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2 minute readNovember 28, 20226:48 AM UTCLast Updated ago China set to launch Shenzhou-15 spacecraft to its space station on Tuesday Reuters

[1/2] Astronauts Fei Junlong, Deng Qingming and Zhang Lu attend a news conference before the Shenzhou-15 spaceflight mission to build China's space station, at Jiuquan Satellite Launch Center, near Jiuquan, Gansu province, China November 28, 2022. cnsphoto via REUTERS

BEIJING, Nov 28 (Reuters) - China will launch the Shenzhou-15 spacecraft to its space station at 11:08 p.m. (1508 GMT) on Nov. 29, the China Manned Space Agency said on Monday, the final mission in the country's plan to complete the crewed orbital outpost.

Onboard will be three male astronauts: Fei Junlong, Deng Qingming and Zhang Lu, the agency said at a news conference.

The space station will be handed over to them within a week by the three astronauts who arrived in early June.

"During the stay, the Shenzhou-15 crew will welcome the visiting Tianzhou-6 cargo ship and hand over the Shenzhou-16 manned spaceship, and are planning to return to China's Dongfeng landing site in May next year," said Ji Qiming, a spokesperson at the agency.

"Currently, the space station combination is in stable status with all equipment functioning well, and ready for the rendezvous, docking and the crew handover," Ji added.

In April 2021, China began construction of the three-module space station with the launch of the Tianhe module, the main living quarters for astronauts.

In July and November it launched the remaining two laboratory modules, Wentian and Mengtian, where scientific experiments will be performed.

The completion of the space station, designed for a lifespan of at least 10 years, will be a milestone in China's ambitions in low-earth orbit, with NASA's aging ISS potentially ceasing operations by the end of the decade.

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The researchers claim that their approach could be used to train AI to carry out other tasks. To begin with, it could be used to for bots that use a keyboard and mouse to navigate websites, book flights or buy groceries online. But in theory it could be used to train robots to carry out physical, real-world tasks by copying first-person video of people doing those things. “It’s plausible,” says Stone.

Matthew Gudzial at the University of Alberta, Canada, who has used videos to teach AI the rules of games like Super Mario Bros, does not think it will happen any time soon, however. Actions in games like Minecraft and Super Mario Bros. are performed by pressing buttons. Actions in the physical world are far more complicated and harder for a machine to learn. "It unlocks a whole mess of new research problems," says Gudzial.

“This work is another testament to the power of scaling up models and training on massive datasets to get good performance,” says Natasha Jaques, who works on multi-agent reinforcement learning at Google and the University of California, Berkeley.

Large internet-sized data sets will certainly unlock new capabilities for AI, says Jaques. “We've seen that over and over again, and it's a great approach.” But OpenAI places a lot of faith in the power of large data sets alone, she says: “Personally, I'm a little more skeptical that data can solve any problem.”

Still, Baker and his colleagues think that collecting more than a million hours of Minecraft videos will make their AI even better. It’s probably the best Minecraft-playing bot yet, says Baker: “But with more data and bigger models I would expect it to feel like you're watching a human playing the game, as opposed to a baby AI trying to mimic a human.”

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“Video is a training resource with a lot of potential,” says Peter Stone, executive director of Sony AI America, who has previously worked on imitation learning.

Imitation learning is an alternative to reinforcement learning, in which a neural network learns to perform a task from scratch via trial and error. This is the technique behind many of the biggest AI breakthroughs in the last few years. It has been used to train models that can beat humans at games, control a fusion reactor, and discover a faster way to do fundamental math.

The problem is that reinforcement learning works best for tasks that have a clear goal, where random actions can lead to accidental success. Reinforcement learning algorithms reward those accidental successes to make them more likely to happen again.

But Minecraft is a game with no clear goal. Players are free to do what they like, wandering a computer-generated world, mining different materials and combining them to make different objects.

Minecraft’s open-endedness makes it a good environment for training AI. Baker was one of the researchers behind Hide & Seek, a project in which bots were let loose in a virtual playground where they used reinforcement learning to figure out how to cooperate and use tools to win simple games. But the bots soon outgrew their surroundings. “The agents kind of took over the universe, there was nothing else for them to do” says Baker. “We wanted to expand it and we thought Minecraft was a great domain to work in.”

