Chapter 16

IN THIS CHAPTER

Investigating the universe

Building off world mines

Looking for new places to explore

Developing structures in space

People have been observing the heavens since time immemorial. Many of the names of constellations and stars come from the Greeks or other ancients (depending on where you live). The Big Dipper alone has many different names and may be seen as a bear when grouped with other stars (see https://tinyurl.com/ymumd3xb for details). People love gazing at the stars and thinking about them, which is why many cultures have thought about actually seeing what the stars look like. As people have become capable of space travel, the universe, as a whole, has taken on new meaning, as described in this chapter. AI enables people to see the universe more clearly and view it in new ways.

Over the years, humans have begun living in space (such as at the International Space Station: https://tinyurl.com/2r2hrbjm) as well as visiting other places, such as the moon and possibly beyond (see https://tinyurl.com/cr92patb and https://tinyurl.com/aftwt6xh). Humans have also begun working in space. Of course, various experiments have produced materials that people can produce only in space. A company, Made In Space (https://madeinspace.us/) actually specializes in this activity. Outside these activities, the use of robots and specialized AI enables the mining of all sorts of materials in space. In fact, the U.S. Congress passed legislation in 2015 making such activity financially feasible by giving companies rights to sell what they mine (https://tinyurl.com/7ajr5v56). This space-mining trend is continuing, but not without some hiccups (see https://tinyurl.com/2jsrud8c and https://tinyurl.com/9zbjss6w). In addition to all of these considerations, this chapter also looks at the role of AI in making space mining work.

The universe holds nearly infinite secrets. One recently discovered secret is the existence of exoplanets, those that exist outside our solar system (see https://tinyurl.com/j69hyp8e for details). Quite a few of them are habitable from our perspective (https://tinyurl.com/z5nrazrf), although scientists think that even uninhabitable for us might still support life for others. The existence of exoplanets means that humans might eventually find life on other planets, but even finding the exoplanets requires AI. The ways in which AI will make all these possibilities visible is truly amazing.

Living and working in space is one thing, but vacationing in space is quite another. As early as 2011, people began talking about the possibility of creating a hotel in near-Earth orbit (https://tinyurl.com/v5eysc7k) or the moon, but the date of the first opening has moved a bit since early hype (https://tinyurl.com/j286e9pz). Some people can take a trip to space now, albeit for just a few minutes, courtesy of Blue Origin’s New Shepard rocket (https://tinyurl.com/d8z4hu8). The point is, AI will enable people to live, work, and even vacation in space using specialized structures, as described in this chapter.

Observing the Universe

A Dutch eyeglass maker named Hans Lippershey is credited with inventing a telescope (which at that time, in about 1600, was called Dutch perspective glasses). (Actually, just who invented the telescope is a subject for significant debate; see https://tinyurl.com/762wc3h3.) Scientists such as the Italian astronomer Galileo Galilei immediately began to scan the skies with something more than their eyes. Thus, telescopes have been around for a long time and have become larger, more complex, and even space based over the years.

The reason for sticking telescopes in space is that the earth’s atmosphere makes it impossible to obtain clear images of anything too far away. The Hubble telescope is one of the first and most famous of the space-based telescopes (see https://tinyurl.com/3pcdhrdv), but many others have followed and more are planned (https://tinyurl.com/2u4yest4 and https://tinyurl.com/x587knmv). As described in the following sections, using modern telescopes requires AI in a number of ways, such as scheduling time to use the Hubble (see https://www.stsci.edu/hst).

Seeing clearly for the first time

One way to avoid earth’s atmosphere is to put your telescope in space. However, this approach is a little on the expensive side, and maintenance can become a nightmare. Most people observing the heavens need another alternative, such as a telescope that can adjust for the blurring action of the earth’s atmosphere by warping the telescope’s mirror (see https://tinyurl.com/46zrn98r).

