The April 4, 2017 chemical attack on the rebel-held town of Khan Sheikhoun in Syria led to at least 70 deaths and more than 100 people requiring medical attention, prompting an outcry from the international community. It led to the April 7 US bombing of the Shayrat air base.

It is alleged that sarin was used in the Khan Sheikhoun attack. This particular chemical became famous in 1995 with the Tokyo subway attack, launched by members of the cult movement Aum Shinrikyo.

Was it sarin?

Sarin is an organophosphorus compound and was first synthesised in 1938 in Germany as part of a pesticide research program.

Sarin is a moderately volatile substance – that is, it readily forms a gas – which can be taken up by inhalation or skin contact. It is an inhibitor of the enzyme acetylcholinesterase, which is critical in regulating nerve function.

When exposed to a low dose of a nerve agent such as sarin, people experience increased production of saliva, a running nose and a feeling of pressure on the chest. The pupils of the eye becomes contracted, so-called “pin-point” pupils.

Pin point pupils, which have been recorded in video footage of the Khan Sheikhoun attack, are a characteristic consequence of acetylcholinesterase inhibitors like sarin. This clinical sign is quite different from the irritating effects of chlorine and mustard gas.

Medium to higher dose exposure to sarin and other nerve agents can result in difficulty in breathing and coughing, abdominal cramps and vomiting, and sometimes involuntary discharge of urine and faeces. Increased saliva production, running eyes and sweating may occur, as well as muscular weakness, tremors or convulsions. Loss of consciousness, and death due to respiratory failure may be seen at higher doses.

Survivors of the Tokyo subway sarin attack recovered reasonably well but experienced some clinically detectable neurological effects, and some evidence of brain changes.

Although sarin use is suspected in Khan Sheikhoun, there are many organophosphorus insecticides that would exert the same effect (in sufficient quantity). It is possible that an organophosphate pesticide or a simple organophosphate (not normally classified as a chemical weapon) was used in this attack.

The production of sarin requires special facilities and is expensive, perhaps running into the tens of millions of dollars. Similar chemicals, such as tabun, are less expensive to make.

Will we ever know what was used?

In order to establish the identity of the substances used in Khan Sheikhoun, a combination of information needs to be gathered and assessed. In particular the results of chemical tests on wipe samples, soil and clothing samples must be determined and verified.

The Organisation for the Prohibition of Chemical Weapons (OPCW) Fact Finding Team would be the most authoritative source to reveal the nature of the chemical(s) used, and we will await their report. However, in the past these reports have been inconclusive owing to the time taken to gather chemical samples, limits of detection, specificity and the presence of mixtures.

The conflict in Syria involves the government military forces, the rebels, ISIS and the Kurds. It is sometimes hard to know where the chemicals might be coming from (for example, from neighbouring countries), or whether they have been produced or sourced locally.

Local history of chemical attacks

This experience in Syria may lead to improved medical responses in the case of future attacks. But in the absence of detailed knowledge of the substances involved, the treatment of casualties is unlikely to be optimal.

With so many individual chemical substances, and improvised mixtures, only generic decontamination and treatment procedures can be used. However, it may be feasible to have chemical specialists attached to hospitals collecting and storing specimens for subsequent analysis.

Sadly, the use of chemicals in Khan Sheikhoun is not an isolated incident. After all, a recent report of the OPCW Fact Finding Mission for the period December 2015 to November 20, 2016, recorded 65 potential incidents of the use of chemical weapons reported in open sources.

The use of chemical weapons has a long history in the region. On March 16, 1988, Iraq dropped bombs containing multiple toxic chemicals on the Kurdish city of Halabja, killing thousands.

It’s been the scientific equivalent of a never ending soap opera. The pygmy human species Homo floresiensis (aka ‘the Hobbit’), discovered in 2003 in a cave on the island of Flores, has been bogged down in a mire of controversy for almost 15 years.

Is it a new human species or just a diseased Homo sapiens? If it’s a new kind of human, where does it fit into the evolutionary tree? How old is it? How did it get to Flores in the first place? These are just a few of the questions that have befuddled anthropologists, and the reasons we’ve lacked satisfactory answers to them are three-fold.

First of all, we don’t yet have a lot of bones from the Hobbit’s kind, despite the valiant efforts of Indonesian, Australian and American archaeologists to find them. From Liang Bua 1 (LB1), the most complete individual found so far, there is a skull, shoulder, arm and forearm bones, wrist bones, close to half of its pelvis, and thigh, leg and foot bones.

Additional bones were found during excavations in 2004 from different individuals to LB1 and include an adult lower jaw and upper and lower limb bones, and even some limb bones from a Hobbit child.

Not a bad sample really, but there’s not nearly enough evidence to fully resolve its place in human evolution. And for many other species, like say Homo erectus from Indonesia, we don’t have many limb bones to compare with the Hobbit’s in the first place.

Bits of modern human here, pieces of Lucy’s kind there, chimpanzee resemblances everywhere! The Hobbit’s the weirdest looking human we’ve found so far, and its strange appearance is the second major reason why it’s been at the heart of one of the nastiest squabbles I’ve witnessed in anthropology.

The overall picture we get from the bones is of a creature that had a very small brain, large teeth and walked about on two-feet but in way very different to our own style of moving. Yet, strangely, it also had very short legs and long arms like a chimpanzee, and probably spent a lot of time living in the trees as well as toddling about on the ground.

Finally, the Hobbit was first believed to be just a mere 18,000 years old, though its age has now been revised to between 100,000 and 60,000 years old. This is way too young given the way the Hobbit looks! And while I don’t doubt it’s accuracy, it’s still shockingly young.

What we might expect to find at this time is something more akin to say a tropical Neanderthal. But instead, with the Hobbit, we have something much more primitive, more like Homo habilis or even Australopithecus afarensis, which both lived millions of years ago in Africa.

One researcher who has made it her life’s mission to resolve the Hobbit’s identity is Debbie Argue from the Australian National University. Argue has claimed to have finally solved the riddle of the Hobbit in a new study published in the Journal of Human Evolution.

According to Argue and her team’s findings the Hobbit is indeed a very primitive species and one closely related to Homo habilis. This fits with my own impressions of Homo floresiensis, but one must always keep an open mind and go where the data take you!

Now, if they’re right, then early humans must have migrated out of Africa more than 2 million years ago and spread right across Asia into the far reaches of oceanic Indonesia. Until the Hobbit came along we thought this region had only been settled by Homo sapiens perhaps 50,000 years ago. So this is a very big shift in our thinking!