They’re not alone. Minecraft is becoming an important testbed for new AI techniques. MineDojo, a Minecraft environment with dozens of predesigned challenges, won an award at this year’s NeurIPS, one of the biggest AI conferences.

Using VPT, OpenAI’s bot was able to carry out tasks that would have been impossible using reinforcement learning alone, such as crafting planks and turning them into a table, which involves around 970 consecutive actions. Even so, they found that the best results came from using imitation learning and reinforcement learning together. Taking a bot trained with VPT and fine-tuning it with reinforcement learning allowed it to carry out tasks involving more than 20,000 consecutive actions.

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Online videos are a vast and untapped source of training data—and OpenAI says it has a new way to use it.

OpenAI has built the best Minecraft-playing bot yet by making it watch 70,000 hours of video of people playing the popular computer game. It showcases a powerful new technique that could be used to train machines to carry out a wide range of tasks by binging on sites like YouTube, a vast and untapped source of training data.

The Minecraft AI learned to perform complicated sequences of keyboard and mouse clicks to complete tasks in the game, such as chopping down trees and crafting tools. It’s the first bot that can craft so-called diamond tools, a task that typically takes good human players 20 minutes of high-speed clicking—or around 24,000 actions.

The result is a breakthrough for a technique known as imitation learning, in which neural networks are trained how to perform tasks by watching humans do them. Imitation learning can be used to train AI to control robot arms, drive cars or navigate webpages.

There is a vast amount of video online showing people doing different tasks. By tapping into this resource, the researchers hope to do for imitation learning what GPT-3 did for large language models. “In the last few years we’ve seen the rise of this GPT-3 paradigm where we see amazing capabilities come from big models trained on enormous swathes of the internet,” says Bowen Baker at OpenAI, one of the team behind the new Minecraft bot. “A large part of that is because we’re modeling what humans do when they go online.”

The problem with existing approaches to imitation learning is that video demonstrations need to be labeled at each step: doing this action makes this happen, doing that action makes that happen, and so on. Annotating by hand in this way is a lot of work, and so such datasets tend to be small. Baker and his colleagues wanted to find a way to turn the millions of videos that are available online into a new dataset.

The team’s approach, called Video Pre-Training (VPT), gets around the bottleneck in imitation learning by training another neural network to label videos automatically. They first hired crowdworkers to play Minecraft, and recorded their keyboard and mouse clicks alongside the video from their screens. This gave the researchers 2000 hours of annotated Minecraft play, which they used to train a model to match actions to onscreen outcome. Clicking a mouse button in a certain situation makes the character swing its axe, for example.

The next step was to use this model to generate action labels for 70,000 hours of unlabelled video taken from the internet and then train the Minecraft bot on this larger dataset.

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If SEI’s project, dubbed CASSIOPeiA, goes ahead, a cost modelling analysis by consultancy Frazer-Nash shows that the LCOE (levelised cost of electricity), used to compare different methods of electricity generation on a consistent basis, falls between £37 and £74/MWh, which is competitive with terrestrial renewable technologies, the organisation said.

Where the technology benefits greatly, is its availability. Compared with solar panels on the ground which are usually able to process 15–22% of solar energy into usable energy as conditions are never perfect, a solar power satellite in GEO can see the Sun for well over 99% of the time.

The idea of solar farms in space could get another big boost as ministers at the European Space Agency are meeting this week to discuss whether to fund a three-year preparatory programme known as SOLARIS. If approved, ESA said it would work in conjunction with European industry, to assess the feasibility, benefits, implementation options, commercial opportunities and risks of SBSP as a contributor to terrestrial energy decarbonisation. A decision whether to proceed with a full-blown project could then be made in 2025.

"The idea of space-based solar power is no longer science fiction," Sanjay Vijendran, SOLARIS’ lead scientist told the BBC.

"The potential is there and we now need to really understand the technological path before a decision can be made to go ahead with trying to build something in space."

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A PLAN to use satellites in Earth’s orbit to harvest the Sun’s energy from space and beam it down to Earth using microwaves could be up and running as early as 2030, with the first-of-a-kind operational system delivering power into the grid by 2040.

The concept of harvesting solar energy in space is not a new one, but until now, high launch costs and limited technology have hampered progress, said Space Energy Initiative (SEI), the organisation behind the solar farm project.

