How soon until we get to a Star Trek reality?

[Professor Emeritus]

We will be dust in 200 years. We have no idea what they will be capable of by then.

Just repeating yourself dogmatically over and over again is not an informed argument.

I hold the same position on this now that I've held since I was getting my degree in the field in the 1990s.....and I've had an additional 25 years to confirm what I had already known from the evidence of the previous 30 years. You can hope for any scifi you want, but the reasonable view is that the boundaries of possibilty as developed by physicists over the last 120 years have become reasonably well-defined.

 

[Wargames]

Just repeating yourself dogmatically over and over again is not an informed argument.

I hold the same position on this now that I've held since I was getting my degree in the field in the 1990s.....and I've had an additional 25 years to confirm what I had already known from the evidence of the previous 30 years. You can hope for any scifi you want, but the reasonable view is that the boundaries of possibilty as developed by physicists over the last 120 years have become reasonably well-defined.

I don’t want to say this in a way that disregards your knowledge and experience but I know intellectual hubris when I hear it.

 

[Professor Emeritus]

I don’t want to say this in a way that disregards your knowledge and experience but I know intellectual hubris when I hear it.

Because you have some sort of objective evidence that it is hubris, or a meaningful track record of correctly identifying hubris? Or just because you have strong feelings and want the opposite of what I'm saying to be true?

 

[Wargames]

Because you have some sort of objective evidence that it is hubris, or a meaningful track record of correctly identifying hubris? Or just because you have strong feelings and want the opposite of what I'm saying to be true?

You’re the one who dropped your resume to prove a point that you cannot prove, in a Star Trek thread.

You cannot predict the future and are speculating same as me, and it’s weird how triggered you are by the mere fact that I can admit there are known unknown and unknown unknown we all exist under.

No one is doubting your science or understanding of science, but no matter how much you know, you cannot predict what science will achieve in 200 years into the future. It’s not hope, it’s wisdom.

You can respond with veiled insults all you like, at the end of the day you are speculating same as me.

 

[Secure Da Bag]

Not a holodeck. But cool, nonetheless

 

[Secure Da Bag]

Remember those crystals in SG-1? Scientists reminds us they are real now (have been for a few years actually).

 

[Secure Da Bag]

Sisko might get to Cardassia after all

MSN

www.msn.com

NASA's new $20M spaceship is hurtling through space uncontrollably
A new NASA spaceship is tumbling through space uncontrollably as engineers on the ground work to fix an issue that caused the $20 million craft to lose control. The agency's Advanced Composite Solar Sail System (ACS3), a craft with four reflective 'sails' designed to test a new type of propulsion system, hit a snag when it unfurled the sails. Engineers noticed a slight bend in one of the 'booms,' or structural beams, that support the sails, impacting its ability to stay on course.

 

[Secure Da Bag]

Warp drives one step closer to reality

MSN

 

[bnew]

NASA engineer developed a propellant-less rocket that defies conventional laws of physics

Dr. Charles Buhler envisions this newfound force propelling objects into space for the next millennium, heralding a new era in exploration

www.thebrighterside.news

NASA engineer developed a propellant-less rocket that defies conventional laws of physics​

Dr. Charles Buhler envisions this newfound force propelling objects into space for the next millennium, heralding a new era in exploration​

Joseph Shavit​

Published Nov 6, 2024 9:07 AM PST

Their propellantless propulsion drive has demonstrated the capability to counteract Earth’s gravity, defying conventional laws of physics. (CREDIT: CC BY-SA 4.0)

In a recent revelation, Dr. Charles Buhler, a seasoned NASA engineer and co-founder of Exodus Propulsion Technologies, unveiled a groundbreaking achievement: their propellantless propulsion drive has demonstrated the capability to counteract Earth's gravity, defying conventional laws of physics.

With a wealth of experience from NASA's most iconic missions under his belt, including the Space Shuttle and the International Space Station (ISS), Dr. Buhler and his team perceive this discovery as a monumental breakthrough set to redefine the landscape of space travel for centuries to come.

Dr. Buhler emphasized the significance of their finding, stating, "The most important message to convey to the public is that a major discovery occurred."

Dr. Charles Buhler, a seasoned NASA engineer and co-founder of Exodus Propulsion Technologies. (CREDIT: Exodus Propulsion Technologies)

Their innovation, harnessing electric fields to generate sustainable thrust without expelling mass, represents a paradigm shift in propulsion physics. Buhler envisions this newfound force propelling objects into space for the next millennium, heralding a new era in exploration.

