AI News, How would machine learning solve trolley problems?

How would machine learning solve trolley problems?

For example, if the world and people are magical, if the train causes something good to happen when someone is hit, if reality is designed to always have meaningful experiences (by the law of significance), or if the world is designed to have objects with a greater ratio of significance eliminating the need for trains, for example the Akashic Records or Paradise or a world for enchanters (the enchanters would have aesthetic taste that eliminated all dangers and made life thoughtful and sublime).

If we could just design all problems to be philosophical, divinatory, and contemplative events, with the outer world being chained to the inner one, there would be no need for harmful events.

Why Doesn't The United States Have High-Speed Bullet Trains Like Europe And Asia?

It kills me to think that for the amount of money and resources we have spent on the second Iraq war, we could have built the backbone of a nationwide high-speed rail network and subsidized its use for a number of years while it ramped up to optimal capacity.

These include: Last but not least, I am a natural optimist and I believe that America will ultimately figure out how to utilize certain emerging technologies to overcome the obstacles to implementing efficient, environmentally friendly and safe transportation for the masses.

I then appended data across a number of metrics and ordered them from top to bottom in terms of 'high speed rail intensity', my own metric that is simply based on the length of HSR lines per million inhabitants:

This contrasts sharply with the way towns were developed in the pre-automobile era, which is when most European towns and villages first came into existence -- these were designed around the primary mode of transportation of the era, a.k.a.

One of the most expensive parts of building new rail lines these days is securing land along a relatively straight path (you can't run trains at high speeds along too sharp a curve).

Case in point -- our most celebrated entrepreneur at the moment is a guy that runs a car company: The investment of hundreds of billions of dollars into the Interstate Highway System also reinforces the critical role of the Automobile in American culture.

In Taiwan, taxes are not as high but still more than doubles the effective price of this beaut: This all results in car ownership rates that are much higher compared to almost every other major country (as you can see in the data table above).

Again -- especially if you factor in the gray lines, many of which are candidates to be upgraded to high-speed rail lines -- this is a pretty intricate web of cities, and once again supports the economics of high-speed rail.

I simply cannot see how many of these proposed routes -- especially in the middle of the country -- can sustain the minimum economics needed to justify the tens of billions per year necessary upkeep and operating costs let alone the hundreds of billions of dollars needed to build those lines in the first place.

Warren Buffett explained his purchase of the remaining stake in the Burlington Northern Santa Fe (BNSF) Railway that he did not already own by citing the fact that these trains could move a ton of goods 470 miles on a single gallon of diesel gasoline.

What this means is that one of the costs of having an efficient freight railway network is that you cannot have a strong passenger traffic network (absent building a completely separate network of course).

So even though I see many obstacles to high-speed rail -- or more broadly, inexpensive, efficient and environmentally friendly mass transportation -- today, I also see how improvements in technology and forward progress in other areas can work to reduce many of these obstacles.

Smart entrepreneurs will surely figure out a way to build apps that connect train stations to a roving army of autonomous and semi-autonomous cars that can safely and efficiently ferry passengers on and off the trains as well as provide the necessary link to the suburbs.

Perhaps new tunneling techniques and machinery will arise which allows us to less expensively build underground tunnels in places where it is simply too hard to secure long, continuous tracts of land.

As we continue to become a wealthier and more productive society, we should look forward to someday being so wealthy and productive that we can easily allocate significant resources to solving our transportation issues while maintaining our very high standard of life elsewhere.

So even though there are some barriers that might hold us back from implementing these shiny new high-speed rail systems that we see many other places in the developed world, let's also remember that we also hold perhaps the most important card of all -- our optimism and ability to invent new technologies to continue pushing our country (and the world) forward.

3 Ways To Train Yourself To Be More Creative

As a result, most people tend to look at those people who develop creative ideas consistently with a kind of reverence.

And people who do seem blessed with a talent for creativity live in fear that talent will run out some day and they will be just like everybody else.