However, recent developments in reusable rockets, and more modular SPS concepts, coupled with benefits that include clean, continuous base-load energy day and night, through all seasons and weather, and with much lower land usage than conventional renewables, is helping the idea gain traction. And with the potential of each satellite to beam around 2.9 GW of net power to a receiving antenna at a fixed point on Earth, it’s a concept that has even attracted the attention of the the UK Government. In July ministers announced that £3m (US$3.6m) in funding would be allocated to space-based solar power (SBSP) projects after confirming the engineering feasibility of the concept through an independent study.

But, to harvest energy comparable in power output to a nuclear power station takes a satellite that is incredibly large. According to SEI a typical system comprises a constellation of massive, kilometre-scale satellites 38,000 km above the ground in a geostationary orbit. At this range the massive satellites should not cause any problems with light pollution, SEI said.

Each has very lightweight solar panels and a system of mirrors to concentrate sunlight onto the panels, generating around 3.4 GW of electricity on the satellite. This is converted into RF microwave radiation, with an efficiency of 85%.

To allow the microwave beam to lock onto the correct point, an encrypted pilot beam is transmitted from the ground to the satellite. The maximum beam intensity is <250 W/m2, less than a quarter of the maximum sun intensity at the equator, and the system will be designed so that it is safe in the event that humans or birds or animals strayed into the beam, said SEI.

The ground rectifying antenna or “rectenna” as it is called then converts the electromagnetic energy into direct current electricity which passes through an inverter which delivers a net 2 GW of AC power into the grid.

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The Meta team’s crucial contribution was therefore to augment reinforcement learning with natural-language processing. Large language models, trained on vast amounts of data to predict deleted words, have an uncanny ability to mimic the patterns of real language and say things that humans might. For Cicero, the team started with a pre-trained model with a baseline understanding of language, and fine-tuned this on dialogues from more than 40,000 past games, to teach it Diplomacy-specific patterns of speech.

To play the game, Cicero looks at the board, remembers past moves and makes an educated guess as to what everyone else will want to do next. Then it tries to work out what makes sense for its own move, by choosing different goals, simulating what might happen, and also simulating how all the other players will react to that.

Once it has come up with a move, it must work out what words to say to the others. To that end, the language model spits out possible messages, throws away the bad ideas and anything that is actual gobbledygook, and chooses the ones, appropriate to the recipients concerned, that its experience and algorithms suggest will most persuasively further its agenda.

Cicero, then, can negotiate, convince, co-operate and compete. Seasoned Diplomacy players will, though, want to know something else: has it learned how to stab? Stabbing—saying one thing and doing another (especially, attacking a current ally) is seen by many as Diplomacy’s defining feature. But, though Cicero did, “strategically withhold information from players in gameplay”, it did not actually stab any of its opponents. Perhaps it was this final lack of Machiavellian ruthlessness which explains why it was only in the top 10%, and not victor ludorum.

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This time it is one that involves negotiation and double-dealing

Backgammon was an easy win. Chess, harder. Go, harder still. But for some aficionados it is only now that artificial intelligence (ai) can truly say it has joined the game-playing club—for it has proved it can routinely beat humans at Diplomacy.

For those unfamiliar with the game, its board is a map of Europe just before the first world war (except that, for no readily apparent reason, Montenegro is missing). Participants, seven ideally, each take on the role of one of the Great Powers: Austria-Hungary, Britain, France, Germany, Italy, Russia and Turkey. Each has armies and navies, and geographically based resources to support them, and can use its forces to capture the territory of neighbours, thus gaining the means to raise more forces while depriving others of the same.

The trick is that, at least at the beginning, players will get nowhere without making agreements to collaborate—yet they are not bound by the game’s rules to keep to these agreements. Only when orders for the movement of troops and vessels, which have to be written down, are revealed, does a player discover who really is a friend, or an enemy.

Cicero, a program devised by a group of Mark Zuckerberg’s employees who dub themselves the Meta Fundamental ai Research Diplomacy Team, proved an adept pupil. As the team describe in Science, when they entered their creation into an online Diplomacy league, in which it played 40 games, it emerged as one of the top 10% of players—and no one rumbled that it was not human.

In all past ai game-playing projects the program has learned by reinforcement. Playing repeatedly against itself or another version of itself, it acts first at random, then more selectively. Eventually, it learns how to achieve the desired goal. Cicero was taught this way, too. But that was only part of its training. Besides having the reasoning to plan a winning strategy, a successful Diplomacy player must also possess the communicative ability to implement it.