Question is, are they right? Well, their work is detailed and undoubtedly well executed, and the results are pretty clear-cut. But there will always be uncertainty with these kinds of studies, and with the Hobbit in particular, for the reasons I’ve outlined.

Still, their broad findings are identical to another study published in 2015 by Mana Membo and her team which concluded the Hobbit to be one of the most primitive members of Homo found so far.

But I find it a little troubling that yet another study published only last year by Valeray Zeitoun and his team, using a similar method to both Argue and Membo, concluded the Hobbit could confidently be placed within Homo erectus.

Implication? The Hobbit isn’t a new species at all, but just a dwarfed version of Homo erectus. But I think it’s too soon to jettison the name Homo floresiensis just yet. For a start, only Argue’s study has accounted for the Hobbit’s weird limb bones, and these must surely weigh heavily on any decision we make about how to classify it?

For me, the Hobbit continues to be best understood as a very primitive member of Homo, with all of the implications this brings for us. And wow! What implications they are!

On a final note, despite the disagreement among these studies, they do mark a maturing of discussions surrounding the Hobbit. We seem to have finally said goodbye to the destructive personal attacks of the past and moved onto figuring out what the Hobbit really is.

Star-Lord Peter Quill and the gang are back as Guardians of the Galaxy, Volume 2 opens in cinemas from today in another outing of the galactic blockbuster.

It’s one of the most fun films I’ve seen in years, combining hilarity with characters you care about, and spectacular visuals that trump the first instalment, Guardians of the Galaxy in 2014.

With the awesome music of “Awesome Mixtape #2”, the team unravel the mystery parentage of Quill (played by Chris Pratt) and meet several new characters (watch the credits carefully). Old foes become new allies and there are treats in store for fans of the comics.

But what about the actual science in the film, how does that stack up?

I’m going to start by giving the film a very generous allowance for being a blockbuster made for entertainment, not an educational documentary. That being said, it’s always fun to get stuck into some of the maths- and science-filled scenarios in the film.

Be warned though, there are some mild spoilers ahead.

Maths fail as humour

It was fantastic to see the film uses explicit maths fails as an integral part of the humour.

Not surprisingly, some of the villain characters in the film aren’t particularly bright, and one memorable scene has them screwing up (in several different ways) elementary maths – basic fractions and percentages – when arguing about a juicy cash bounty.

Maths fails have been used as humour in other films and television shows; William Shatner’s tongue in cheek maths in Star Trek being one good example:

These were pretty simple maths fails though and there was a lot of other maths and science in the rest of the film.

Escaping a quantum asteroid field

In one of the many starship chase scenes in the film, the ships have to navigate through what is called a quantum asteroid field.

Asteroids come and go. 123rf.com/Tom De Spiegelaere/Michael Milford

Asteroids randomly appear and disappear as the ships navigate through the field, making it a very dangerous way to escape (a nice twist on traditional asteroid fields where you can see all the asteroids).

So what are the chances of a ship making it through the quantum asteroid field?

The field looks to be mostly empty space. So let’s say that each second the ship spends in the field, there’s a 1 in 100 chance that an asteroid will suddenly materialise on top of the ship, destroying it.

If a ship spends 3 minutes navigating the length of the field, we can calculate the chances of any one ship making it through:

= (survival chance per second)^{number of seconds}

= (1 – destruction chance per second)^{number of seconds}

= (1 – 0.01)^{3 × 60}

= (0.99)¹⁸⁰

= 16.38%

That’s pretty high actually, a 1 in 6 chance. From watching the film, it looks like not many make it through (apart from the heroes of course).

If we know how many of the ships actually make it through, we can work out the survival rate per second. Let’s say 1 (just the heroes’ ship) out of 100 ships make it through, then the chance of surviving the field per second becomes:

= (Chance of surviving field)^{1/number of seconds}

= (Chance of surviving field)^1/180

= (0.01)^1/180

= 0.9747

= 97.47%

Which would suggest a higher danger from the asteroids – a 2.53% chance of being destroyed by a quantum asteroid in any second.

Elevation grenades

Rocket Raccoon (again voiced somewhat unrecognisably by Bradley Cooper) gets to kick some butt in this film too.

Yet another unique weapon is some sort of electrical effect mine, which chucks aliens high up into the air only for them to fall back to earth again (see the trailer):

Elevating the aliens. 123rf.com/Beata Kraus, Chastity/Michael Milford

To chuck aliens so they reach the top of the pine trees (say 30m), we can work out the velocity of the blast:

2 × gravity × height-change = v-final² – v-initial²

At the top, the alien’s velocity (v-final) is zero, so:

2 × -9.81 × 30 = 0² – v-initial²

v-initial² = 2 × 9.81 × 30

v-initial = square root (2 × 9.81 × 30)

v-initial = 24.26 m/s

So to knock the aliens up to the treetops, the mine would have to propel them upwards at an initial speed of about 24m/s.

This is actually a very low blast velocity (possibly to reduce harm), compared to typical conventional explosives that can travel faster than the speed of sound (although objects hit by the blast don’t necessarily travel as fast).

Visiting every planet

One of the characters, the awesomely named Ego (Kurt Russell), has spent many years visiting many, if not all of the planets in the galaxy.

Visiting every planet. 123rf.com/Viktar Malyshchyts, Vadim Sadovski/Michael Milford

This, one can imagine, is not a trivial feat.

According to a recent study, there might be approximately 100 billion planets in our Milky Way galaxy.

To work out how long it normally takes to visit all these planets, you’d have to solve the infamous travelling salesman problem. This problem is about calculating the fastest way to visit a number of locations.

Luckily for us, this particular character regularly has to return to home base. We can simplify the calculation a little by assuming they only visit one planet per trip away from their base.

We also need to know how big the Milky Way is. Best estimates are that it’s between 100,000 and 180,000 light years in diameter. We can simplify this by saying it’s a circle of uniform diameter 140,000 light years.

We can also simplify matters by assuming that the home base is optimally positioned at the centre of the galaxy.

Our traveller is going to need to make 100 billion trips out to a planet and back.

