, Portable Diagnostics
A fouling-resistant, affinity-based platform enables cheap, simultaneous sensing of multiple biomarkers
between our bodies and our electronic health records and with AlphaFold 3 server especially with inter-operating these with a G street view time slider at both the cell and molecule view levels and for example here in
"How to view Google Street View in a smart meeting room"
Several key limitations currently impede the development of a Google Street View-like system at the cellular and molecular level, particularly in the context of genetics, aging reversal, and targeted drug therapies, even with advancements like AlphaFold 3 and eRapid sensors:
Data Acquisition and Resolution
- Current Street View limitations: Google Street View captures images at a macroscopic, outdoor level. Its capabilities are vastly insufficient to capture cellular and molecular structures and dynamics.
- Imaging limitations: Capturing the intricate details of a cell or the dynamic interactions of molecules requires highly specialized imaging techniques, like high-resolution microscopy and molecular dynamics simulations, which are a far cry from the data collected for Street View.
- Real-time data at the molecular level: Real-time information on the molecular state of a living system is extremely difficult and expensive to collect, and displaying such information in a comprehensive "molecular Street View" is beyond current technological capabilities.
Data Storage and Processing
- Massive Data Volume: Capturing and storing data at the cellular and molecular levels for entire organisms, let alone tracking changes over time for aging reversal studies, would create astronomical data volumes, requiring novel storage and processing solutions.
- Interoperability Challenges: Integrating diverse data types (genomic, proteomic, metabolomic, etc.) collected at different resolutions and from various sources (EHRs, sensor data like eRapid) into a cohesive "molecular Street View" environment poses significant technical challenges.
Modeling and Visualization
- AlphaFold 3 and Beyond: While Google DeepMind's AlphaFold 3 has made significant advancements in predicting protein structures and their interactions, AlphaFold 3 focuses on individual molecules and their interactions and lacks the ability to visualize or simulate the complex interplay of countless molecules and cells within a living organism at a "Street View" scale.
- Predicting aging reversal mechanisms: Accurately predicting the effects of genetic modifications and drug therapies on complex aging processes and cellular interactions across an entire organism remains a grand challenge in biology.
- Visualization of dynamic processes: Effectively visualizing dynamic processes and changes in real-time, such as cellular metabolism, gene expression, and disease progression, in a readily understandable "molecular Street View" is still a distant goal.
Ethical and Privacy Concerns
- Privacy of genetic and health data: Integrating personal genetic information and electronic health records (EHRs) into such a system raises considerable ethical and privacy concerns that require robust security measures and stringent regulations.
- Avatar-EHR connection: Connecting a digital avatar representation of an individual with their detailed health information for targeted therapies or personalized aging interventions raises complex issues around data ownership, consent, and potential misuse.
Scientific and Technical Hurdles
- Fundamental understanding of aging: Despite progress in aging research, our fundamental understanding of the complex genetic and environmental factors contributing to aging and age-related diseases is still evolving.
- Targeting specific cells and molecules: Delivering genetic therapies and drug treatments to specific cells and molecules within the human body with precision and safety is an ongoing area of research and development.
In conclusion
While the concept of a Google Street View-like system at the cellular and molecular level for aging reversal and drug development is a fascinating vision, it faces numerous scientific, technological, and ethical limitations that will require significant breakthroughs across various fields to overcome
*
Several limitations pose challenges to the integration of Google Street View with a time slider for visualizing phenomena at the phenotype, cell, and molecular levels in the context of genetics, aging reversal, and extreme longevity therapies, along with the integration of AlphaFold 3 capabilities:
1. Technical Limitations
- Data availability and resolution at cellular and molecular levels: Google Street View primarily captures macro-level imagery. Zooming in to the level of individual cells and molecules necessitates vast amounts of high-resolution, multi-dimensional biological data (like from the Human Cell Atlas). Current techniques for visualizing cell and molecular structures struggle with real-time processing and integration of large, complex datasets, especially from dense populations or across different experiments.