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In the 1990s, Dr. John Hunter led what was known as Super HARP, which was a methane-and-hydrogen powered ballistic launch system that achieved exit velocities of 6,700 mph (10,800 kph). Rival startup Green Launch asserts that laboratory-based hydrogen systems have achieved exit velocities of 25,000 mph (39,600 kph) and that a full-scale projectile speed of 9,000 mph (14,400 kph) is accessible. In fact, a December 2021 test achieved exit velocities of 4,400 mph (7,200 kph): nearly matching SpinLaunch’s desired full-scale goals. While SpinLaunch will require at least two extra stages to reach space, Green Launch aims to reach the Kármán line that defines the start of space, 100 kilometers (62 miles) up, from the projectile launch alone.

There’s no doubt that there’s a lot of truth to the old saying that “fortune favors the bold,” and SpinLaunch is certainly a bold idea. However, the laws of physics pose numerous obstacles for those who would build high-powered, rapidly moving large-scale apparatuses with moving parts. In the 1990s, the Department of Energy attempted to build enormous centrifuges for accelerating large objects, but they always began to break down at speeds of ~3,100 mph (5,000 kph): about 60% of the speeds that SpinLaunch aims to achieve. The challenges before the team aiming to reach their stated goals are enormous.

That isn’t to say that SpinLaunch is impossible or that its concepts violate the laws of physics; they do not. However, there’s a very big distinction between what’s physically possible and what’s physically practical. It’s not clear that, with three times the diameter of the current prototype, the desired launch parameters can be met. Even if they are, it remains to be seen if the later-stages required to take the launched payloads to orbit can operate after experiencing the extreme SpinLaunch spin-up and launch and drag conditions. It’s important to explore a variety of options in the quest to reach space, but scaling up a prototype is rarely as easy as one might initially think.

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Can the launch vehicle/payload survive this set of conditions and remain fully operational and undamaged? It’s possible, but it’s never been done before. Again, this is an unprecedented obstacle that must be overcome.

Problem #4: The atmospheric drag force experienced by the payload will be tremendous.

If you hold your hand out of a car window when you’re traveling at 100 kph (62 mph), how much of a drag force will it experience relative to traveling at half that speed: 50 kph (31 mph)? The answer isn’t twice as much force, as one might expect, but rather four times as much force. The drag force you experience is proportional to the cross-sectional area of the object (your hand, in this case) but also to the velocity you’re moving at squared.

Normally, rockets start out moving slowly near Earth’s surface — where the atmosphere is thickest — and pick up speed as they continue accelerating up through the atmosphere. The highest speeds are achieved at the highest altitudes: where the air is thinnest.

Not so with SpinLaunch; in fact, the reverse is true. The payload will be moving at its fastest where the atmosphere is the thickest, which maximizes speed and energy losses due to drag. This will also heat up the payload substantially, and in ways that no payload that’s ever made it to space before has experienced. The biggest problem with Project HARP, back when it was being run, is that there was no payload that could be launched that would be capable, at its high altitude, of taking it the rest of the way to space. Can SpinLaunch overcome that problem? It remains to be demonstrated.

Problem #5: Gun-based ballistic launchers can achieve much greater exit speeds than SpinLaunch.

Although it’s a brilliant idea to try and cut out the first stage of a rocket, which after all is where the greatest fuel expenditures come from, SpinLaunch’s goals are impressive. With a launch speed of 5,000 mph (8,100 kph), it will certainly reach high altitudes on its own.

But why pioneer a technology that requires a large amount of expense, infrastructure, and moving parts — as well as requiring your payload to endure tens of thousands of gs for tens of minutes — when you can just scale up what we’ve already learned from Project HARP?

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At its full-scale size and with a desired exit speed of 5,000 mph (8,100 kph), that translates into a peak centripetal acceleration, just before the payload is launched, of somewhere between 50,000 and 100,000 gs, where one g is the acceleration due to gravity at Earth’s surface. The payload must ramp up to this peak acceleration over long periods of time — something like ~30 minutes — and survive it with all systems intact, including the on-board rocket system, in order to reach orbit. This represents a peak acceleration that’s eight times what the current prototype experiences.

Such conditions have never been met to date; this is a tremendous obstacle to be overcome.