Stars (and associated planets) are generally more densely distributed near the centre of the galaxy, and more sparse further out. A rough approximation we can use is that the average distance from home base to a planet is one quarter of the galaxy diameter – 35,000 light years. That’s a return trip of 70,000 light years, so the total trip distance is:

= average trip distance × number of trips

= 70,000 light years × 100,000,000,000

= 7,000,000,000,000,000 light years

That’s 7 quadrillion (7×10¹⁵) light years. The universe is estimated to be only about 14 billion years old, which is nowhere near enough time to visit all those planets one by one.

With some more calculations, it turns out even visiting all the planets in one go takes longer than the age of the universe.

So, even with speed of light transportation, this is stretching what might be possible for Ego.

Yondu kicks butt

Yondu Udonta (Michael Rooker) is the morally ambiguous rogue and leader of a group of outlaw mercenaries called the Ravagers. He kidnapped Peter as a boy in the original Guardians film, and raised him into adulthood, resulting in a complex relationship to say the least.

Yondu is armed with one of the most unique of weapons in recent film history, a lethal arrow that he can control by whistling. He uses it to great effect in the first film, but steps up his game even further in Volume 2.

Shooting the enemy, one arrow at a time. 123rf.com/mik38, Chastity/Michael Milford

In one scene, he clears out an entire ship of bad guys. It’s not clear how fast Yondu’s arrow can go, but let’s say it can go faster than a car but slower than a plane, say maybe 275kmh, like a conventional arrow.

A large spacecraft might have a couple of kilometres of corridors and various rooms spread out within it, so the time to clear out the baddies is:

= total distance / speed

= 2km / 275kmh

= 0.0073 hours

= 26.3 seconds

Most fight scenes involving Yondu don’t last more than a few seconds, so that sounds about right.

The verdict

Guardians of the Galaxy, Volume 2 is a lot of fun. Hats off to the scriptwriters and director for the explicit maths fail jokes, and for all the other science- and math-filled content.

Some of the fantastical situations in the film could happen mathematically, but at least one of them would be tough.

Still, films are made to be entertaining, and Guardians of the Galaxy, Volume 2 delivers in an epic way.

Our world view and resultant actions are often driven by a simple theorem, devised in secret more than 150 years ago by a quiet English mathematician and theologian, Thomas Bayes, and only published after his death.

Bayes’ Theorem was famously used to crack the Nazi Enigma code during World War II, and now manages uncertainty across science, technology, medicine and much more.

So how does it work?

Bayes’ Theorem explained

Thomas Bayes’ insight was remarkably simple. The probability of a hypothesis being true depends on two criteria:

1. how sensible it is, based on current knowledge (the “prior”)


2. how well it fits new evidence.

Yet, for 100 years after his death, scientists typically evaluated their hypotheses against only the new evidence. This is the traditional hypothesis-testing (or frequentist) approach that most of us are taught in science class.

The difference between the Bayesian and frequentist approaches is starkest when an implausible explanation perfectly fits a piece of new evidence.

Let me concoct the hypothesis: “The Moon is made of cheese.”

I look skywards and collect relevant new evidence, noting that the Moon is cheesy yellow in colour. In a traditional hypothesis-testing framework, I would conclude that the new evidence is consistent with my radical hypothesis, thus increasing my confidence in it.

But using Bayes’ Theorem, I’d be more circumspect. While my hypothesis fits the new evidence, the idea was ludicrous to begin with, violating everything we know about cosmology and mineralogy.

Thus, the overall probability of the Moon being cheese – which is a product of both terms – remains very low.

Admittedly, this is an extreme caricature. No respectable scientist would ever bother testing such a dumb hypothesis.

But scientists globally are always evaluating a huge number of hypotheses, and some of these are going to be rather far-fetched.

For example, a 2010 study initially suggested that people with moderate political views have eyes that can literally see more shades of grey.

This was later dismissed after further testing, conducted because the researchers recognised it was implausible to begin with. But it’s almost certain that other similar studies have been accepted uncritically.

The Bayesian approach in life

We use prior knowledge from our experiences and memories, and new evidence from our senses, to assign probabilities to everyday things and manage our lives.

Consider something as simple as answering your work mobile phone, which you usually keep on your office desk when at work, or on the charger when at home.

You are at home gardening and hear it ringing inside the house. Your new data is consistent with it being anywhere indoors, yet you go straight to the charger.

You have combined your prior knowledge of the phone (usually either on the office desk, or on the charger at home) with the new evidence (somewhere in the house) to pinpoint its location.

If the phone is not at the charger, then you use your prior knowledge of where you have sometimes previously left the phone to narrow down your search.

You ignore most places in the house (the fridge, the sock drawer) as highly unlikely a priori, and hone in on what you consider the most likely places until you eventually find the phone. You are using Bayes’ Theorem to find the phone.

Belief and evidence

A feature of Bayesian inference is that prior belief is most important when data are weak. We use this principle intuitively.

For example, if you are playing darts in a pub and a nearby stranger says that he or she is a professional darts player, you might initially assume the person is joking.

You know almost nothing about the person, but the chances of meeting a real professional darts player are small. DartPlayers Australia tells The Conversation there are only about 15 in Australia.

If the stranger throws a dart and hits the bullseye, it still mightn’t sway you. It could just be a lucky shot.

But if that person hits the bullseye ten times in a row, you would tend to accept their claim of being a professional. Your prior belief becomes overridden as evidence accumulates. Bayes’ Theorem at work again.

The one theory to rule them all

Bayesian reasoning now underpins vast areas of human enquiry, from cancer screening to global warming, genetics, monetary policy and artificial intelligence.

Risk assessment and insurance are areas where Bayesian reasoning is fundamental. Every time a cyclone or flood hits a region, insurance premiums skyrocket. Why?

Risk can be tremendously complex to quantify and current conditions might provide scant information about likely future disasters. Insurers therefore estimate risk based on both current conditions and what’s happened before.

Every time a natural disaster strikes, they update their prior information on that region into something less favourable. They foresee a greater probability of future claims, and so raise premiums.

Bayesian inference similarly plays an important role in medical diagnosis. A symptom (the new evidence) can be a consequence of various possible diseases (the hypotheses). But different diseases have different prior probabilities for different people.

A major problem with online medical tools such as webMD is that prior probabilities are not properly taken into account. They know very little about your personal history. A huge range of possible ailments can be thrown up.

A visit to a doctor who knows your prior medical records will result in a narrower and more sensible diagnosis. Bayes’ Theorem once again.

Alan Turing and Enigma

Bayesian approaches allow us to extract precise information from vague data, to find narrow solutions from a huge universe of possibilities.