Imagine having to calculate the blurring effect of the earth’s atmosphere based on the light from something like a laser thousands of times a second. The only way to make such a huge number of calculations and then move the mirror’s actuators in just the right way is to use AI, something that is quite adept at performing the sort of math required to make adaptive optics possible. The article at https://tinyurl.com/r2a7bwsb provides just one example of the use of AI in adaptive optics. The sites at https://tinyurl.com/3bchhr2a and https://tinyurl.com/5hwhj53b provide additional resources for discovering how neural networks are used in adaptive optic systems.

To provide even better optics, future telescopes will feature 3-D correction of blurring effects using Multiconjugate Adaptive Optics (MCAO) (https://tinyurl.com/k96suruf and https://tinyurl.com/bwmfh6bn). This new technology will correct the narrow field of view suffered by current telescopes, but will require even greater (and more precise) control of multiple actuator levels through multiple mirrors. Telescopes such as the Giant Magellan Telescope, the Thirty-Meter Telescope, and the European Extremely Large Telescope (see https://tinyurl.com/yjfrzx59) will rely on this technology to make their $1 billion-plus investment price worth the effort. (Efforts are ongoing with MAVIS, the MCAO-Assisted Visible Imager and Spectrograph, described at https://tinyurl.com/245ap3nr.)

Finding new places to go

Before the eighteenth century, people were tied to the surface of the earth, but they still gazed at the heavens and dreamed. Humans tried all sorts of odd experiments to leave earth, such as tower jumping (see https://tinyurl.com/5e4sywva), but before hot air balloons, any sort of true flight seemed out of reach. We still explored, though, and humans continue to explore today, looking for new places to go.

The idea of having places to visit really didn’t become much of a reality before the first moon landing on July 20, 1969 (see https://tinyurl.com/m8unzp9s). Yes, we could look, but we couldn’t touch. Even so, since that time people have looked at all sorts of places to go and have, through robots, reached a few of them, such as Mars (https://tinyurl.com/382b95d4 and https://tinyurl.com/3nb345wd) and the Rosetta comet (see https://tinyurl.com/5px86sr5). Each of these explorations serves to stimulate the human desire to go to still other new places. More important, none of them would have happened without the complex math that AI can perform.

Finding things in space used to rely on telescopes. However, NASA and other organizations increasingly rely on other approaches, such as using AI, as described at https://tinyurl.com/u44vey2p. In this case, machine learning made it possible to locate an eighth planet around Kepler 90. Of course, the problem with finding so many places to go is determining whether we can actually reach some of the more exotic places. Voyager 1, the probe farthest from Earth, has recently picked up a new signal (https://tinyurl.com/4nmcunwu) created by plasma waves from other worlds. Yet, it’s only 14 billion miles away (0.0024 light years), just a walk in the galactic park, and Kepler 90 is 2,545 light years away, so any interstellar travel will take a long time and require the use of AI.

Fortunately, our own solar system contains all kinds of places that might be reachable. For example, the Encyclopaedia Britannica recommends visiting places like the Caloris Basin on Mercury (see https://tinyurl.com/5dzfft8f). You might also want to check out the MIT Technology Review (https://tinyurl.com/rmp6th7s) for the top-five locations today (the list changes a bit all the time as we learn more).

Considering the evolution of the universe

Humans have stared at the universe for a long time and still have no real idea of precisely what the universe is, except to know that we live in it. Of course, the observations continue, but the essence of the universe is still a huge unknown. Scientists use AI to carefully plot the motions of various parts of the universe to try to discover just how the universe works (see https://tinyurl.com/bfknhdc).

Creating new scientific principles

Ultimately, the research that humans perform in learning more about space, the local solar system, the galaxy, and the universe must pay some dividend. Otherwise, no one will want to continue funding it. The AI winters discussed in Chapter 15 are an example of what happens to a technology, no matter how promising, when it fails to deliver on expectations. Consequently, given the long history of space exploration, people must be deriving some benefit. In most cases, these benefits are in the form of new scientific principles — an increase in the understanding of how things work. By applying the lessons learned from space exploration and travel, people can make life here on earth better. In addition, space-based technologies often find their way into products that people use daily.