Problem #2: Traditional liquid-based rocket fuel cannot be used.

It’s always preferable to build upon already-existing technologies than it is to have to invent something entirely new, and yet the latter is very much what’s in store for a SpinLaunch payload. The reason is simple: if you have a liquid-based fuel on board, you need a plumbing system to contain and control it; this is exactly the type of system that will not survive the spin-up accelerations that SpinLaunch requires.

This means that solid rocket fuel will need to be used instead: something with the hardness and durability of something like formica. In principle, this can be done, but it represents a substantial obstacle toward reaching space.

While solid-propellant rockets offer a number of advantages over liquid-propellant ones, those advantages include stability, durability, and reliability. Unfortunately, however, they have lowered efficiencies and are less controllable than liquid propellant alternatives, which is why solid-fuel rockets are primarily used in military armaments but liquid-fuel rockets are typically used for spaceflight. Even if this difficulty can be overcome, the limitations of solid-fuel applications will inherently limit the mass of the payloads that can be delivered with SpinLaunch.

Problem #3: Piercing the mylar sheet preserving SpinLaunch’s vacuum could destroy the payload.

Do you remember the unfortunate and tragic Space Shuttle Columbia disaster? When Columbia attempted atmospheric re-entry, the spacecraft catastrophically broke apart, killing all astronauts on board. The reason the shuttle disintegrated in the atmosphere, however, was simply a small, lightweight piece of foam insulation that struck a portion of the craft at very high speeds. That’s a key concept in physics: the amount of kinetic energy that something possesses — and hence, the amount of damage it can cause in a collision — is proportional to its mass, but proportional to its speed squared.

With an exit velocity of 5,000 miles-per-hour as opposed to the 1,000 miles-per-hour of the current prototype, that means:

  • the launch vehicle will strike the mylar sheet with 25 times the kinetic energy of current tests,

  • the mylar sheet will impart 25 times the amount of energy as current tests to the payload,

  • and the transition from the payload traveling through vacuum to traveling through Earth’s atmosphere means “hitting a wall” of atmosphere that the payload will strike with 25 times the amount of force that the current prototype experiences.

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It’s very likely that Project HARP served as the inspiration for what SpinLaunch is attempting to do today.

The idea of SpinLaunch is both devilishly simple and incredibly complex. Instead of using a gun-based launch like Project HARP did, SpinLaunch will build a large circular accelerator, kind of like a centrifuge. On one end, a payload inside an aerodynamic craft is prepared; on the other end, a counterweight balances it out. The air inside is evacuated, creating a vacuum. And then, the spin-up begins. With each revolution inside the SpinLaunch mechanism, the payload and counterweight speed up, increasing their angular velocity over and over.

Once a critical speed is reached, the payload detaches from the rest of the apparatus and is launched straight upward, where it penetrates a thin but airtight sheath, entering Earth’s atmosphere. The goal isn’t to go all the way up into space, but rather “only” to extremely high altitudes, not only above Earth’s troposphere and into the stratosphere, but even above the stratosphere and all the way into the mesosphere. Only then will a booster rocket kick in and take the payload the rest of the way into space, saving an enormous amount of fuel costs and launch costs overall. Ideally, SpinLaunch will be capable of launching many payloads each day, at a fraction of the cost of even reusable rocket launches.

So far, SpinLaunch has built two prototypes, the largest of which is a third the diameter of the desired final version. Already, this prototype has successfully launched test payloads:

  • that have successfully detached at the right moment,

  • that have successfully pierced a mylar membrane maintaining the vacuum, at exit speeds of approximately 1,000 mph (1600 kph),

  • where the payload has then reached heights of ~30,000 feet, or nearly 10 kilometers.

This is remarkable and impressive, but not necessarily impressive enough. In order to successfully enter low-Earth orbit, a spacecraft needs to reach altitudes of around 300 kilometers (186 miles) with orbital speeds of 25,000 kph (16,000 mph), which implies much greater speeds and heights than SpinLaunch has been able to reach. To get there, the plan is to have the full-scale SpinLaunch system achieve exit speeds of 5,000 mph (8,100 kph), and to then have a working late-stage rocket activate to take the payload the rest of the way into orbit once it reaches a height of ~60 kilometers.

Will SpinLaunch be a feasible concept when it’s scaled up to its desired design? That all depends on whether the following physical problems can be overcome.