They were central to how British mathematician Alan Turing cracked the German Engima code. This hastened the allied victory in World War II by at least two years and thus saved millions of lives.

To decipher a set of encrypted German messages, searching the near-infinite number of potential translations was impossible, especially as the code changed daily via different rotor settings on the tortuously complex Enigma encryption machine.

Turing’s crucial Bayesian insight was that certain messages were much more likely than other messages.

These likely solutions, or “cribs” as his team called them, were based on previous decrypted messages, as well as logical expectations.

For example, messages from U-boats were likely to contain phrases related to weather or allied shipping.

The strong prior information provided by these cribs greatly narrowed the number of possible translations that needed to be evaluated, allowing Turing’s codebreaking machine to decipher the Enigma code rapidly enough to outpace the daily changes.

Bayes and evolution

Why are we so interested in Bayesian methodology? In our own field of study, evolutionary biology, as in much of science, Bayesian methods are becoming increasingly central.

From predicting the effects of climate change to understanding the spread of infectious diseases, biologists are typically searching for a few plausible solutions from a vast array of possibilities.

In our research, which mainly involves reconstructing the history and evolution of life, these approaches can help us find the single correct evolutionary tree from literally billions of possible branching patterns.

In work – as in everyday life – Bayesian methods can help us to find small needles in huge haystacks.

The dark side of Bayesian inference

Of course, problems can arise in Bayesian inference when priors are incorrectly applied.

In law courts, this can lead to serious miscarriages of justice (see the prosecutor’s fallacy).

In a famous example from the UK, Sally Clark was wrongly convicted in 1999 of murdering her two children.

Prosecutors had argued that the probability of two babies dying of natural causes (the prior probability that she is innocent of both charges) was so low – one in 73 million – that she must have murdered them.

But they failed to take into account that the probability of a mother killing both of her children (the prior probability that she is guilty of both charges) was also incredibly low. So the relative prior probabilities that she was totally innocent or a double murderer were more similar than initially argued.

Clark was later cleared on appeal with the appeal court judges criticising the use of the statistic in the original trial.

This highlights how poor understanding of Bayes’ Theorem can have far-reaching consequences. But the flip side is that Bayesian methods with well justified, appropriate priors can provide insights that are otherwise unobtainable.

The discovery of massive galaxy that stopped making any new stars by the time the Universe was only 1.65 billion years old means we may have to rethink our theories on how galaxies formed.

The galaxy, known as ZF-COSMOS-20115, formed all of its stars (more than three times as many as our Milky Way has today) through an extreme starburst event.

But it stopped forming stars to become a “red and dead” galaxy not much more than a billion years after the Big Bang. Such galaxies are common in our Universe today but not expected to have existed at this ancient epoch. Galaxies turn red when they stop forming stars due to the resulting absence of hot, blue stars that have very short lifetimes.

This discovery by our team sets a new record for the earliest massive red galaxy, with details published in Nature this month.

It is an incredibly rare find that poses a new challenge to galaxy evolution models to accommodate the existence of such galaxies much earlier in the Universe.

An earlier discovery

To put this discovery in context, I’d like to give a short, personal history of research on early massive galaxies.

In 2004 I wrote an uncannily similar Nature paper about the existence of massive, old galaxies in the early Universe that were discovered in deep near-infrared surveys. At that time we were peering back across space to 3 billion years after the Big Bang.

These were a challenge for the models of galaxy formation that scientists were working with at the time, the start of a period where our pictures of how galaxies formed were rapidly being rewritten.

At the time, a picture of galaxies forming by lots of mergers in hierarchical assembly was in vogue. The problem was that this meant that today’s massive galaxies were in little bits billions of years ago.

But significant changes were made – driven in part by observations of the abundance of early massive galaxies, the observations of large gas-rich disk galaxies at these epochs and the discovery of “red nuggets” – extremely compact massive elliptical galaxies which stopped forming stars early on.

We moved to a picture where most galaxy growth and formation was driven by the formation of stars within the galaxy itself, from cosmic gas coming in to the galaxy.

This gas is fed into galaxies along the cosmic web by cold streams that are effective early on and allow us to grow massive galaxies more quickly in the computer modelling.

Many, many astronomers contributed to these developments and it was fun to play a minor role.

The new discovery

So what about this new discovery? This stems from the ZFOURGE survey, a deep near-infrared imaging survey we have been conducting on the Magellan telescopes in Chile, since 2010.

Back in 2013, one of our students, Caroline Straatman of Leiden University, discovered a population of pale red dots in the ZFOURGE survey.

These dots were bright in the near-infrared but very faint in the 35 other wavelength bands we observed. This peak suggested the presence of roughly 500 million year old stars but at a huge cosmic redshift.

In the local Universe this peak appears in blue light, so the redshift points to a time around 1.5 billion years after the Big Bang. The light suggested that no young stars were present, and the near-infrared brightness suggested these were massive objects (10¹¹ solar masses).

To put this in context, our Milky Way has been growing continuously for 12 billion years but is 3-5 times less massive.

Even more remarkably, the galaxies looked like ellipticals and were almost point sources, even with high-resolution Hubble Space Telescope observations. They were less than 5,000 light years across. Extremely dense red nuggets at an earlier time than anyone had suspected.

Lines in the spectrum

In 2012 a powerful new near-infrared spectrograph was commissioned on the W M Keck telescopes in Hawaii. Last year we used it to get a two-night exposure on some of these objects.

We were amazed when we got a spectrum of the brightest (and most massive). They showed the distinct signature of Balmer absorption lines of stars around 500 million years old. Importantly there was no sign of current star-formation.

This galaxy was already massive and between 500 million and 1 billion years old.

It must have formed extremely fast, and then its star formation died quickly. This extreme behaviour could require significant rewriting of our pictures of galaxy formation in the first billion years of cosmic history.

Why? Well, we think galaxies form in the centres of halos of cold dark matter. Dark matter particles is not made of ordinary atoms, and particle physicists are still trying to detect these in the laboratory.

These halos can form very early and act as seeds for galaxy formation giving it a kick start. Without dark matter it would be difficult to form any galaxy.

The problem is at this early time there are barely enough massive dark matter halos to accommodate such massive galaxies. As a consequence in simulated Universes we don’t find this population of non-star forming galaxies so early, nor do we find the massive ancestors with extreme star-formation rates a billion years earlier.