Consider just one exploration: the Apollo 11 moon landing. People still feel the effects of the technology explosion that occurred during the workup for that mission. For example, the need to conserve space prompted the government to spend lots of money on technologies such as integrated circuits (ICs) that we take for granted today (see https://tinyurl.com/myebdcnr). Depending on what source you read, every dollar invested in research by the government in NASA nets Americans $7 to $8 in goods and services today.

However, the space race generated new technology beyond the creation of actual capsules and their associated components. For example, the movie Hidden Figures (https://tinyurl.com/4bjerd5n) presents a view of NASA that most people don’t think about: All that math requires a lot of computing power. In the movie, you see the evolution of NASA math from human computers to electronic computers. However, if you watch the movie carefully, you see that the computer ends up working alongside the human, much as AI will work alongside humans as our knowledge of the universe increases.

Today we have data about space coming from everywhere. This data is helping us create new scientific principles about things we can’t even see, such as dark matter (an area of space with mass but no visible presence) and dark energy (an unknown and unidentified form of energy that counteracts the effects of gravitation between bodies in space). By understanding these invisible entities using technologies like the dark emulator (https://tinyurl.com/pvf7pyy7), we build new knowledge about how forces work on our own planet. Researchers are so buried in data, however, that they must use AI just to make sense of a small part of it (see https://tinyurl.com/yvuxk8fu). The point is that the future of space and our use of technologies created for space depend on making use of all that data we’re collecting, which requires AI at this point.

Performing Space Mining

Space mining has received more than a little attention in the media and the scientific community as well. Movies such as Alien (https://tinyurl.com/acdyp4ya) provide a glimpse as to what a future mining ship might look like. (With luck, space mining won’t involve hostile aliens.) People and organizations have a number of reasons to want to exploit space mining, such as to save planet Earth from further ecological damage (https://tinyurl.com/kcj4tzrt). Of course, there is the money aspect as well (https://tinyurl.com/244w6s7d). Countries of all sizes are getting involved in space mining (see https://tinyurl.com/88dsakfb and https://tinyurl.com/r3hty7yw for details). There are also detractors who think the idea will never take solid form (https://tinyurl.com/2df2krsk). With all this in mind, the following sections take a deeper look at space mining.

Harvesting water

Water covers about 71 percent of the earth. In fact, the earth has so much water that we often find it difficult to keep it out of places where we don’t want it. However, earth is an exception to the rule. Space doesn’t have an overabundance of water. Of course, you might wonder why you’d even need water in space, other than of the sort needed to keep astronauts hydrated and potentially to keep plants irrigated. The fact is that water makes great rocket fuel. Separating H₂O into its constituent components produces hydrogen and oxygen, which are both components of rocket fuel today (see https://tinyurl.com/23jpp9b5 for details). Consequently, that big, dirty ice ball in the sky could end up being a refueling station at some point.

Obtaining rare earths and other metals

Mining has always been dirty, but some mining is much dirtier than other mining, and rare earths fall into that category. Rare-earth mining is so dirty (see https://tinyurl.com/mnbh7ayy and https://tinyurl.com/zue7deyk) that all the rare-earth mines in the U.S. were closed until the U.S. government saw a need to reopen the Mountain Pass rare-earth mine as a strategic reserve for the military because of a Chinese chokehold on rare earths (https://tinyurl.com/4asedrzj). One of the worst parts of rare-earth mining is that it irradiates the surrounding areas with thorium radiation.

USING DRONES AND ROBOTS FOR MINING

You can’t determine what an asteroid contains until you get really close to it. In addition, the number of asteroids that require exploration before finding anything worthwhile is significant — far more than human pilots could ever explore. Also, getting close to any object that might be rotating in an odd way and have strange characteristics involves dangers. For all these reasons, most asteroid exploration for mining purposes will occur by using autonomous drones of various sorts. These drones will go from asteroid to asteroid, looking for needed materials. When a drone finds a needed material, it will alert a centralized station with precise location information and other asteroid characteristics.

As this point, a robot will be dispatched to do something with the asteroid. Most people feel that mining will occur in place, but actually, mining in place would prove both dangerous and costly. Another idea is to move the asteroid to a safer location, such as in orbit around the moon, to perform the required mining. The point is that robots would do the moving, and possibly other robots would perform the mining. Humans might be involved in robot repair and likely involved in monitoring both drone and robot activities. Think about it as safer, less polluting, and more interesting mining than could happen here on earth.