Problem #1: Can the payload survive spin-up?

This is not a trivial problem. Whenever you accelerate an object to move in a circle, it experiences not only the “spin-up” force that causes its angular speed to increase, but also a centripetal force — a force toward the center of the circle — that prevents the object from either crashing into the side of the accelerator or from flying off in a straight line prematurely. That centripetal force is dependent on three factors:

  • the mass of the payload,

  • the speed of the object,

  • and the size (radius) of the circle.

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SpinLaunch will cleverly attempt to reach space with minimal rocket fuel. But will physics prevent a full-scale version from succeeding?

  • Although humanity has succeeded in sending spacecraft into orbit and even beyond Earth's gravitational pull, the only way we've done so is via fuel-devouring rocket launches.

  • In the past, alternatives have been proposed: railguns, projectile launches, space elevators, and more, but none have ever delivered a single payload into orbit.

  • With a working prototype successfully launching objects at 1,000 miles-per-hour, SpinLaunch looks promising. But will the laws of physics stand in the way of a full-scale version?

It’s long been the dream of humanity to escape the bonds of Earth’s gravitational pull, paving the way for us to explore the vast reaches of space that lie beyond our world. Beginning in the 20th century, we started to achieve this dream by leveraging the power of rocket technology, where we’d burn fuel to provide a large and constant acceleration to a payload, eventually taking it above Earth’s atmosphere and either into orbit around our planet or — more ambitiously — to escape from our planet’s gravity entirely.

However, rocket launches, even when the launch vehicle is salvageable and reusable, are tremendously resource-intensive, expensive, and environmentally unfriendly. Since the mid-20th century, numerous alternative technologies have been proposed to send objects to space, but none have yet achieved that goal as of 2022. One company aims to change that in the coming few years: SpinLaunch. Ideally, they’ll build a full-scale version of their modestly-sized working prototype to spin objects up to speeds of 5,000 miles-per-hour (8,100 kph) and launch them upward, where a small booster will take them all the way into space. It’s an ambitious goal, but the laws of physics might be standing in the way. Here’s why.

A few ideas have been offered as alternatives to rocket launches over time.

  • A railgun, for instance, would electromagnetically accelerate a projectile along a track until the projectile reached the end, where it could potentially reach space with a large enough exit velocity.

  • A space elevator, alternatively, would lift an object intended for orbit all the way up above Earth’s atmosphere, relying on solid-enough infrastructure to carry a payload without a launch vehicle.

  • Or a ballistic solution, where an object is simply fired at high velocity upward through the atmosphere, could take an object most of the way or even completely into space.

That last option, through the 1950s and 1960s, gave rise to Project HARP: the High Altitude Research Project, which once sent a gun-fired projectile up to the highest altitude ever achieved by that means, to 180 kilometers (110 miles) above the surface of the Earth. However, a combination of factors — including the trauma experienced by the payload during its initial firing — prevented a late-stage rocket booster from functioning as part of the payload, prohibiting it from reaching orbit or from escaping Earth’s gravity.

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But there is debate in the scientific community around whether the microwave beams will damage communications, human health or the environment.

Yang said the Chinese space station would get involved in a number of critical experiments to bring the space power plant from science fiction to reality. Some external portals on the station were designed to have high-powered electrical equipment plugged in, he said.

However, the generation of a strong electric current and conversion to microwaves will produce excessive heat and many other problems, which are not easy to solve in the space environment.

The space station is an ideal platform for China to evaluate the long-term performance of the new technology and equipment in orbit, Yang said.

The Chinese space scientists also plan to use cargo ships – which are usually left to burn in the atmosphere after a mission – as a basic component to build the solar power plant. Using several robotic arms, Tiangong could join up a number of cargo ships and some extra solar panel units to create a prototype power plant.

This mini power plant, after rising to an orbit 100km above the space station with ion thrusters for safety, would conduct experiments to verify technologies for the full-scale plant, including microwave energy transmission and powering up an allied satellite with a high-energy laser beam, according to a slide show Yang presented to the conference.

China plans to conduct the first space-to-Earth energy transmission experiment over the next few years. A small space power plant that can supply electricity to remote military outposts will be up and running by the 2030s, while commercial power generation is expected to start in the 2050s.

The US Air Force also plans to launch a solar-powered satellite in 2025 that will be capable of producing and sending focused microwave beams from near-Earth orbit.

