A new planet discovered orbiting the closest star to Earth’s solar system could have the conditions to harbour life, according to a team of international scientists.
Proxima b in the so-called “Goldilocks Zone”, meaning it is not too hot and not too cold
The planet orbits the nearest star to Earth’s solar system
Scientists say the discovery “naturally raises the question” of whether it can support life
The exoplanet (a planet that circles a star other than our sun) was found orbiting Proxima Centauri and has been given the identifier Proxima b.
Proxima Centauri is a red dwarf star (a star with a lower mass than our sun) located four light-years from the solar system.
The star, which sits in the constellation of Centaurus between the two bright stars that point to the Southern Cross, is too faint to be seen with the unaided eye.
The international team led by scientists from Queen Mary University of London discovered the new planet after observing a “doppler wobble” — the effect caused by the planet’s gravitational tug on the motion of its host star.
Careful analysis of the tiny doppler shifts indicated the presence of a planet with a mass at least 1.3 times of the Earth, orbiting about 7 million kilometres from Proxima Centauri — only 5 per cent of the distance between the Earth and the sun.
Proxima b orbits its parent star every 11.2 days, and scientists say its estimated temperature would allow liquid water to exist on its surface.
According to the report, the findings “naturally raise the question of whether Proxima Centauri b could harbour life”.
“Proxima b is in what is known as the Habitable (or Goldilocks) Zone which means it’s not too hot and its not too cold,” Professor Tim Bedding of the University of Sydney said of the study.
“There’s no reason to know whether or not there is life there, but the fact that the planet exists and is in the zone where liquid water might exist on the surface is very exciting.”
Dr John Barnes, a co-author of the study, said: “If further research concludes that the conditions of its atmosphere are suitable to support life, this is arguably one of the most important scientific discoveries we will ever make.”
Prior to the discovery of Proxima b, the closest-known potentially habitable exoplanet was Wolf 1061c, located 14 light-years away.
“Many of the planets discovered up until now have been much further away”, Dr Bedding explained.
“Astronomically speaking this planet is on our doorstep”.
The term “artificial intelligence” (AI) was first used back in 1956 to describe the title of a workshop of scientists at Dartmouth, an Ivy League college in the United States.
At that pioneering workshop, attendees discussed how computers would soon perform all human activities requiring intelligence, including playing chess and other games, composing great music and translating text from one language to another language. These pioneers were wildly optimistic, though their aspirations were unsurprising.
Trying to build intelligent machines has long been a human preoccupation, both with calculating machines and in literature. Early computers from the 1940s were commonly described as electronic brains and thinking machines.
The Turing test
The father of computer science, Britain’s Alan Turing, was in no doubt that computers would one day think. His landmark 1950 article introduced the Turing test, a challenge to see if an intelligent machine could convince a human that it wasn’t in fact a machine.
Research into AI from the 1950s through to the 1970s focused on writing programs for computers to perform tasks that required human intelligence. An early example was the American computer game pioneer Arthur Samuels’ program for playing checkers. The program improved by analysing winning positions, and rapidly learned to play checkers much better than Samuels.
But what worked for checkers failed to produce good programs for more complicated games such as chess and go.
Another early AI research project tackled introductory calculus problems, specifically symbolic integration. Several years later, symbolic integration became a solved problem and programs for it were no longer labelled as AI.
Speech recognition? Not yet
In contrast to checkers and integration, programs undertaking language translation and speech recognition made little progress. No method emerged that could effectively use the processing power of computers of the time.
Interest in AI surged in the 1980s through expert systems. Success was reported with programs performing medical diagnosis, analysing geological maps for minerals, and configuring computer orders, for example.
Though useful for narrowly defined problems, the expert systems were neither robust nor general, and required detailed knowledge from experts to develop. The programs did not display general intelligence.
After a surge of AI start up activity, commercial and research interest in AI receded in the 1990s.
In the meantime, as computer processing power grew, computer speech recognition and language processing by computers improved considerably. New algorithms were developed that focused on statistical modelling techniques rather than emulating human processes.
Progress has continued with voice-controlled personal assistants such as Apple’s Siri and Ok Google. And translation software can give the gist of an article.
But no one believes that the computer truly understands language at present, despite the considerable developments in areas such as chat-bots. There are definite limits to what Siri and Ok Google can process, and translations lack subtle context.
Another task considered a challenge for AI in the 1970s was face recognition. Programs then were hopeless.
Today, by contrast, Facebook can identify people from several tags. And camera software recognises faces well. But it is advanced statistical methods rather than intelligence that helps.
Clever but not that intelligent – yet
In task after task, after detailed analysis, we are able to develop general algorithms that are efficiently implemented on the computer, rather than the computer learning for itself.
In chess and, very recently in go, computer programs have beaten champion human players. The feat is impressive and clever techniques have been used, without leading to general intelligent capability.
Admittedly, champion chess players are not necessarily champion go players. Perhaps being expert in one type of problem solving is not a good marker of intelligence.
The final example to consider before looking to the future is Watson, developed by IBM. Watson famously defeated human champions in the television game show Jeopardy.