One of the more interesting developments is that a company in China recently sent a space-mining robot into near-Earth orbit to clean up the mess there (https://tinyurl.com/3r8u3hpv). This might seem like an unimportant step, but it’s a step nonetheless, and scientists will gain essential information from this step into a much larger world of mining.

The cellphone you carry, the tablet you use, the car you drive, the television you watch, and the solar panel and windmill that provide electricity to your house all rely on extremely hazardous materials in the form of rare earths (see https://tinyurl.com/yt6hak4s for just a few examples of usage). Most people aren’t even aware that these materials aren’t sustainable because of the way we currently use them (https://tinyurl.com/9df6xu25). Given the track record of these minerals, they represent the best reason to mine minerals off planet, where the toxins won’t affect us any longer. In fact, mining should be only the first step; all manufacturing should move off planet as well (yes, the potential for pollution is that great).

AI is essential to efforts to find better sources of rare earths that won’t pollute our planet into oblivion. One of the interesting oddities of rare earths is that the moon has a significant supply of them (see https://tinyurl.com/c67pkc68) and mining could start there as early as 2025. In fact, many politicians now see mining the moon for rare earths as a strategic need (see https://tinyurl.com/7j9hxczz). The problem is that efforts to discover precisely what the moon is made of haven’t been altogether successful so far, and it’s important to know what to expect. The Moon Minerology Mapper (https://tinyurl.com/yw8ns87p) is just one of many efforts to discover the composition of the moon. (An upcoming project, Trailblazer (https://tinyurl.com/2xsr55jf), will look for water.) The probes, robots, data analysis, and all the required planning will require use of AI because the issues are a lot more complicated than you might think.

Finding new elements

The periodic table that contains a list of all available elements has received a number of updates over the years. In fact, four new elements appeared in the table in 2016 (see https://tinyurl.com/2ab23chb). However, finding those four new elements required the work of a minimum of a hundred scientists using advanced AI (see https://tinyurl.com/337etd7z) because they typically last a fraction of a second in a lab environment. Interestingly enough, space could provide an environment in which these new elements exist naturally, rather than a fraction of a second, as they do on earth, because the protons in the nucleus repel each other.

As this story shows, we’re still finding new elements to add to the periodic table, and space will almost certainly provide even more. Supernovas and other space phenomena can help replicate elements that scientists create by using particle accelerators or reactors. In fact, particle physicists have used AI in their work since the 1980s (see https://tinyurl.com/26phwpku).

Combining the elements provides new materials. AI is also directly responsible for helping chemists find new ways to combine elements into interesting new crystals (see https://tinyurl.com/z6jutf9s). In one case, scientists discovered 2 million new kinds of crystals using just four elements, but those discoveries relied on the use of AI. Just imagine what will happen in the future as scientists start opening the door to AI and deep learning (which will be able to determine whether the resulting crystals are actually useful).

Enhancing communication

Any undertaking in space that is as complex as mining requires the use of advanced communications. Even if the probes and robots used for mining include deep learning capability to handle most of the minor and some of the major incidents that will occur during the mining process, humans will still need to solve problems that the AI can’t. Waiting for hours only to discover that a problem exists, and then spending yet more hours trying to determine the source of the problem, will spell disaster for space-based mining. Current manual communication techniques require an upgrade that, odd as it might seem, also includes AI (see https://tinyurl.com/rp7anumz).

Cognitive radio relies on AI to make decisions automatically about the need to improve radio efficiency in various ways (see https://tinyurl.com/3xcffd3p). The human operator need not worry about precisely how the signal gets from one place to another; it simply does so in the most efficient manner possible. In many cases, cognitive radio relies on unused or underused spectrum to achieve its goal, but it can rely on other methods as well. In other words, the current methods to control probes such as those listed at https://tinyurl.com/5dmvkewz just won’t work in the future when it’s necessary to do more, in less time, with less spectrum (because of the increased communication load).