So, do we need two recipes for galaxy formation where some form extremely quickly and the rest take 12 billion years?

Time will tell. The history of this field has shown that the theoretical community has a very strong record of postdiction (as opposed to prediction), and I expect a slew of papers will turn up in the next few weeks to explain this object!

Teasing of theorists aside, galaxy formation is a very difficult field to work in; the astrophysics are complex and it is very much driven by new observations which is why it is so much fun to work in.

Meanwhile our groups are pursuing the quest for massive galaxies to even earlier times. We have designed new filters to identify these and hope to start a new survey using the Gemini telescopes this year. Theorists, get your predictions in now.

Learning how to drive is an ongoing process for we humans as we adapt to new situations, new road rules and new technology, and learn the lessons from when things go wrong.

But how does a driverless car learn how to drive, especially when something goes wrong?

That’s the question being asked of Uber after last month’s crash in Arizona. Two of its engineers were inside when one of its autonomous vehicles spun 180 degrees and flipped onto its side.

Uber pulled its test fleet off the road pending police enquiries, and a few days later the vehicles were back on the road.

Smack, spin, flip

The Tempe Police Department’s report on the investigation into the crash, obtained by the EE Times, details what happened.

The report says that the Uber Volvo (red in the graphic below) was moving south at 38mph (61kmh) in a 40mph (64kmh) zone when it collided with the Honda (blue in the graphic) turning west into a side street (point 1).

Knocked off course, the Uber Volvo hit the traffic light at the corner (point 2) and then spun and flipped, damaging two other vehicles (points 3 and 4) before sliding to a stop on its side (point 5).

Thankfully, no one was hurt. The police determined that the Honda driver “failed to yield” (give way) and issued a ticket. The Uber car was not at fault.

Questions, questions

But Mike Demler, an analyst with the Linley Group technology consultancy, told the EE Times that the Uber car could have done better:

It is totally careless and stupid to proceed at 38mph through a blind intersection.

Demler said that Uber needs to explain why its vehicle proceeded through the intersection at just under the speed limit when it could “see” that traffic had come to a stop in the middle and leftmost lanes.

The EE Times report said that Uber had “fallen silent” on the incident. But as Uber uses “deep learning” to control its autonomous cars, it’s not clear that Uber could answer Demler’s query even if it wanted to.

In deep learning, the actual code that would make the decision not to slow down would be a complex state in a neural network, not a line of code prescribing a simple rule like “if vision is obstructed at intersection, slow down”.

Debugging deep learning

The case raises a deep technical issue. How do you debug an autonomous vehicle control system that is based on deep learning? How do you reduce the risk of autonomous cars getting smashed and flipped when humans driving alongside them make bad judgements?

Demler’s point is that the Uber car had not “learned” to slow down as a prudent precautionary measure at an intersection with obstructed lines of sight. Most human drivers would naturally beware and slow down when approaching an intersection with obstructed vision due to stationary cars.

When it comes to deep reinforcement learning, this relies on “value functions” to evaluate states that result from the application of policies.

A value function is a number that evaluates a state. In chess, a strong opening move by white such as pawn e7 to e5 attracts a high value. A weak opening such as pawn a2 to a3 attracts a low one.

The value function can be like “ouch” for computers. Reinforcement learning gets its name from positive and negative reinforcement in psychology.

Until the Uber vehicle hits something and the value function of the deep learning records the digital equivalent of “following that policy led to a bad state – on side, smashed up and facing wrong way – ouch!” the Uber control system might not quantify the risk appropriately.

Having now hit something it will, hopefully, have learned its lesson at the school of hard knocks. In future, Uber cars should do better at similar intersections with similar traffic conditions.

Debugging formal logic

An alternative to deep learning is autonomous vehicles using explicitly stated rules expressed in formal logic.

This is being developed by nuTonomy, which is running an autonomous taxi pilot in cooperation with authorities in Singapore.

NuTonomy’s approach to controlling autonomous vehicles is based on a rules hierarchy. Top priority goes to rules such as “don’t hit pedestrians”, followed by “don’t hit other vehicles” and “don’t hit objects”.

Rules such as “maintain speed when safe” and “don’t cross the centreline” get a lower priority, while rules such as “give a comfortable ride” are the first to be broken when an emergency arises.

While NuTonomy does use machine learning for many things, it does not use it for normative control: deciding what a car ought to do.

In October last year, a NuTonomy test vehicle accident was involved in an accident: a low-speed tap resulting in a dent, not a spin and flip.

The company’s chief operating officer Doug Parker told IEEE Spectrum:

What you want is to be able to go back and say, “Did our car do the right thing in that situation, and if it didn’t, why didn’t it make the right decision?” With formal logic, it’s very easy.

Key advantages of formal logic are provable correctness and relative ease of debugging. Debugging machine learning is trickier. On the other hand, with machine learning, you do not need to code complex hierarchies of rules.

Time will tell which is the better approach to driving lessons for driverless cars. For now, both systems still have much to learn.

As of today, Australian internet service providers (ISPs) and telecommunications companies are officially required to collect “metadata” about their customers’ communications. According to the legislation, this data includes:

• name, address, date of birth, email addresses and other identifying information of the person that holds an account


• details of any communication, including:
  
  • the mode of communication (voice, sms, email, chat, forum, social media)
  
  
  • the location of the person at the start and end of the communication
  
  
  • the address and details of the receiver of the communication
  
  
  • the network used for the communication (ADSL, Wi-Fi, VoIP, cable, etc).
  
  

What it does not include is details of websites a person visits, and nor does it include information about what they did on those sites.

There is still confusion on this point amongst the public and media, and more generally about what the data retention law really means for Australians. There is still talk about the need to “hide online browsing” because of this legislation, when in fact ISPs are not required to save such information.

Even in the US where privacy rules have been overturned by the House of Representatives – theoretically allowing ISPs to sell or market customer’s browsing history – in practice, ISPs have a vested interest in maintaining customer privacy.

There is still a strong argument to be made regarding being concerned about the metadata being stored, and consequently about the steps Australians can make to protect their privacy.

The list of Australian government departments that have requested access to metadata, or have explicit authority to request access to the metadata, collected by the ISPs and telecommunications companies is extensive and wide ranging. This means that a larger part of Australians’ lives could become accessible to these agencies, and the information collected could potentially be used against them.

The most effective way of protecting privacy of communications on the Internet is to use a virtual private network (VPN), which will quite simply prevent all details of communications (and yes, also browsing history) from being visible to an ISP.