- Time-series data for cellular and molecular dynamics: Developing a "time slider" at the cell and molecular levels demands capturing and storing dynamic changes over time, potentially over significant periods in the context of aging reversal and longevity therapies. This involves advancements in live-cell imaging, multi-omics data acquisition (genomics, proteomics, etc.), and efficient data storage and retrieval systems to handle the sheer volume and complexity of this information.
- Integration and visualization of diverse data types: Seamlessly overlaying genetic data (e.g., genetic risk scores for traits relevant to aging), molecular structures from tools like AlphaFold 3 (which can predict protein structures and interactions), cellular imagery, and Street View imagery requires a robust data integration and visualization infrastructure. This involves reconciling different data formats, scales, and temporal resolutions, and developing algorithms for mapping biological data onto geographical locations or representations.
- Computational resources and accessibility: The integration of technologies like AlphaFold 3, while powerful, demands significant computational resources (like specialized GPUs). Ensuring widespread accessibility and user-friendliness of such an integrated platform, particularly for researchers who may not be experts in high-performance computing, presents a significant challenge.
2. Scientific Limitations
- Causal links between genetics, environment, and aging: While studies suggest correlations between environment and health, establishing definitive causal links between specific genetic variations, environmental factors observed in Street View, and aging reversal or longevity requires extensive and rigorous research.
- Completeness of biological models: AlphaFold 3 can predict biomolecular structures with high accuracy, notes KevinMD.com and according to the National Institutes of Health (NIH). However, it is important to remember that these are predictions and may not perfectly reflect the dynamic and complex interactions within a living organism. Furthermore, accurately modeling how drug therapies impact these interactions over time for aging reversal and longevity remains a considerable scientific hurdle.
3. Ethical and societal considerations
- Privacy and data security: The integration of genetic and personal health data with geographical locations raises significant privacy concerns. Ensuring the anonymity and security of such sensitive information, especially given the ease of re-identification with genomic data, is paramount. Navigating regulations and establishing robust safeguards would be critical for building trust and enabling participation.
- Equity and accessibility: Unequal access to these advanced technologies and therapies could exacerbate existing health disparities. Fair and equitable access to information and potentially expensive longevity treatments needs to be addressed through careful planning and policy development.
- Societal impacts and unintended consequences: The prospect of widespread aging reversal and extreme longevity raises profound questions about social structures, resource allocation, and the concept of human nature. Careful consideration of the potential societal and environmental impacts is essential, as highlighted in Table III of.
In essence, while the integration of Google Street View, time sliders, and advanced AI models like AlphaFold 3 holds immense promise for understanding and addressing aging, it requires overcoming substantial technical, scientific, and ethical hurdles. These include managing and visualizing massive datasets, developing accurate predictive models of biological processes, and establishing strong safeguards for privacy, equity, and responsible deployment.
*
What are the initial limitations to developing Google Street View with time slider and Google Maps and at the cell view level and molecular view level too, in terms of genetics and for aging reversal genetic drug therapies and with Alpha 4 server and with extreme longevity genetics with regard to the time slider to ?
Gemini AI -
Initial limitations include the rarity of extreme longevity phenotypes, the need for large and diverse sample sizes to find significant genetic associations, and the inherent complexity of integrating diverse and high-dimensional biological data with existing mapping technologies. Representing genetic pathways and drug therapies visually on a map-like interface, at both a "cell view" and "molecular" level, poses significant data modeling and visualization challenges. Furthermore, technical hurdles exist in processing and storing this massive, multi-scale data on servers
*
Again, elaborated -
What are the initial limitations to developing Google Street View with time slider and Google Maps and at the Street view phenotype level, cell view, and molecular view level too in terms of genetics and for aging reversal
and with extreme longevity genetic drug therapies and especially through connecting our avatar agent electronic health records with Pegman and potentially via this sensor
eRapid: Multiplexed Electrochemical Sensors for Fast, Accurate, Portable Diagnostics
A fouling-resistant, affinity-based platform enables cheap, simultaneous sensing of multiple biomarkers
between our bodies and our electronic health records and with AlphaFold 3 server especially with inter-operating these with a G street view time slider at both the cell and molecule view levels and for example here in
"How to view Google Street View in a smart meeting room"
AI overview -
Several key limitations currently impede the development of a Google Street View-like system at the cellular and molecular level, particularly in the context of genetics, aging reversal, and targeted drug therapies, even with advancements like AlphaFold 3 and eRapid sensors:
Data Acquisition and Resolution
- Current Street View limitations: Google Street View captures images at a macroscopic, outdoor level. Its capabilities are vastly insufficient to capture cellular and molecular structures and dynamics.