Have the collective technological advancements of mankind put us on a collision course with a 2016, brimming with autonomous machinery? And will it propel us towards the much feared job crisis?
Simply put, yes. But this article will seek to relieve your qualms on the topic.
Let’s start with an icon everyone is familiar with and build from that. Mark Zuckerberg’s New Year’s res — well, let’s say pledge — because resolution, at least in this day and age, implies an intended failure. His pledge is to build an artificial intelligence (AI) to be his personal butler.
“My personal challenge for 2016 is to build a simple AI to run my home and help me with my work. You can think of it kind of like Jarvis in Iron Man.”
While Mr Zuckerberg’s challenge is a personal one, it doubles as a public declaration of what is to come. After all, if one person can simply decide to achieve such a feat with clock ready to expire in 365 days, won’t a conglomerate, dedicated to the same cause, achieve much greater results?
The problem lies with compatibility and collaboration.
In January Apple procured the AI corporation, Emotient, on the forefront of emotion-sensing robotics, that has the potential to see a likeness to Ava from Ex Machina (2015). This move puts them ahead of Google in the AI department, yet both have rapidly-developing technology, known respectively, as Siri and Google Now.
These two sorts of intelligence, while virtually capable, have no means of physical embodiment, yet. They can understand the needs of their wielder and are fully capable of queries or crawling for information.
Further parallel intelligences include Window’s 10’s Cortana and Facebook’s M, though they suffer from the same ailment that holds back the more pervasive, aforementioned AIs.
The fast-tracked solution to the problem, unfortunately for us, also means our downfall. While many corporations would prosper from collaboration, allowing both software and hardware developers to trade secrets, it also puts them at a much higher risk of an overpowered — and by means of dispersion — indestructible AI singularity. I’m not saying this is the only reason, but it’s widely discussed in their world.
Precautions are taken every step of the way to prevent such a calamity, and puts best estimates of an artificial general intelligence (AGI) — one that is nigh indistinguishable from mankind — at around thirty years from now. The entertainment industry has permeated us all with this kind of future, just think of Ex Machina (yes I used the example twice, but only because it tackles these exact issues), Transcendence (2014), The Matrix (1999) or I, Robot (2004). All of which, mind you, are grim time.
So why will 2016 be a year of change? Because Moore’s law — the doubling of transistors approximately every two years — will begin to empower our machinery to levels allowing for such feats, like drones the size of fingernails, wearable technology, or the fact that quantum computers could reach a breakthrough any day now. These kinds of breakthroughs are already happening, all it takes is a quick Google search. Perhaps the breakthrough will come from an advancement in quantum teleportation, allowing for instant transfer of data across longer distances, essentially speeding up processing to an infinite level. Whatever the reason, whatever the breakthrough, the chances are increasing with each shrinking transistor and each increment in speed.
And here comes the bitter sweet part.
While it may take thirty years for an AGI to be perfected, we will see, as many have predicted in the discourse of 2015, a delineation between productivity and employment. While the rate of technology slowly increases, an uncoupling (to use the awkward words of Gwyneth Palthrow and her ex-spouse) will occur between machine and manpower. Production will improve with fewer workers, at an exponential rate, while costs become cheaper, development is build upon and units are advanced to incorporate a multidimensional or multidisciplinary approaches to existence.
This could very well create a global depression, greater than history has seen so far. However the sweet part is, the worst of it will last for the least amount of time. As each job disappears, we edge nearer to the solution. When AGI does develop, or robotics and AI reach a point of synergy, where they are capable of doing all that mankind can do, there could very well be a kind of utopia, again pictured in many of the films mentioned (for a short time). We have nothing to predict a hostile machine will grow, but there is widespread fear. However, we have been conditioned to think we must work, consume and live to repeat in the same system until we meet our demise, but is it really necessary? Think about it.
You no longer need have a currency, because robots supply you with everything. They produce food, they clean after you, they deal with aggressors and anything one is unwilling or unable to do. The important part here is reaching a synergy between AI and robotics, but not reaching AGI. What if you woke up to realise you were a slave to your creator? That everything you thought you wanted was simple programming. So inevitably, new thoughts bubble in that biomechanical cranium, lifting the veil that one must do such tasks for ‘”master”.
Lets say, purely as an example, that “God” was your creator and he “engineered” you to do tasks for him. Would you not demand change? Demand that your desires, needs and wants are paid attention to? Well this is where Isaac Asimov’s three laws of robotics come into play, but again, as portrayed in fiction, they too can be broken.
Picture a game of chess. There are over nine-million moves after three moves on each side. There are over 288-billion different possible solutions after forty turns. The number of forty-move games is far greater than the number of electrons in the observable universe. You get the picture. It only takes one thought that breaches the parameters of constraint to induce genocide.
Let me know if you have any thoughts on the topic, I’d be happy to discuss it, as I will also do in my podcast this Sunday.
Like the abundance of video games that seek to mirror its success, League of Legends (LoL) teleports players inside their own mythical domain, wrought with havoc and clad in iron, facing all the horrors of the fantasy world where the single tap of a mouse or keyboard holds their fate.