Unveiling their discovery at the Alternative Propulsion Energy Conference (APEC), Dr. Buhler shared insights into their journey. Despite initial skepticism, their pursuit led them to electrostatics, a field in which Dr. Buhler is an eminent authority.

Collaborating with a diverse team from prestigious institutions and industries, their collective expertise culminated in a breakthrough that defied conventional expectations.

Over a span of decades, the team meticulously conducted experiments, culminating in their propellantless propulsion drive.

Through iterative refinement and rigorous testing, they achieved thrust measurements exceeding previous limits. Notably, their latest iteration exhibited a remarkable feat: generating thrust equivalent to one Earth gravity, a milestone in their quest.

Detailing their methodology, Dr. Buhler explained the significance of their tests conducted in a custom-made vacuum chamber simulating deep space conditions. These experiments validated their propulsion drive's efficacy, eliminating alternative explanations and solidifying their patent.

Their innovation, harnessing electric fields to generate sustainable thrust without expelling mass, represents a paradigm shift in propulsion physics. (CREDIT: Exodus Propulsion Technologies)

Despite their pioneering success, Dr. Buhler acknowledged the existence of competing concepts like the EM Drive and Quantum Drive. While these initiatives showcase potential, Exodus Propulsion Technologies' breakthrough offers a unique perspective.

Dr. Buhler welcomes collaboration with interested parties, offering their expertise to advance propulsion technologies mutually.

Notably, their experiments unveiled intriguing phenomena, including sustained thrust without continuous electrical input. Such anomalies prompt further inquiry and underscore the complexity of the underlying physics. Seeking funding for space demonstrations, Dr. Buhler envisions expanding their understanding and inspiring scientific exploration.

Reflecting on the broader implications, Dr. Buhler emphasized the role of science in dissecting their discovery's implications.

While their experiments provide empirical evidence, understanding the underlying principles remains a collective endeavor. He remains optimistic that their findings could illuminate profound scientific inquiries, challenging conventional understanding.

Dr. Buhler's revelation marks a pivotal moment in space exploration, unlocking new possibilities for propulsion technologies.

A few of the hundreds of tests the team ran on their propellantless propulsion drive between 2016 and 2023. (CREDIT: Exodus Propulsion Technologies, Buhler, et al.)

As scientists delve deeper into the mysteries of their discovery, the horizon of human exploration expands, propelled by ingenuity and curiosity.

Note: Materials provided above by the The Brighter Side of News. Content may be edited for style and length.

 

[Secure Da Bag]

Shuttlecraft on there way?

 

[inndaskKy]

Dr. Charles Buhler, a seasoned NASA engineer and co-founder of Exodus Propulsion Technologies. (CREDIT: Exodus Propulsion Technologies)

But also...




...he's built like prime Nikola Jokic

 

[Secure Da Bag]

We might be getting shuttlecrafts, brehs.

MSN

• Scientists at the Chinese Academy of Sciences have developed a quantum engine powered by entanglement—the quantum property allows for the transfer of information across vast distances.
• The researchers created this engine by placing two calcium atoms in an ion trap, zapping it with a laser, and using the differences in entanglement (rather than heat) to create energy.
• This concept doesn’t improve on the conversion efficiency of previous quantum engines, but it does prove that increased entanglement positively impacts mechanical efficiency.

The word “quantum” is proliferating into nearly every facet of modern technology. There’s quantum computers, of course, but also quantum hard drives, quantum internet, and yes, even quantum engines. However—as is true with all of these other “quantum” technologies—this isn’t your typical piston/combustion situation. Instead, these engines leverage the wonky properties of quantum mechanics to induce mechanical motion.

Although an incredibly nascent technology, quantum engines come in a couple different flavors. Last year, scientists at the Okinawa Institute of Science and Technology developed a quantum engine that leveraged the complicated interplay between fermions and Bose-Einstein condensates. This created energy by replacing heat (the typical energy source of an ICE engine) with the “quantum nature of the particles in the gas,” a press statement read at the time. This engine had an efficiency of 25 percent—not bad for a first go at it, but nowhere close to becoming a practical engine.
.......

 

[Secure Da Bag]

We're alot closer to "Computer" than I thought.

MSN

....
"With this new AI approach, the speed at which we can have a solution is unbelievable. The time to calculate the prediction of a heart digital twin is going to decrease from many hours to 30 seconds, and it will be done on a desktop computer rather than on a supercomputer, allowing us to make it part of the daily clinical workflow."