- Imaging limitations: Capturing the intricate details of a cell or the dynamic interactions of molecules requires highly specialized imaging techniques, like high-resolution microscopy and molecular dynamics simulations, which are a far cry from the data collected for Street View.
- Real-time data at the molecular level: Real-time information on the molecular state of a living system is extremely difficult and expensive to collect, and displaying such information in a comprehensive "molecular Street View" is beyond current technological capabilities.
Data Storage and Processing
- Massive Data Volume: Capturing and storing data at the cellular and molecular levels for entire organisms, let alone tracking changes over time for aging reversal studies, would create astronomical data volumes, requiring novel storage and processing solutions.
- Interoperability Challenges: Integrating diverse data types (genomic, proteomic, metabolomic, etc.) collected at different resolutions and from various sources (EHRs, sensor data like eRapid) into a cohesive "molecular Street View" environment poses significant technical challenges.
Modeling and Visualization
- AlphaFold 3 and Beyond: While Google DeepMind's AlphaFold 3 has made significant advancements in predicting protein structures and their interactions, AlphaFold 3 focuses on individual molecules and their interactions and lacks the ability to visualize or simulate the complex interplay of countless molecules and cells within a living organism at a "Street View" scale.
- Predicting aging reversal mechanisms: Accurately predicting the effects of genetic modifications and drug therapies on complex aging processes and cellular interactions across an entire organism remains a grand challenge in biology.
- Visualization of dynamic processes: Effectively visualizing dynamic processes and changes in real-time, such as cellular metabolism, gene expression, and disease progression, in a readily understandable "molecular Street View" is still a distant goal.
Ethical and Privacy Concerns
- Privacy of genetic and health data: Integrating personal genetic information and electronic health records (EHRs) into such a system raises considerable ethical and privacy concerns that require robust security measures and stringent regulations.
- Avatar-EHR connection: Connecting a digital avatar representation of an individual with their detailed health information for targeted therapies or personalized aging interventions raises complex issues around data ownership, consent, and potential misuse.
Scientific and Technical Hurdles
- Fundamental understanding of aging: Despite progress in aging research, our fundamental understanding of the complex genetic and environmental factors contributing to aging and age-related diseases is still evolving.
- Targeting specific cells and molecules: Delivering genetic therapies and drug treatments to specific cells and molecules within the human body with precision and safety is an ongoing area of research and development.
In conclusion
While the concept of a Google Street View-like system at the cellular and molecular level for aging reversal and drug development is a fascinating vision, it faces numerous scientific, technological, and ethical limitations that will require significant breakthroughs across various fields to overcome
*
Several limitations pose challenges to the integration of Google Street View with a time slider for visualizing phenomena at the phenotype, cell, and molecular levels in the context of genetics, aging reversal, and extreme longevity therapies, along with the integration of AlphaFold 3 capabilities:
1. Technical Limitations
- Data availability and resolution at cellular and molecular levels: Google Street View primarily captures macro-level imagery. Zooming in to the level of individual cells and molecules necessitates vast amounts of high-resolution, multi-dimensional biological data (like from the Human Cell Atlas). Current techniques for visualizing cell and molecular structures struggle with real-time processing and integration of large, complex datasets, especially from dense populations or across different experiments.
- Time-series data for cellular and molecular dynamics: Developing a "time slider" at the cell and molecular levels demands capturing and storing dynamic changes over time, potentially over significant periods in the context of aging reversal and longevity therapies. This involves advancements in live-cell imaging, multi-omics data acquisition (genomics, proteomics, etc.), and efficient data storage and retrieval systems to handle the sheer volume and complexity of this information.