Exploring New Places

Space is vast. Humans are unlikely to ever explore it all. Anyone who tells you that all the frontiers are gone has obviously not looked up at the sky. Even the sci-fi authors seem to think that the universe will continue to hold places to explore for humans. Of course, if multiverse theory is true (https://tinyurl.com/4thxmsyf), the number of places to explore may be infinite. The problem isn’t even one of finding somewhere to go; rather, it’s one of figuring out which place to go first. The following sections help you understand the role of AI in moving people from planet earth, to other planets, and then to the stars.

Starting with the probe

Humans have already starting putting probes out everywhere to explore everything. In fact, using probes is older than many people think. As early as 1916, Dr. Robert H. Goddard, an American rocket pioneer, calculated that a rocket could be sent to the moon with an explosive payload that could be seen from earth. However, it was E. Burgess and C. A. Cross who gave the world the term probe as part of a paper they wrote entitled The Martian Probe in 1952. Most people consider a space probe to be a vehicle designed to escape earth and explore some other location. The first probe to make a soft landing on the moon was Luna 9 in 1966.

Probes today aren’t just trying to reach some location. When they arrive at the location, they perform complex tasks and then radio the results of those tasks back to scientists on earth. For example, NASA designed the Mars Curiosity probe to determine whether Mars ever hosted microbial life. (The search for life continues with the Perseverance rover: https://tinyurl.com/3j6kuv85). To perform this task, both rovers have complex computer systems that can perform many tasks on their own and Perseverance has a complex set of goals to achieve (https://mars.nasa.gov/mars2020/mission/science/goals/). Of course, the highlight of current Mars visitors is Ingenuity, which is the first helicopter on the planet (https://mars.nasa.gov/technology/helicopter/). In all three cases, waiting for humans simply isn’t an option in many cases; some issues require immediate resolution.

It doesn’t take much to imagine the vast amount of information that individual probes, such as Curiosity, generate. Just analyzing the Curiosity data requires the same big data analytics used by organizations such as Netflix and Goldman Sachs (see https://tinyurl.com/7bb2xc5x). The difference is that the data stream comes from Mars, not from local users, so any data analysis must consider the time required to actually obtain the information. In fact, the time delay between Earth and Mars is as much as 24 minutes (and when the two planets are in conjunction for a couple of weeks every few years, no communication is possible). With this in mind, Curiosity and other probes must think for themselves (https://tinyurl.com/rffj8j29) even when it comes to performing certain kinds of analysis.

After data arrives back on Earth, scientists store and then analyze it. The process, even with the help of AI, will take years. Obviously, reaching the stars will take patience and even more computing power than humans currently possess. With the universe being such a messy place, the use of probes is essential, but the probes may need more autonomy just to find the right places to search.

CONSIDERING EXISTING COLONIZATION TARGETS

Depending on which article you read, scientists are already considering likely places for humans to colonize sometime in the future. Colonization will become essential for numerous reasons, but the burgeoning population of planet earth figures highly in the math. Of course, the potential factories and mining operations on other planets are also part of the consideration. Plus, having another place to live does improve our chances should another killer asteroid strike earth. With these thoughts in mind, here is a list of the commonly considered colonization targets (your list may differ):

· Moon

· Mars

· Europa

· Enceladus

· Ceres

· Titan

All these potential candidates come with special requirements that AI can help solve. For example, colonizing the moon requires the use of domes. In addition, colonists must have a source of water — enough water to split into oxygen for breathing and hydrogen to use as a heat source and fuel. So, probes will provide some information, but modeling the colonization environment will require time and a great deal of processing power here on earth before humans can move to some other location.

Relying on robotic missions

Humans aren’t likely to ever actually visit a planet directly as a means of learning more about it, sci-fi books and movies notwithstanding. It makes more sense to send robots to planets to discover whether sending humans there is even worth the time, because robots are less expensive and easier to deploy. Humans have actually sent robots to a number of planets and moons in the solar system already, but Mars seems to be a favorite target for a number of reasons:

· A robotic mission can leave for Mars every 26 months.