Afterward, if you try to repeat what you learned to someone else you may realize that your feeling of understanding was a reflection that the speaker understood the topic very well.

The Future of Jobs and Jobs Training

Automation, robotics, algorithms and artificial intelligence (AI) in recent times have shown they can do equal or sometimes even better work than humans who are dermatologists, insurance claims adjusters, lawyers, seismic testers in oil fields, sports journalists and financial reporters, crew members on guided-missile destroyers, hiring managers, psychological testers, retail salespeople, and border patrol agents.

Moreover, there is growing anxiety that technology developments on the near horizon will crush the jobs of the millions who drive cars and trucks, analyze medical tests and data, perform middle management chores, dispense medicine, trade stocks and evaluate markets, fight on battlefields, perform government functions, and even replace those who program software – that is, the creators of algorithms.

A recent study by labor economists found that “one more robot per thousand workers reduces the employment to population ratio by about 0.18-0.34 percentage points and wages by 0.25-0.5 percent.” When Pew Research Center and Elon University’s Imagining the Internet Center asked experts in 2014 whether AI and robotics would create more jobs than they would destroy, the verdict was evenly split: 48% of the respondents envisioned a future where more jobs are lost than created, while 52% said more jobs would be created than lost.

At the same time, recent IT advances offer new and potentially more widely accessible ways to access education.” Jobholders themselves have internalized this insight: A 2016 Pew Research Center survey, “The State of American Jobs,” found that 87% of workers believe it will be essential for them to get training and develop new job skills throughout their work life in order to keep up with changes in the workplace.

Some 1,408 responded to the following question, sharing their expectations about what is likely to evolve by 2026: In the next 10 years, do you think we will see the emergence of new educational and training programs that can successfully train large numbers of workers in the skills they will need to perform the jobs of the future?

Respondents see a new education and training ecosystem emerging in which some job preparation functions are performed by formal educational institutions in fairly traditional classroom settings, some elements are offered online, some are created by for-profit firms, some are free, some exploit augmented and virtual reality elements and gaming sensibilities, and a lot of real-time learning takes place in formats that job seekers pursue on their own.

focus on nurturing unique human skills that artificial intelligence (AI) and machines seem unable to replicate: Many of these experts discussed in their responses the human talents they believe machines and automation may not be able to duplicate, noting that these should be the skills developed and nurtured by education and training programs to prepare people to work successfully alongside AI.

One such comment came from Simon Gottschalk, a professor in the department of sociology at the University of Nevada, Las Vegas: “The skills necessary at the higher echelons will include especially the ability to efficiently network, manage public relations, display intercultural sensitivity, marketing, and generally what author Dan Goleman would call ‘social’ and ‘emotional’ intelligence.

[This also includes] creativity, and just enough critical thinking to move outside the box.” Another example is the response of Fredric Litto, a professor emeritus of communications and longtime distance-learning expert from the University of São Paulo: “We are now in the transitional stage of employers gradually reducing their prejudice in the hiring of those who studied at a distance, and moving in favor of such ‘graduates’ who, in the workplace, demonstrate greater proactiveness, initiative, discipline, collaborativeness – because they studied online.” Other respondents mentioned traits including leadership, design thinking, “human meta communication,” deliberation, conflict resolution, and the capacity to motivate, mobilize and innovate.

So in short, we can train small numbers of individuals (tens of thousands) per year using today’s community colleges and university systems, but probably not more.” Several respondents argued that job training is not a primary concern at a time when accelerating change in market economies is creating massive economic divides that seem likely to leave many people behind.

Most experts seem to have faith that rapid technological development and a rising wariness of coming impacts of the AI/robotics revolution are going to spur the public, private and governmental actions needed for education and training systems to be adapted to deliver more flexible, open, adaptable, resilient, certifiable and useful lifelong learning.

As automation puts increasing numbers of low- and middle-skill workers out of work, these models will also provide for certifications and training needs to function in an increasingly automated service sector.” Michael Wollowski, an associate professor of computer science at the Rose-Hulman Institute of Technology, commented, “We will definitely see a vast increase in educational and training programs.