- Integration and visualization of diverse data types: Seamlessly overlaying genetic data (e.g., genetic risk scores for traits relevant to aging), molecular structures from tools like AlphaFold 3 (which can predict protein structures and interactions), cellular imagery, and Street View imagery requires a robust data integration and visualization infrastructure. This involves reconciling different data formats, scales, and temporal resolutions, and developing algorithms for mapping biological data onto geographical locations or representations.
- Computational resources and accessibility: The integration of technologies like AlphaFold 3, while powerful, demands significant computational resources (like specialized GPUs). Ensuring widespread accessibility and user-friendliness of such an integrated platform, particularly for researchers who may not be experts in high-performance computing, presents a significant challenge.
2. Scientific Limitations
- Causal links between genetics, environment, and aging: While studies suggest correlations between environment and health, establishing definitive causal links between specific genetic variations, environmental factors observed in Street View, and aging reversal or longevity requires extensive and rigorous research.
- Completeness of biological models: AlphaFold 3 can predict biomolecular structures with high accuracy, notes KevinMD.com and according to the National Institutes of Health (NIH). However, it is important to remember that these are predictions and may not perfectly reflect the dynamic and complex interactions within a living organism. Furthermore, accurately modeling how drug therapies impact these interactions over time for aging reversal and longevity remains a considerable scientific hurdle.
3. Ethical and societal considerations
- Privacy and data security: The integration of genetic and personal health data with geographical locations raises significant privacy concerns. Ensuring the anonymity and security of such sensitive information, especially given the ease of re-identification with genomic data, is paramount. Navigating regulations and establishing robust safeguards would be critical for building trust and enabling participation.
- Equity and accessibility: Unequal access to these advanced technologies and therapies could exacerbate existing health disparities. Fair and equitable access to information and potentially expensive longevity treatments needs to be addressed through careful planning and policy development.
- Societal impacts and unintended consequences: The prospect of widespread aging reversal and extreme longevity raises profound questions about social structures, resource allocation, and the concept of human nature. Careful consideration of the potential societal and environmental impacts is essential, as highlighted in Table III of.
In essence, while the integration of Google Street View, time sliders, and advanced AI models like AlphaFold 3 holds immense promise for understanding and addressing aging, it requires overcoming substantial technical, scientific, and ethical hurdles. These include managing and visualizing massive datasets, developing accurate predictive models of biological processes, and establishing strong safeguards for privacy, equity, and responsible deployment.
--
Society, Information Technology, and the Global University (2025, forthcoming)
Scottish Small Piping album #2 - Honey Piobaireachd (2022)
- https://twitter.com/
Scottish Small Piping album #1 Honey in the Bag ~ Out of the Air tune (2020)
Order Book #4 To the Dance or the Pools? ~ Virtually! How different it is to soak at Harbin Hot Springs, than to realize it in virtual reality (2019)
Order Book #3 Winding Road Rainbow: Harbin, Wandering & the Poetry of Loving Bliss (2018)
Order Book #2 Haiku-ish and Other Loving Hippie Harbin Poetry (2017)
Order Actual-Virtual Ethnographic Book #1: Naked Harbin Ethnography (2016)
- Scott GK MacLeod
Founder, President, CEO & Professor
CC-4 licensed MIT OCW-centric, Wiki,
World University & School (WUaS)
- USPS US Post Office, General Delivery, Canyon, CA 94516
1) non-profit 501(c)(3) Public Charity
MIT OCW-centric,
World University and School - http://
2) for profit general stock company WUaS Corporation in CA - http://
(o) 415 480 4577 - sgkmacleod@
(m) 412 478 0116 - sgkmacleod@gmail.com
World Univ & Sch Innovation Research -
*
https://en.wikipedia.org/wiki/American_kestrel
https://commons.wikimedia.org/wiki/Category:Falco_sparverius
https://species.wikimedia.org/wiki/Falco_sparverius
...
Posts
No comments:
Post a Comment