Some studies have suggested that the microwaves – mostly in the same frequency range as those used by a Wi-fi router – will be safe for humans unless a person stepped into a receiving area.

But how to keep the energy beam aimed at a precise spot on Earth over a distance of tens of thousands of kilometres remains a major challenge, according to scientists involved in these projects.

Some researchers also warned that persistent, intense energy transmission between space and Earth could cause disturbances in the ionosphere that could lead to unexpected impacts on the Earth’s environment.

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  • Tiangong expected to play a key role in China’s space solar power station project by providing a testing platform for high-voltage electric devices

  • Space power station could point beam to almost any location, making it an ideal to power military equipment or remote outposts, says project team

China’s space station will join a controversial project to collect solar power from space and send it to Earth in a high-energy microwave beam, according to a senior scientist.

The Chinese space station Tiangong – which means “heavenly palace” – became fully operational when the last major service module, Mengtian, docked this month.

Some space scientists have suggested Tiangong – the largest infrastructure in orbit owned and run exclusively by a single country at present – can change the pace or direction of the space race.

Yang Hong, chief designer of the space station, told a conference in Wenchang, Hainan, on Tuesday that Tiangong would play a key role in China’s space solar power station (SSPS) project by providing a testing platform for high-voltage electric devices and in helping assemble ultra-large structures.

In a lecture at the conference attended by space scientists and engineers from around the world, Yang said the space station had the resources and capability to do demonstrations, “verify key technologies, accelerate technological breakthroughs and accumulate in-orbit experimental data” for the SSPS project.

He said these would help China meet its peak carbon and carbon neutral goals.

A paper published by the project team in the journal Chinese Space Science and Technology in June reported that the full-sized Chinese space solar power plant would be a 1km-wide structure beaming gigawatt-power microwaves to Earth from a distance of 36,000km (22,4000 miles).

Unlike traditional solar farms that work only during the day, the space-based solar array would collect and transmit energy 24 hours a day, it said.

The microwave beams could penetrate clouds and be picked up by an antenna on the ground to generate electricity.

Operating in the geostationary orbit, the space power station could direct the beam to almost any location, making it an ideal candidate to power military equipment or remote outposts, the team said. However, some researchers have also speculated that the beam could be used as a weapon.

The European Union and many countries, including Japan, Britain and the United States, have launched research programmes to develop similar technologies.

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Programmers have, of course, always studied, learned from, and copied each other's code. But not everyone is sure it is fair for AI to do the same, especially if AI can then churn out tons of valuable code itself, without respecting the source material’s license requirements. “As a technologist, I'm a huge fan of AI ,” Butterick says. “I'm looking forward to all the possibilities of these tools. But they have to be fair to everybody.”

Thomas Dohmke, the CEO of GitHub, says that Copilot now comes with a feature designed to prevent copying from existing code. “When you enable this, and the suggestion that Copilot would make matches code published on GitHub—not even looking at the license—it will not make that suggestion,” he says

Whether this provides enough legal protection remains to be seen, and the coming legal case may have broader implications. “Assuming it doesn’t settle, it’s definitely going to be a landmark case,” says Luis Villa, a coder turned lawyer who specializes in cases related to open source.

Villa, who knows GitHub cofounder Nat Friedman personally, does not believe it is clear that tools like Copilot go against the ethos of open source and free software. “The free software movement in the ’80s and ’90s talked a lot about reducing the power of copyrights in order to increase people’s ability to code,” he says. “I find it a little bit frustrating that we're now in a position where some people are running around saying we need maximum copyright in order to protect these communities.”

Whatever the outcome of the Copilot case, Villa says it could shape the destiny of other areas of generative AI. If the outcome of the Copilot case hinges on how similar AI-generated code is to its training material, there could be implications for systems that reproduce images or music that matches the style of material in their training data.

Anil Dash, the CEO of Glitch and a board member of the Electronic Frontier Foundation, says that the legal debate is just one part of a bigger adjustment set in train by generative AI. “When people see AI creating art, creating writing, and creating code, they think ‘What is all this, what does it mean to my business, and what does it mean to society?’” he says. “I don't think every organization has thought deeply about it, and I think that's sort of the next frontier.” As more people begin to ponder and experiment with generative AI, there will probably be more lawsuits too.

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