Our established systems of job training, primarily community colleges and state universities, will continue to play a crucial role, though catastrophically declining public support for these institutions will raise serious challenges.” David Karger, a professor of computer science at MIT, wrote, “Most of what we now call online learning is little more than glorified textbooks, but the future is very promising.

The more likely enhancement will be to take digital enhancements out into the world – again, breaking down the walls of the classroom and school – to inform and enhance experience.” An anonymous respondent echoed the sentiment of quite a few others who do not think it is possible to advance and enhance online education and training much in the next decade, writing, “These programs have a cost, and too few are willing to sacrifice for these programs.” More such arguments are included in later sections of this report.

There will be a greater need for such systems as the needs for new expertise in the workforce [increase] and the capacity of traditional education systems proves that it is not capable of meeting the need in a cost-effective manner.” The president of a technology LLC wrote, “Training, teaching are all going online, partly because of high costs of campus education.” Richard Adler, distinguished fellow at the Institute for the Future, predicted, “AI, voice-response, telepresence VR and gamification techniques will come together to create powerful new learning environments capable of personalizing and accelerating learning across a broad range of fields.” Ray Schroeder, associate vice chancellor for online learning at the University of Illinois, Springfield, commented, “It is projected that those entering the workforce today will pursue four or five different careers (not just jobs) over their lifetime.

They will further fuel the scaling of learning to reach even more massive online classes.” Fredric Litto, an professor emeritus of communications and longtime distance-learning expert from the University of São Paulo, replied, “There is no field of work that cannot be learned, totally or in great part, in well-organized and administered online programs, either in traditional ‘course’ formats, or in self-directed, independent learning opportunities, supplemented, when appropriate, by face-to-face, hands-on, practice situations.” Tawny Schlieski, research director at Intel and president of the Oregon Story Board, explained, “New technologies of human/computer interaction like augmented and virtual reality offer the possibility of entirely new mechanisms of education.

As these tools evolve over the next decade, the academics we work with expect to see radical change in training and workforce development, which will roll into (although probably against a longer timeline) more traditional institutions of higher learning.” Many respondents said real-world, campus-based higher education will continue to thrive during the next decade.

Some say major universities’ core online course content, developed with all of the new-tech bells and whistles, will be marketed globally and adopted as baseline learning in smaller higher education locales, where online elements from major MOOCs can be optimally paired in hybrid learning with in-person mentoring activities.

… Human bodies in close proximity to other human bodies stimulate real compassion, empathy, vulnerability and social-emotional intelligence.Frank Elavsky Uta Russmann, communications/marketing/sales professor at the FHWien University of Applied Sciences in Vienna, Austria, said, “In the future, more and more jobs will require highly sophisticated people whose skills cannot be trained in ‘mass’ online programs.

Traditional four-year and graduate programs will better prepare people for jobs in the future, as such an education gives people a general understanding and knowledge about their field, and here people learn how to approach new things, ask questions and find answers, deal with new situations, etc.

Many people have gained these skills throughout history without any kind of formal schooling, but with the growing emphasis on virtual and digital mediums of production, education and commerce, people will have less and less exposure to other humans in person and other human perspectives.” Isto Huvila, professor at Uppsala University, replied, “The difference between educating to perform and educating to make the future is the difference between vocational [education] and higher (university) education.

But this does not mean that alternative means and paths of learning and accreditation would not be useful as … complementary to the traditional system that has limitations as well.” Dana Klisanin, psychologist/futurist at Evolutionary Guidance Media R&D, wrote, “Educational institutions that succeed will use the tools of social media and game design to grant students’ access to teachers from all over the world and increase their motivation to succeed.

… Online educational programs will influence the credentialing systems of traditional institutions, and online institutions will increasingly offer meet-ups and mingles such that a true hybrid educational approach emerges.” Will training for skills most important in the jobs of the future work well in large-scale settings by 2026?