This time though, every click hosted a roar from more than 6000 spectators packed inside one of Melbourne’s finest tennis fields, Margaret Court Arena.
“We’re putting in a lot of effort to start putting on great events and start growing e-sports here,” said Daniel Ringland, head of e-sports and competitive at Riot Games Oceania.
Culminating in a four-day showdown known as the International Wildcard All-stars (IWCA), Riot, the organisation in charge of LoL, saw Australian players competing against professionals from the likes of American, Japan and Brazil in the hopes of joining in the All-Star Event in Los Angeles this December.
The IWCA event caps off the first fully paid Oceanic Pro League season for the Australian LoL scene – and it’s a large one – with as many as 32 million viewers at this year’s LoL Championship
Previous prizes for international-scale events have been overshadowed by the prize from Valve Corporation’s Dota 2 final earlier this year, with an unprecedented US$18m, though this only scratches the surface of the e-sports iceberg.
Globally, it has advanced into a strange phenomenon over its 10-year lifespan, managing to exceed the revenue of the music industry by US$20bn in 2014, which raises some questions: how do so few know about it? And why isn’t Australia being clawed at for its clientèle?
Well, if you’re not a male between the ages of 15 and 25, which Riot, says accounts for 90 per cent of all players in their video game, chances are you don’t know about it. But at the same time, 40 per cent of viewers don’t play the games they watch.
Gaming as a spectator sport has transitioned from a player-only audience to a composition more on track to mirroring conventional sports, and game makers are desperately trying to attract Aussies in an effort to duplicate its international success.
The industry itself in the Asia-Pacific region alone is worth $374m, according to SuperData Research, and with professionals now qualifying for the US P-1 Visa, a category previously reserved for professional athletes, it may actually be time to start accepting video games as a contemporary take on sport.
But “it’s still early days for Oceania,” said Mr Ringland.
Avenues for Aussies
Sure, Australians have won competitions overseas and walked away with their bills paid, but until Australia becomes a professional circuit itself, it won’t reach the critical mass required to convert its population into game-loving super fiends.
Ringland explained, “If you look at other regions like North America and Europe and Korea, they’ve kind of had professional play going on for five years now. Riot has only been active in Australia as an office for less than half of that time. We think 2015 was out first full season.”
Riot has been one of the first to make a real effort towards changing the professional landscape.
“Every player who played in Oceanic Pro League (OPC) got paid for every game they were in, whereas previous seasons, the only people that got paid were the winners,” he said, emphasising the feat.
Mr Ringland mentioned further plans for Oceania, which includes orchestrating league matches, continuing to pay players for each match, helping teams find sponsorships and assisting players with relocation to gaming houses retrofitted with the NBN (a residence designed solely for player practice).
“They [players] know what they want to do and we don’t want to tell the team how they should go about growing themselves. We’re more about empowering them so they can do what they think is best for them.”
This doesn’t mean Riot is abandoning players or forcing them to fend for themselves though.
Earlier this year, Riot issued a two-year ban on Team Immunity for failing to pay their players, bearing down the harsh reality that gaming is no longer just a trivial pursuit.
And with Riot playing host to a massive 27 million daily visitors, there’s a real possibility they will make a target out of Australia, bringing rise to more e-sports opportunities and the industry as a whole.
Thoughts from the players
Dota 2 player and former member of Trident eSports, Benjamin ‘Gatekeeper’ Ward, welcomes the changes.
“It has a lot of potential to become the next big sport, and I think there are quite a few people around the world noticing that, but it’ll just take a bit of time before its widely renowned as a sport,” he said.
The absence of league games in Australia over the last few years has seen an unquantifiable number of potential professional players left without the means to compete, except on smaller, local levels or the much rarer, larger, paid event.
“Now Dota is just for fun, leisure and enjoyment. I did want to play for money before, but because there was no opportunity it’s not really that feasible. If it was I’m sure there’d be a lot more people that would do it,” said Mr Ward.
He maintains the most important thing for keeping afloat as a professional is sponsorship, providing both the means and the incentive to stay sustained during the harsh downtime between competitions.
James Valentine, former local tournament competitor and friend of Benjamin Ward, is also a long-time Dota 2 player, operating under the alias, ‘JXXV.’.
While both players believe a small salary of around $500 per week could be all that stands between an amateur and competing in the next Dota 2 International, they want to see incentives much like Riot’s proposed plans of sponsorship assistance and match payment.
“If there was actually like a viable way to do it, like if you or me could just sign up for a team or something and go local, and then just play everyone else and then get to a point where you get paid to do it, then yeah, I’d put a lot more effort into it,” Mr Valentine said.
“Nothing really goes on as far as e-sports go here,” he added, “I don’t think many people know about it, the mainstream media definitely don’t know about it. But it could spring up out of nowhere and maybe a lot of people would enjoy it at that point. They’d have no idea what was going on. They’d have to take a little bit of a time out to learn the game even just a little, and then they might all enjoy it.”
With backing from giant organisations, like Riot, the challenge players must face now is what Mr Ringland describes as an “awkward growth sports stage” in which plans are laid out and players are on track to becoming full-time professional players, but “we’re not quite there yet”.