Although the use of a VPN is a good idea for protecting privacy, there are still some risks involved in using this technology. Firstly, VPN users have to trust that the company providing the services is actually doing what they claim and really protecting their customers. Recently, a large number of Android VPN apps have been shown to have significant privacy and security issues with them. Even with the better-known VPN providers, customers are required to simply trust that the VPN provider is doing what they claim and not keeping records or logs.

There are a set of well known and well regarded VPN providers that have “mostly” operated without controversy. VPN software has become extremely simple to operate on PCs and mobile devices. With growing numbers of customers, VPN providers have made an effort to scale servers and bandwidth to make the potential slow-downs from using a VPN less noticeable.

Theoretically, a VPN can be set up to operate continuously whenever there is a network connection. This would mean that any subsequent communications done over that network would be entirely private. Using a mobile VPN would allow even the fact that Facetime or WhatsApp was used to communicate with someone to be hidden from an ISP.

Without a VPN, the ISP would record that a Facetime conversation occurred between the customer and another person, the length of the connection and the location of the customer at the time. Of course, identifying the person that the customer talked to would still take some work in tracking down an internet address and again, this information might yield only the address of a VPN provider and not the individual.

VPNs are becoming an essential part of being on the internet. Apart from the privacy aspect, there is the added security they provide, especially when using unknown wireless networks such as in cafes, airports, or even at work. They also provide the ability to avoid geolocked content on services like Netflix, which up until the advent of metadata retention was the main reason for most people using a VPN, especially in Australia.

Given the commitments to privacy and security made by companies like Apple and Google, it would not be at all surprising if they started to provide their own VPN services to customers that were seamlessly built into their devices.

Updated 18th April 2017 at 14:30 to reflect a clarification by a senior media adviser for the Office of the Attorney General on the organisations that have explicit authority to request access to metadata under section 110A of the Telecommunications (Interception and Access) Act 1979

Which is more important, a fact or an opinion on any given subject? It might be tempting to say the fact. But not so fast…

Lately, we find ourselves lamenting the post-truth world, in which facts seem no more important than opinions, and sometimes less so.

We also tend to see this as a recent devaluation of knowledge. But this is a phenomenon with a long history.

As the science fiction writer Isaac Asimov wrote in 1980:

Anti-intellectualism has been a constant thread winding its way through our political and cultural life, nurtured by the false notion that democracy means that “my ignorance is just as good as your knowledge”.

The view that opinions can be more important than facts need not mean the same thing as the devaluing of knowledge. It’s always been the case that in certain situations opinions have been more important than facts, and this is a good thing. Let me explain.

Not all facts are true

To call something a fact is, presumably, to make a claim that it is true. This isn’t a problem for many things, although defending such a claim can be harder than you think.

What we think are facts – that is, those things we think are true – can end up being wrong despite our most honest commitment to genuine inquiry.

For example, is red wine good or bad for you? And was there a dinosaur called the brontosaurus or not? The Harvard researcher Samuel Arbesman points out these examples and others of how facts change in his book The Half Life of Facts.

It’s not only that facts can change that is a problem. While we might be happy to consider it a fact that Earth is spherical, we would be wrong to do so because it’s actually a bit pear-shaped. Thinking it a sphere, however, is very different from thinking it to be flat.

Asimov expressed this beautifully in his essay The Relativity of Wrong. For Asimov, the person who thinks Earth is a sphere is wrong, and so is the person who thinks the Earth is flat. But the person who thinks that they are equally wrong is more wrong than both.

Geometrical hair-splitting aside, calling something a fact is therefore not a proclamation of infallibility. It is usually used to represent the best knowledge we have at any given time.

It’s also not the knockout blow we might hope for in an argument. Saying something is a fact by itself does nothing to convince someone who doesn’t agree with you. Unaccompanied by any warrant for belief, it is not a technique of persuasion. Proof by volume and repetition – repeatedly yelling “but it’s a fact!” – simply doesn’t work. Or at least it shouldn’t.

Matters of fact and opinion

Then again, calling something an opinion need not mean an escape to the fairyland of wishful thinking. This too is not a knockout attack in an argument. If we think of an opinion as one person’s view on a subject, then many opinions can be solid.

For example, it’s my opinion that science gives us a powerful narrative to help understand our place in the Universe, at least as much as any religious perspective does. It’s not an empirical fact that science does so, but it works for me.

But we can be much clearer in our meaning if we separate things into matters of fact and matters of opinion.

Matters of fact are confined to empirical claims, such as what the boiling point of a substance is, whether lead is denser than water, or whether the planet is warming.

Matters of opinion are non-empirical claims, and include questions of value and of personal preference such as whether it’s ok to eat animals, and whether vanilla ice cream is better than chocolate. Ethics is an exemplar of a system in which matters of fact cannot by themselves decide courses of action.

Matters of opinion can be informed by matters of fact (for example, finding out that animals can suffer may influence whether I choose to eat them), but ultimately they are not answered by matters of fact (why is it relevant if they can suffer?).

Backing up the facts and opinions

Opinions are not just pale shadows of facts; they are judgements and conclusions. They can be the result of careful and sophisticated deliberation in areas for which empirical investigation is inadequate or ill-suited.

While it’s nice to think of the world so neatly divided into matters of fact and matters of opinion, it’s not always so clinical in its precision. For example, it is a fact that I prefer vanilla ice cream over chocolate. In other words, it is apparently a matter of fact that I am having a subjective experience.

But we can heal that potential rift by further restricting matters of fact to those things that can be verified by others.

While it’s true that my ice cream preference could be experimentally indicated by observing my behaviour and interviewing me, it cannot be independently verified by others beyond doubt. I could be faking it.

But we can all agree in principle on whether the atmosphere contains more nitrogen or carbon dioxide because we can share the methodology of inquiry that gives us the answer. We can also agree on matters of value if the case for a particular view is rationally persuasive.

Facts and opinions need not be positioned in opposition to each other, as they have complementary functions in our decision-making. In a rational framework, they are equally useful. But that’s just my opinion – it’s not a fact.

The first Australian-built satellites to be launched in 15 years are set to take off this week from Cape Canaveral in Florida.

Unlike the enormous satellites Australia uses for telecommunications, each of these new satellites is the size of a loaf of bread. But although small, they may provide a key step in enabling Australia’s entry into the global satellite market.