Functions requiring emotional intelligence, empathy, compassion, and creative judgment and discernment will expand and be increasingly valued in our culture.” Tiffany Shlain, filmmaker and founder of the Webby Awards, wrote, “The skills needed to succeed in today’s world and the future are curiosity, creativity, taking initiative, multi-disciplinary thinking and empathy.

A mindset of persistence and the necessary passion to succeed are also critical.” Louisa Heinrich, founder at Superhuman Limited, commented, “Lateral and system-thinking skills are increasingly critical for success in an ever-changing global landscape, and these will need to be re-prioritised at all levels of education.” An anonymous technologist commented, “Programming and problem solving, learning how to work with artificial intelligence and robotics will become more important, and more and more workers will be replaced by software/hardware-based ‘workers.’ Automation will reduce the need for the current workforce, and the divide between the upper class and the lower class will continue to eat the middle class.” Some who are pessimistic about the future of human work due to advances in capable AI and robotics mocked the current push in the U.S. to train more people in technical skills.

A few people mentioned that young adults need to be taught how to have face-to-face interaction, including one who said they “seem to be sorely lacking in these skills and can only interact with a cellphone or laptop.” Because so many intricacies of the workplace – the human, soft and hard – are learned on the job, respondents said they expect apprenticeships and forms of mentoring will regain value and evolve along with the 21st‑century workplace.

Through evolving technologies (e.g., blockchain), this may provide opportunities for learners to document and frame their own learning pathways.” An instructional designer with 19 years of experience commented, “The pattern I’m seeing is toward individualized learning – almost on the level of tutoring or apprenticeship.

The key to the future will be flexibility and personal motivation to learn and tinker with new things.” As they anticipate the appearance of effective new learning environments and advances in digital accountability systems, many of these experts believe fresh certification programs will be created to attest to workers’ participation in training programs and the mastery of skills.

People with new types of credentialing systems are seen as more qualified than traditional four-year and graduate programs.” Many workplaces place a higher value on real-world work portfolios than they do on a degree or certification, yet their hiring systems – including AI bots programmed to scan resumés – still use the commonly accepted credentials as a basis for interviewing candidates.

software engineering and system administration professional commented, “The reliability of the traditional educational system is already being questioned – in some fields it’s considered common sense that certifications and degrees mean little, and that a portfolio, references, and hands-on interviews are much more important for assessing a candidate’s ability.

I believe that many – not all – areas of instruction should shift to competency-based education in which the outcomes needed are made clear and students are given multiple paths to achieve those outcomes, and they are certified not based on tests and grades but instead on portfolios of their work demonstrating their knowledge.” While the first three themes found among the responses to this canvassing were mostly hopeful about advances in education and training for 21st‑century jobs, a large share of responses from top experts reflect a significant degree of pessimism for various reasons.

Among the other reasons listed by people who do not expect these kinds of transformative advances in job creation and job skill upgrading: Some among the 70% of respondents who are mostly optimistic about the future of training for jobs also echoed one or more of the points above – mentioning these tension points while hoping for the best.

Thomas Claburn, editor-at-large at Information Week, wrote, “I’m skeptical that educational and training programs can keep pace with technology.” Traditional models train people to equate what they do with who they are (i.e., what do you want to be when you grow up) rather than to acquire critical thinking and flexible skills and attitudes that fit a rapidly changing world.Pamela Rutledge Andrew Walls, managing vice president at Gartner, wrote, “Barring a neuroscience advance that enables us to embed knowledge and skills directly into brain tissue and muscle formation, there will be no quantum leap in our ability to ‘up-skill’ people.

Remy Cross, assistant professor of sociology, Webster University, commented, “Lacking a significant breakthrough in machine learning that could lead to further breakthroughs in adaptive responses by a fully online system, it is too hard to adequately instruct large numbers of people in the kinds of soft skills that are anticipated as being in most demand.