Partial differential equations are generally solved by breaking complex shapes like airplane wings or body organs into grids or meshes made of small elements. The problem is then solved on each simple piece and recombined. But if these shapes change—like in crashes or deformations—the grids must be updated and the solutions recalculated, which can be computationally slow and expensive.

DIMON solves that problem by using AI to understand how physical systems behave across different shapes, without needing to recalculate everything from scratch for each new shape. Instead of dividing shapes into grids and solving equations over and over, the AI predicts how factors such as heat, stress, or motion will behave based on patterns it has learned, making it much faster and more efficient in tasks like optimizing designs or modeling shape-specific scenarios.
....

 

[bnew]

New AI cracks complex engineering problems faster than supercomputers

Modeling how cars deform in a crash, how spacecraft responds to extreme environments, or how bridges resist stress could be made thousands of times faster thanks to new artificial intelligence that enables personal computers to solve massive math problems that generally require supercomputers.

www.sciencedaily.com

​

New AI cracks complex engineering problems faster than supercomputers​

​

The shape-shifting technological solution could be a game-changer for engineering designs​

Date: December 9, 2024 Source: Johns Hopkins University Summary: Modeling how cars deform in a crash, how spacecraft responds to extreme environments, or how bridges resist stress could be made thousands of times faster thanks to new artificial intelligence that enables personal computers to solve massive math problems that generally require supercomputers.

FULL STORY

---

Modeling how cars deform in a crash, how spacecraft responds to extreme environments, or how bridges resist stress could be made thousands of times faster thanks to new artificial intelligence that enables personal computers to solve massive math problems that generally require supercomputers.

The new AI framework is a generic approach that can quickly predict solutions to pervasive and time-consuming math equations needed to create models of how fluids or electrical currents propagate through different geometries, like those involved in standard engineering testing.

Details about the research appear in Nature Computational Science.

Called DIMON (Diffeomorphic Mapping Operator Learning), the framework solves ubiquitous math problems known as partial differential equations that are present in nearly all scientific and engineering research. Using these equations, researchers can translate real-world systems or processes into mathematical representations of how objects or environments will change over time and space.

"While the motivation to develop it came from our own work, this is a solution that we think will have generally a massive impact on various fields of engineering because it's very generic and scalable," said Natalia Trayanova, a Johns Hopkins University biomedical engineering and medicine professor who co-led the research. "It can work basically on any problem, in any domain of science or engineering, to solve partial differential equations on multiple geometries, like in crash testing, orthopedics research, or other complex problems where shapes, forces, and materials change."

In addition to demonstrating the applicability of DIMON in solving other engineering problems, Trayanova's team tested the new AI on over 1,000 heart "digital twins," highly detailed computer models of real patients' hearts. The platform was able to predict how electrical signals propagated through each unique heart shape, achieving high prognostic accuracy.

Trayanova's team relies on solving partial differential equations to study cardiac arrhythmia, which is an electrical impulse misbehavior in the heart that causes irregular beating. With their heart digital twins, researchers can diagnose whether patients might develop the often-fatal condition and recommend ways to treat it.

"We're bringing novel technology into the clinic, but a lot of our solutions are so slow it takes us about a week from when we scan a patient's heart and solve the partial differential equations to predict if the patient is at high risk for sudden cardiac death and what is the best treatment plan," said Trayanova, who directs the Johns Hopkins Alliance for Cardiovascular Diagnostic and Treatment Innovation. "With this new AI approach, the speed at which we can have a solution is unbelievable. The time to calculate the prediction of a heart digital twin is going to decrease from many hours to 30 seconds, and it will be done on a desktop computer rather than on a supercomputer, allowing us to make it part of the daily clinical workflow."

Partial differential equations are generally solved by breaking complex shapes like airplane wings or body organs into grids or meshes made of small elements. The problem is then solved on each simple piece and recombined. But if these shapes change -- like in crashes or deformations -- the grids must be updated and the solutions recalculated, which can be computationally slow and expensive.

DIMON solves that problem by using AI to understand how physical systems behave across different shapes, without needing to recalculate everything from scratch for each new shape. Instead of dividing shapes into grids and solving equations over and over, the AI predicts how factors such as heat, stress, or motion will behave based on patterns it has learned, making it much faster and more efficient in tasks like optimizing designs or modeling shape-specific scenarios.

The team is incorporating into the DIMON framework cardiac pathology that leads to arrhythmia. Because of its versatility, the technology can be applied to shape optimization and many other engineering tasks where solving partial differential equations on new shapes is repeatedly needed, said Minglang Yin, a Johns Hopkins Biomedical Engineering Postdoctoral Fellow who developed the platform.