Three types of cubesats are the Australian contribution to the international QB50 mission, in which 36 satellites from different institutions around the world will carry instruments provided by the Von Karman Institute (VKI) to examine the lower thermosphere. This is a very interesting part of the atmosphere for several reasons, such as the way it disturbs GPS measurements.

The cubesats will be first delivered to the International Space Station, and then released into their orbits.

The three teams that developed the Australian cubesats are: one from UNSW, one collaboration between the University of Sydney, the Australian National University and UNSW, and one collaboration between the universities of Adelaide and South Australia.

Once the VKI instrument and support systems (power, communications, and so on) are installed, there is still room for the teams to install payloads of their own.

The UNSW cubesat, known as UNSW-EC0, is running four experiments including a GPS receiver, and two boards testing radiation-robust software and self-healing electronics. The fourth experiment is to test the satellite’s chassis, built using a 3D-printed material never before flown in space.

The launch is significant, not just because it is so long since Australia built satellites, but because it could be the start of something much bigger.

Small is good

Globally, the space industry had an estimated US$335 billion (AU$440 billion) turnover in 2015. It’s expected to reach US$1 trillion (AU$1.3 trillion) by 2030.

This is an innovation sector Australia cannot ignore, and small satellites – especially nano-satellites or cubesats – offer Australia a way in.

According to a report last month by Allied Market Research, the small satellite market is expected to be worth US$7 billion (AU$9.2 billion) by 2020, with a compound annual growth rate of about 20%.

Analyst Spaceworks said in February that by 2023, the requirement for launches in the 1kg to 50kg class will be 320 to 460 satellites per year, more than 70% of them for commercial purposes.

Another analyst Euroconsult last year said there would be more than 3,500 small satellite launches in the next decade, worth US$22 billion (AU$29 billion) with launch earnings of US$5.3 billion (AU$7 billion). That’s a 76% increase over the previous decade.

Australia in space

This disruption has the potential to be more important for Australia than for any other developed nation.

Australia is the largest economy in the world not to have a space agency, which I have highlighted before, and suggested ways forward. As a result, Australia has not developed a traditional space industry.

Exploiting cubesats offers an opportunity for Australia to participate in this industry, despite the absence of an agency.

In the same way that the success of Rocket Lab forced New Zealand to establish a space agency, Australia’s success with cubesats could finally see the establishment of an agency here.

A gathering of space minds

The launch of the QB50 cubesats has been delayed several times and is currently slated for 1am (AEST) on Wednesday April 19.

So by sheer coincidence it will coincide with a gathering in Sydney of the Australian cubesat community – CUBESAT 2017: Launching Cubesats for and from Australia – that will showcase some of the remarkable progress Australia has made in recent years.

This includes three cubesat missions that have constructed satellites – QB50 mentioned above, and a further two from the Defence Science and Technology Group: Biarri (two launches of one cubesat and three cubesats) and Buccaneer (one cubesat).

A large number of Australian start-ups are looking to operate in the global small satellite market.

Several companies are developing launch capability, including Gilmour Space Technologies in Queensland. Other companies are developing ground segment capability to help manage operational satellites including Saber Astronautics in Sydney. Some are developing cubesat components such as Obelisk Systems in Maitland, New South Wales.

Ambitiously, there are also companies looking to develop cubesat constellations, which are large numbers of satellites with orbits optimised for global coverage for a range of different applications. The Australian leader at present is Fleet from Adelaide.

Government interest

CUBESAT 2017 is the second workshop of its kind. When the first was run, two years ago, there was no way then to anticipate the huge leaps Australia has made in this niche area of space.

Recently, the Space Industry Association of Australia released a white paper calling for a space agency.

There was some encouragement for the community in the response from the federal Science Minister, Senator Arthur Sinodinos, to that call when he said:

I’m quite excited at the idea of us doing more in space.

So there is hope we may see some developments.

In terms of cubesats, it is with great excitement we look forward to where we’ll be in the next two years, when perhaps we can say, with Australian-made assets in space, that the Australian space industry has finally been established.

The Facebook Live video of the murder of 74 year old Robert Godwin Sr. by Steve Stephens has been watched at least 1.6 million times.

It took Facebook 3 hours to take the video down, and by that time it had been copied and circulated repeatedly by Facebook users.

In Sweden, three men were arrested after streaming the sexual assault of a woman live to a private Facebook group.

Facebook’s VP, Global Operations wrote that

We disabled the suspect’s account within 23 minutes of receiving the first report about the murder video, and two hours after receiving a report of any kind. But we know we need to do better.

Facebook was notified about the murder video 1 hour and 45 minutes after it had been posted.

There is a limit to what Facebook can actually do about preventing this sort of posting, short of banning what is now the core of the platform, video, and in particular, live video.

The idea that notoriety and 15 minutes of fame through mass media spurring murderers is not new. In the past, critics have argued that mainstream media has played a major role in publicising mass murderers and giving them the very thing that they crave. Not only that, but there has been a view that this process actually then spurs others into copycat crimes.

With social media and live streaming, mainstream media is no longer needed. Criminals, murderers and terrorists have found that they can go directly to a seemingly eager audience to view crime as it happens.

It is not only murderers who are turning to Facebook. The live streaming of suicides has become an increasingly frequent occurrence.

On another level, Facebook and social media has been implicated in fuelling gang violence by allowing gangs to trade insults and make violent threats. It’s behaviour that has been termed “internet banging” by sociologists Desmond Patton, Robert Eschmann and Dirk Butler, who have been studying this phenomenon.

For teens, cyberbullying and “being mean” online are the expected consequence of being online and using social media, especially Facebook.

The question that researchers and others are increasingly asking is whether the negative consequences of social media will inevitably outweigh any benefits.

The fundamental problem with social media, and more generally with the internet, is the online disinhibition effect that lies at the heart of trolling and bad behaviour. The issue with bad behaviour online is that it becomes the new normal. As society readjusts to these new norms, online disinhibition kicks in again to move the norm to new extremes.

Another psychological phenomenon that may be at play is the bystander effect. People on social media can watch a video of a murder, suicide or rape and not take action, like reporting the video, because there is an assumption that because so many others are watching, somebody would have already taken that action.

Just as the world is getting fatter because we can’t say no to gratification from fats and sugars, social media is destined to become more violent and aggressive. The fascination with watching others behaving badly is too hard to resist, fuelling even further tendencies of exhibitionism and narcissism that then motivate more people to behave badly and record the experience online. To that extent, online exposure to bad behaviour becomes the cerebral equivalent to polluting the body with junk food.