… While there have been generational gains in the developments of online communities, a large-scale educational experience (either MOOC or on-demand broadcasts) will not be able to duplicate that.” Stowe Boyd, managing director of Another Voice and a well-known thinker on work futures, discussed the intangibles of preparing humans to partner with AI and bot systems: “While we may see the creation and rollout of new training programs,” he observed, “it’s unclear whether they will be able to retrain those displaced from traditional sorts of work to fit into the workforce of the near future.

And employers may play less of a role, especially as AI- and bot-augmented independent contracting may be the best path for many, rather than ‘a job.’ Homesteading in exurbia may be the answer for many, with ‘forty acres and a bot’ as a political campaign slogan of 2024.” Luis Miron, a distinguished university professor and director of the Institute for Quality and Equity in Education at Loyola University in New Orleans, wrote, “Bluntly speaking, I have little confidence in the educational sector, K-16, having the capacity and vision to offer high-quality online educational programs capable of transforming the training needs of the wider society.

… Successful education models will begin developing ‘mixed methods’ to leverage technology with traditional delivery and rewrite certification processes with practice-relevant standards.” Justin Reich, executive director at the MIT Teaching Systems Lab, observed, “There will continue to be for-profit actors in the sector, and while some may offer choice and opportunity for students, many others will be exploitative, with a great[er] focus on extracting federal grants and burdening students with debt than actually educating students and creating new opportunities.” John Paine, a business analyst, commented, “The competing desires 1) to make educational activity available to all and 2) to monetize the bejeezus out of anything related to the internet will limit the effectiveness of any online learning systems in a more widespread context.” danah boyd, founder of Data &

Whether the traditional programs or new programs will be better at teaching adaptive learning remains to be seen.” Cory Salveson, learning systems and analytics lead at RSM US, responded, “The nature of work today, and in future, is such that if people want to keep increasingly scarce well-paying jobs, they will need to educate themselves in an ongoing manner for their whole lives.” Some of these experts say those who aren’t motivated to continue to learn and grow will be left behind.

So, not only does the self-direction factor pose a problem for teaching at scale, the fact that a high degree of self-direction may be required for successful completion of coursework towards the new workforce means that existing structures of inequality will be replicated in the future if we rely on these large-scale programs.” Among the 30% of respondents who said they did not think things would turn out well in the future were those who said the trajectory of technology will overwhelm labor markets, killing more jobs than it creates.

They foresee a society where AI programs and machines do most of the work and raise questions about people’s sense of identity, the socio-economic divisions that already distress them, their ability to pay for basic needs, their ability to use the growing amount of “leisure time” constructively and the impact of all of this on economic systems.

The current automation is based on ‘general purpose’ technologies – machine learning, Turing complete computers, a universal network architecture that is equally optimized for all applications – and there’s good reason to believe that this will be more disruptive, and create fewer new jobs, than those that came before.” Glenn Ricart, Internet Hall of Fame member and founder and chief technology officer of US Ignite, said, “Up to the present time, automation largely has been replacing physical drudgery and repetitive motion – things that can and should improve the quality of people’s work lives.

How will we cope with a workforce that is simply irrelevant?” The question isn’t how to train people for nonexistent jobs, it’s how to share the wealth in a world where we don’t need most people to work.Nathaniel Borenstein Nathaniel Borenstein, chief scientist at Mimecast, replied, “I challenge the premise of this question [that humans will have to be trained for future jobs].

There is also the massive sociological economic impact of general automation and AI that must be addressed to redistribute wealth and focus life skills at lifelong learning.” Tom Sommerville, agile coach, wrote, “Our greatest economic challenges over the next decade will be climate change and the wholesale loss of most jobs to automation.

There will also be a parallel call for benefits, professional development, and compensation that smooths out the rough patches in this on-demand labor life, but such efforts will lag behind the exploitation of said labor because big business has more resources and big tech moves too fast for human-scale responses of accountability and responsibility.