· Mars is in the solar system’s habitable zone, so it makes a likely target for colonization.

· Many scientists believe that life once existed on Mars.

The human love affair with Mars started in October 1960 when the Soviet Union launched Marsnik 1 and Marsnik 2. Unfortunately, neither probe even made it into Earth’s orbit, much less to Mars. The U.S. tried next, with the Mariner 3 spacecraft in 1964 and the Mariner 4 spacecraft in 1965. The Mariner 4 fly-by succeeded by sending 12 photos of the red planet back to Earth. Since that time, humans have sent myriad probes to Mars and a host of robots as well, and the robots are starting to reveal the secrets of Mars. (The success rate for trips to Mars, however, is less than 50 percent, according to https://tinyurl.com/2djdb6um.) Besides probes designed to perform fly-bys and observe Mars from space, robots land on Mars in three forms:

· Lander: A robotic device designed to sit in one place and perform relatively complex tasks.

· Rover: A robotic device that moves from one location to another — increasing the amount of ground covered.

· Flyer: A robotic device that is able to fly from one location to another—covering large amounts of ground relatively fast and from an aerial vantage point.

You can find a list of the landers and rovers sent to Mars since 1971 at https://tinyurl.com/5h9y7jzs and https://tinyurl.com/423ataen. Even though most landers and rovers come from the United States, China, or the former Soviet Union (which actually wasn’t successful), at least one rover is from England (Japan has one planned for the near future). As the techniques required for a successful landing become better known, you can expect to see other countries participate in the race to Mars (even if only by remote control).

As landers and rovers become more capable, the need for AI increases. For example, Perseverance has a relatively complex AI that helps it choose new targets for exploration autonomously, as described at https://tinyurl.com/3yyzyjdx. Don’t get the idea, though, that this AI is replacing the scientists on Earth. The scientists still determine the properties of the rocks that the AI will search for when used. In addition, a scientist can override the AI and choose a different target. The AI is there to assist, not replace, the scientist and provides an example of how people and AI will work together in the future.

Adding the human element

Humans want to visit places beyond Earth. Of course, the only place that we’ve actually visited is the moon. The first such visit occurred on July 20, 1969, with the Apollo 11 mission. Since then, people have landed on the moon six times, ending with the Apollo 17 flight on December 7, 1972. China, India, and Russia all have future plans for moon landings. The Russian-manned flight is scheduled to occur around 2030. NASA plans to land on the moon in the future, but has no reliable schedule for this event yet (there are rumors of sometime in 2024).

NASA does have plans for Mars. An actual human visit to Mars will likely have to wait until the 2030s (https://www.nasa.gov/topics/moon-to-mars/overview). As you might imagine, data science, AI, machine learning, and deep learning will figure prominently in any effort to reach Mars. Because of the distance and environment, people will require a lot of support to make a Mars landing feasible. In addition, getting back from Mars will be considerably harder than getting back from the moon. Even the lift-off will be harder because of the presence of some atmosphere and greater gravity on Mars.

In 1968, Arthur C. Clarke released the book 2001: A Space Odyssey. The book must have struck a chord, because it spawned a movie and a television series, not to mention three additional books. In 2001: A Space Odyssey, you find the Heuristically programmed ALgorithmic (HAL) 9000 computer that ends up running amok because of a conflict in its mission parameters. The main purpose of the computer was to help the space travelers complete their mission, but the implied purpose was to also keep the space travelers from going nuts from loneliness. Whatever hopes you have of seeing a HAL-like computer on any space flights are likely doomed to failure. For one thing, any AI programmed for space isn’t likely to purposely keep the crew in the dark about the mission parameters. Space flights will use an AI, no doubt about it, but it will be of a more practical and mundane construction than the HAL 9000.

Building Structures in Space

Just visiting space won’t be enough at some point. The reality of space travel is that everything is located so far from everything else that we need waypoints between destinations. Even with waypoints, space travel will require serious effort. However, the waypoints are important even today. Imagine that people actually do start mining the moon. Having a warehouse in near-Earth orbit will be a requirement because of the immense cost of getting mining equipment and other resources moved from the earth’s surface. Of course, the reverse trip also has to happen to get the mined resources and finished products from space to earth. People also want to take vacations in space, and scientists already rely on various structures to continue their investigations. The following sections discuss the use of various structures in different ways to help humanity move from planet Earth to the stars.