"For each problem, DIMON first solves the partial differential equations on a single shape and then maps the solution to multiple new shapes. This shape-shifting ability highlights its tremendous versatility," Yin said. "We are very excited to put it to work on many problems as well as to provide it to the broader community to accelerate their engineering design solutions."

Other authors are Nicolas Charon of University of Houston, Ryan Brody and Mauro Maggioni (co-lead) of Johns Hopkins, and Lu Lu of Yale University.

This work is supported by NIH grants R01HL166759 and R01HL174440; a grant from the Leducq Foundations; the Heart Rhythm Society Fellowship; U.S. Department of Energy grants DE-SC0025592 and DE-SC0025593; NSF grants DMS-2347833, DMS-1945224, and DMS-2436738; and Air Force Research Laboratory awards FA9550-20-1-0288, FA9550-21-1-0317, and FA9550-23-1-0445.

GitHub - MinglangYin/DIMON

Contribute to MinglangYin/DIMON development by creating an account on GitHub.

github.com

[2402.07250] DIMON: Learning Solution Operators of Partial Differential Equations on a Diffeomorphic Family of Domains

 

[bnew]

AI generated:

Essential Questions & Answers to Capture the Main Points and Core Meaning of the Text​

1. What is the central theme or argument of the text, and how does the new AI framework, DIMON, address it?​

The central theme of the text is the development and application of a new artificial intelligence framework called DIMON (Diffeomorphic Mapping Operator Learning) that enables personal computers to solve massive math problems, specifically partial differential equations, much faster than supercomputers. DIMON addresses this by providing a generic approach that can quickly predict solutions to these equations, which are ubiquitous in scientific and engineering research. This framework allows for the efficient modeling of how objects or environments change over time and space, making it a game-changer for various engineering design tasks.

2. What are the key supporting ideas and applications of DIMON in various fields of engineering?​

DIMON has several key supporting ideas and applications:

• Crash Testing: It can model how cars deform in crashes.
• Spacecraft Design: It can simulate how spacecraft respond to extreme environments.
• Bridge Stress Analysis: It can analyze how bridges resist stress.
• Cardiac Research: It can predict how electrical signals propagate through unique heart shapes, aiding in the diagnosis and treatment of cardiac arrhythmia.
• General Engineering Problems: It is versatile and scalable, capable of solving partial differential equations on multiple geometries, making it applicable to a wide range of engineering tasks.

3. What crucial facts or evidence support the effectiveness and efficiency of DIMON?​

Several crucial facts support DIMON's effectiveness and efficiency:

• Speed Improvement: DIMON reduces the calculation time for predicting heart digital twins from many hours to just 30 seconds.
• Accuracy: It achieved high prognostic accuracy in predicting electrical signal propagation through heart digital twins.
• Versatility: It was tested on over 1,000 heart digital twins and demonstrated its ability to work on various shapes and problems.
• Computational Efficiency: Unlike traditional methods that require dividing shapes into grids and recalculating solutions for each new shape, DIMON uses AI to predict behavior based on learned patterns, making it much faster and more efficient.

4. What is the author's purpose or perspective in presenting this research, and what implications does it have for the broader scientific and engineering communities?​

The authors, led by Natalia Trayanova and Minglang Yin, present this research to highlight the significant impact DIMON could have on various fields of science and engineering. Their perspective is that DIMON is not just a solution for their specific work but a generic tool that can accelerate engineering design solutions across multiple domains. The implications are that DIMON can make complex engineering tasks faster, more efficient, and accessible on personal computers rather than requiring supercomputers, thereby integrating advanced computational capabilities into daily clinical workflows and engineering practices.

5. What are the significant implications or conclusions drawn from the implementation of DIMON, particularly in terms of speed, efficiency, and potential applications?​

The significant implications of DIMON include:

• Speed: It drastically reduces the time required to solve partial differential equations, from hours or days to seconds.
• Efficiency: It makes complex computational tasks more efficient by avoiding the need for repeated grid updates and recalculations.
• Potential Applications: Beyond cardiac research, DIMON can be applied to shape optimization, crash testing, orthopedics research, and other complex problems involving changing shapes and materials.
• Clinical Impact: It can become part of the daily clinical workflow for diagnosing and treating conditions like cardiac arrhythmia.
• Broader Impact: Its versatility and scalability suggest it could revolutionize how engineering designs are approached across various disciplines.