As a society we need to take advantage of that, and nurture our natural hunger for knowledge and productive work while respecting and encouraging our diversity, a fundamental balancing feature of all nature, human and otherwise.” Jeff Jarvis, professor at the City University of New York Graduate School of Journalism, wrote, “At a roundtable on the future convened by Union Square Ventures a few years ago, I heard this economic goal presented: We need to see the marginal cost of teaching another student fall to zero to see true innovation come to education, allowing change to occur outside the tax-based (and thus safe) confines of public education.

But we will likely see a radical economic disruption in education – using new tools and means to learn and certify learning – and that is the way by which we will manage to train many more people in many new skills.” Cory Doctorow, activist-in-residence at MIT Media Lab and co-owner of Boing Boing (boingboing.net), responded, “There is, for the immediate and medium term, a huge shortage of IT talent, of course – especially security researchers and professionals.

An earlier and more enduring focus on stats and statistical literacy – which can readily be taught using current affairs, for example, analyzing the poll numbers from elections, the claims made by climate change scientists, or even the excellent oral arguments in the Supreme Court Texas abortion law case – would impart skills that transferred well into IT, programming and, especially, security.” Amy Webb, futurist and CEO at the Future Today Institute, commented, “Gill Pratt, a former program manager of the Defense Advanced Research Projects Agency (DARPA), recently warned of a Cambrian Explosion of robotics.

If there are unanticipated external events – environmental disasters, new pandemics and the like – that could devastate a country’s economy and significantly impact its workforce, which might catalyze the development of online learning opportunities.” Mike Roberts, Internet Hall of Fame member and first president and CEO of the Internet Corporation for Assigned Names and Numbers (ICANN), responded, “MOOCs and related efforts are in their infancy, so ‘yes,’ there will [be] considerable expansion as more is learned about what works and what doesn’t work.

And most importantly, we do not mix education with religion – never.’” Anil Dash, entrepreneur, technologist, and advocate @AnilDash, predicted, “These credentials will start to become widespread, but acceptance and quality of the training programs will map to the existing systemic biases that inform current educational and career programs.” Henning Schulzrinne, Internet Hall of Fame member and professor at Columbia University, wrote, “Training programs have had the problem that short-duration generic programs are often not very effective except as a way to incrementally add very specific skills (‘learn how to operate the new industry-specific tool X in a week’) to the existing repertoire.

The MOOC-style programs have shown themselves to be most effective for this ‘delta’ learning for practicing professionals, not turning a high school graduate into somebody who can compete with a college graduate.” Jamais Cascio, distinguished fellow at the Institute for the Future, responded, “We will certainly see attempts to devise training and education to match workers to new jobs, but for the most part they’re likely to fall victim to two related problems.

As learning systems improve, we will soon (if we’re not already) be at a point where adaptive algorithms can learn new jobs faster than humans.” Kate Crawford, a well-known internet researcher studying how people engage with networked technologies, wrote, “We clearly need new educational and training programs to address the deepening precarity of the labor market.

K-12 teachers are constantly pulled from class time with students for professional development or during class are required to take attendance, [complete] grade assessments, fill out grade checks, practice fire drills – all degrading quality teaching time.

Large school systems can’t scale major improvements in current systems without leveraging the tools that society and industry are using to transform their practice.” Barry Chudakov, founder and principal at Sertain Research and StreamFuzion Corp., replied: “One serious drawback to fast-tracking needed educational and training programs: the people who are creating the jobs of the future have so little time to reflect and gain perspective on the people they will need – and how adding these people to their corporate culture changes that culture.

These entrepreneurs are so busy building technology infrastructures, filing patents, testing beta incarnations of ideas and processes – not to mention navigating the thicket of regulations and restrictions that surround many emerging technologies and industries – that they simply don’t have time to look around and see the implications of the changes their companies are creating.

Because all human processes and activities can now be quantified, and there is considerable exploration and technology development in the application of quantification to everything from our sleep patterns and shopping habits to our emotions and online behaviors, many new and important business models are emerging from quantification and the learning algorithms that drive it.