Taking your first space vacation

Companies have promised space vacations for some time now. Orbital Technologies made one of the first of these promises in 2011, which had an original expected date of 2016 (see https://tinyurl.com/rhxujxpc for details). The date has slipped a little to 2027 (https://tinyurl.com/ysvjmxdb). Even though you can’t take a space vacation yet, the video at https://tinyurl.com/5c6eaa73 tells you about the technology required to make such a vacation possible. Most of the concepts found in these sites are feasible, at least to some extent, but aren’t really around today. What you’re seeing is vaporware (a promised product that doesn’t actually exist yet but is probable enough to attract attention), but it’s interesting, anyway.

Blue Origin, the company founded by Jeff Bezos, actually does have a functional rocket and quarters (https://tinyurl.com/7ry9fej6). The rocket has made a number of trips to date without any passengers and at least one with Jeff Bezos aboard (https://tinyurl.com/jh5pphu4). This trip didn’t actually take people to space but rather into a near-Earth orbit of 100 kilometers. Companies such as Blue Origin (https://www.blueorigin.com/)and SpaceX (www.spacex.com) have the best chance right now of making a space vacation a reality. In fact, SpaceX is actually discussing plans for a vacation to Mars (http://www.spacex.com/mars).

Whatever the future holds, people will eventually end up in space for various reasons, including vacations. You should count on a cost as astronomical as your distance from earth. Space travel won’t be cheap for the foreseeable future. In any case, companies are working on space vacations now, but you can’t take one yet.

Performing scientific investigation

A lot of scientific investigation already occurs in space, all of which is currently aided by AI in some way. Everything from the International Space Station to the Hubbard Telescope depends heavily on AI (https://tinyurl.com/rvbe7hrt). Regarding the future, you can envision entire labs in space, or short-term hops into space to conduct experiments. Zero Gravity currently offers what it terms a parabolic vomit comet flight to perform near weightless experiments (https://www.gozerog.com/). The flight actually occurs in a plane that goes into a dive from high altitude. This trend is likely to continue, and at higher altitudes.

Industrializing space

Making space travel pay comes in several forms. Humans already enjoy considerable benefits from technologies developed for space flight and adopted for civilian use here on Earth. (Just one of many articles emphasizing the importance of space to life here on Earth is at https://tinyurl.com/zr2nmapn.) However, even with the technology transfers, space is still very expensive, and a better payback could occur by adapting what we know in other ways, such as by creating space factories (https://tinyurl.com/bexux4kr).

In fact, we may find that space factories provide the only way to produce certain materials and products (see https://tinyurl.com/87d2pt5t as an example). Having a zero-gravity environment affects how materials react and combine, which means that some of what’s impossible here on earth suddenly becomes quite possible in space. In addition, some processes are easily performed only in space, such as making a completely round ball bearing (https://tinyurl.com/bhapjsb).

Using space for storage

People will eventually store some items in space, and that makes sense. As space travel becomes more prevalent and humans begin industrializing space; the need to store items such as fuel and mined materials will increase. Because people won’t know where mined materials will see use (space factories will require materials, too), keeping the materials in space until a need for them occurs on Earth will actually be less expensive than storing them on Earth. The Orbit Fab space gas station (https://tinyurl.com/24hcypny) has already been launched. We may need it as part of our quest to visit Mars (https://tinyurl.com/28xhuzmj and https://tinyurl.com/kvfjhks2).

Although no current plans exist for the storage of hazardous materials in space, the future could also see humans storing such waste there, where it can’t pollute the planet. Of course, the question of why we’d store hazardous waste, rather than do something like incinerate it in the sun, comes to mind. For that matter, logical minds might question the need to keep producing hazardous waste at all. As long as humans exist, however, we’ll continue to produce hazardous waste. Storing such waste in space would give us a chance to find some means of recycling it into something useful, while keeping it out of the way.