Lastly, we don’t need large-scale training of workers – we need real education (not job-focused) and opportunities for people to pursue diverse pathways for career development and lifelong learning.” Patrick Tucker, technology editor at Defense One and author of “The Naked Future,” observed: “Online education offers the opportunity to gather data on student performance continuously, or telemetrically.

… What telemetric education offers is the opportunity to continuously and constantly evaluate a student to gain a much more comprehensive understanding of ability, retention of information, even how other behaviors and factors such as time of day, other calendar items, nutrition, amount of time on Pokemon Go, influence learning.

That opportunity doesn’t come easily in a crowded classroom – especially not for women or minority students, many of whom feel that if they ask the wrong question or display ignorance, they’ll confirm some unflattering, broadly held perception about their social group.” David Golumbia, associate professor of digital studies at Virginia Commonwealth University, commented, “As an educator, I am completely unconvinced by the current rhetoric that says our educational system is unable to meet the needs of current or future workforces.

Maglev: Magnetic Levitating Trains

Maglev trains use magnetism to levitate above the tracks on which they travel.

It also discusses the importance of electrical engineering in developing maglev, and how electrical engineers can make this technology the next transportation revolution.

Instead of rolling along the track, it quietly floats above and glides smoothly from origin to destination without ever touching a rail.

This may sound like science fiction, but instances of this technology already exist in a number of places in the world.

The fundamental ideas behind maglev technology can be traced back to the early 20th century.

Much work went into laying the groundwork for these trains, including the development of electric motors and research in magnetism.

A few scientists, namely Robert Goddard and Emile Bachelet, even dared to propose a vehicle that would float using magnets (Yadav, 2013).  In 1934, a German man by the name of Hermann Kemper was given a patent for the first concept of a magnetic, levitating train (Yadav, 2013).

Germany built and tested a string of prototype maglev systems and called their design the TransRapid (Figure 1).

The trains achieved speeds of over 250 mph (402 kph) on the test track (Luu, 2005).

Source: © Stahlkocher / CC BY-SA 3.0 Japan continued development of its maglev technology into the 90s and beyond.

They tested a new series, called the MLX, which broke 350 mph (563 kph) in 2003 (Yadav, 2013).

It carries passengers a distance of 19 miles (30km) in 8 minutes, reaching a top speed of over 250 mph (431 kph) (Coates, 2004).

There are three essential parts to achieving maglev functionality: levitation, propulsion and guidance (as seen below).

A normal electric rotary motor uses magnetism to create torque and spin an axle.

Similarly, instead of a rotating force, the rotor experiences a linear force that pulls it down the stator.

When describing a linear motor, the standard is to use the term “primary” instead of “stator,” and “secondary” instead of “rotor.” In maglev trains, the secondary is attached to the bottom of the train cars, and the primary is in the guideway.

Because the secondary is now producing its own stationary magnetic field, it travels down the primary in sync with the moving field—hence the name for this variant of motor (Gieras, 2011).

Through this connection, when the train moves closer to one side a restoring force is induced which pushes it back towards the center.

It travels over 50 mph (80 kph) faster than the fastest high-speed wheel-rail (320-kph Hayabusa, 2013).

Any organization attempting to implement a maglev system must start from scratch and build a completely new set of tracks.

Even though guideways cost less than rails over time (Powell, 2003), it is hard to justify spending so much upfront.

Countries with high-speed rails already in place don’t want to spend billions of dollars implementing a system that is only marginally better than the existing solution.

Developing these trains has required input from a number of different fields other than mechanical engineering, including physics and chemistry.

Eric Laithwaite, an electrical engineer, developed the first linear induction motor, an important and necessary precursor to maglev trains.

Some important topics to the field are electromagnetic fields and waves, circuit theory, feedback control systems, and power engineering.

There are even proposals to build long underground tubes, suck the air out of the tubes, and place maglev trains inside of them.

In this setting there would be virtually no wind resistance, so a train could easily reach speeds exceeding the speed of sound (Thornton, 2007).

I, for one, look forward to gliding across the countryside at 300 mph in a levitating box of magnets.

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