Another macabre practice that has been fuelled by social media is the growth in people taking selfies at horror sites such as the Dachau concentration camp, and locations of disasters such as plane crash sites.

Of course, there is the balancing effect of people acting collectively through social media for individual and collective good but this, like exercise in combating obesity, takes effort and it is not at all certain that it can neutralise the negative aspects of social media.

Facebook and other social media sites are not in a position to address the growing problem playing out on their platforms. It is not even possible to criminalise the act itself as a deterrent if what is actually being depicted is already a crime. Bad behaviour online may be amenable to similar strategies used to target other poor behaviours like smoking and excessive drinking through regulation or even pricing. The US and other governments are taking this approach in dealing with cyberbullying.

The German Government is also investigating Facebook for its role in inciting racial and ethnic hatred and could hold it accountable.

Ultimately, holding the companies that facilitate this behaviour accountable would force their hand to either limit what could be posted by having it moderated or simply restricting the service in some other way.

Qantas switched on its free inflight internet service trial on April 7, with Virgin set to launch its own similar program later this month.

It’s been one year since Qantas made its original announcement of inflight Wi-Fi, and five months since the first trial period was postponed. Qantas and its service partners acted fast to bring its trial to fruition.

Qantas’ inflight free internet trial across Australian domestic routes will be based on the ViaSat satellite broadband service, and will use NBN Co’s SkyMuster satellites. These are the same satellites that deliver broadband internet to remote Australia.

So what will the demand on this service mean for internet customers on land and in the air?

Satellite broadband in a plane

The Skymuster geostationary satellites (positioned about 36,000km above Earth) act as an internet bridge, connecting a ground-based internet gateway to broadband customers on the aircraft.

A specialised satellite receiver installed in the plane provides the link to the satellite, in much the same way that a residential broadband installation connects homes to satellites. An onboard network of Wi-Fi routers then provides a direct internet connection either to an entertainment system installed in the seat, or to a compatible device belonging to the passenger.

Compared to onground Wi-Fi, onboard service delivery involves a relatively large number of passengers sharing the same satellite link.

The satellite receiver on the aircraft therefore needs to meet stringent design and operational requirements and can be very expensive for airlines to install across their fleet.

Qantas’ own customer survey cites accessing emails (52%), web surfing (46%), streaming music, TV or movies (31%), accessing social media (30%), and news (30%) as the most popular modes of expected use.

Qantas and other carriers are also seeking to gain more efficiency across their flight management by allowing crew to obtain real-time updates on flight details via in-flight internet.

Through a combination of new satellites with improved capacities, plus optimisation of the data flow from different services accessed by different passengers, service providers are promising better services.

Movies, not videoconferencing

Qantas’ announcement claims availability of ten times the speed of conventional onboard Wi-Fi using older satellites. But it remains shy in speculating on the actual speed of the connection that passengers can expect to experience.

Currently, outback residential customers accessing similar services through SkyMuster satellites experience peak speeds of 25Mb per second downstream and 5Mb per second upstream.

Broadband customers in urban areas can expect much higher data speeds. NBN Co recently started offering 100Mb per second and 40Mb per second peak downstream and upstream rates.

If you assume 30% of passengers use the service on a Boeing 737 (trial aircraft, 174 passengers), they can reasonably expect speeds of only a few Mb per second. With content being accessed on 9″ seat-mounted displays/tablets or 4-5″ mobile phone screens, passengers might be able to enjoy reasonable quality streaming services or watch their favourite footy game live, as has proved to be the case on a recent trial flight with Qantas inflight internet.

But as the data streams need to travel long distances (from ground to satellite, and then satellite to aircraft), service can experience time delays, referred to as latency. This may affect the customer experience when real-time interactive communications such as video conferencing or online games are in use.

ViaSat claims to offer more than 100Mb per second to aircrafts with the use of specialised satellite transmitters and receivers installed on aircrafts. The company is already working with carriers such as American Airlines. Finnair, United Airlines and Virgin America also signed up for the services over America and Europe.

Internet delivery company gogo also has a hold on this fast developing market, with other carriers as its partners.

Delivering internet to a moving target

Satellites provide broadband connectivity by dividing set geographic regions into smaller areas. Specific beams are set up to transmit and receive signals in an independent manner. This provides more capacity shared among fewer customers, and is designed to optimise service delivery to fixed residences and support applications with low-speed mobility.

For example, Skymuster satellites use a mix of small (135km radius) and wide (325km radius) beams over different regions.

When such service is delivered to aircraft traversing wide distances at very high speeds, handover between multiple beams must be addressed. Depending on the use of smaller or wider beams, such issues could be tackled by networking techniques at the expense of some bandwidth.

Techniques currently in play to improve delivery of satellite broadband include compression (to reduce the amount of data to be transferred), buffering (by caching every byte of information transmitted) and acceleration (techniques relating to how packets of information are handled and how connections are managed).

The fundamental limitation caused by internet signals traversing back and forth between the earth and space remains a major issue. Also, satellite broadband service depends on wireless transmission over a medium prone to weather effects and volatility.

Any minor drop outs in services are exacerbated by the long round trip delay involved in satellite transmission, as it takes longer to repair and restore connectivity.

Also, when multiple people connect and reconnect via such platforms with significant delays, the resilience of satellite-based connectivity might face challenging stability issues (like those experienced by NBN customers in 2016).

Problems linked to pricing and capping of in-flight data packages also need to be considered.

Competing interests

A spokeperson for NBN said that despite the launch of new onboard services, satellite broadband provision to the outback will be prioritised.

But many in the bush are worried about their state of broadband connectivity. It’s an issue that will likely be exacerbated by expanding demand with growing numbers of broadband-using passengers on domestic air routes.

Broadband use in remote Australia is also increasing, and not just for communication. Many applications based on the “Internet of Things” require internet connectivity.

In regional Australia, these range from logistics management, smart farming to facility management in the resources sector. All these services will place growing demand on satellite broadband.

Planning for the time when Skymuster satellites approach capacity limits should be considered. As SkyMuster II starts to deliver services, this might relieve the bandwidth demand.

Unlike the case with its Skymuster I launch, NBN has not yet provided time lines on SkyMuster II in terms of its testing phase or when it will be ready to offer services. Given its successful launch in October 2016, one would expect it should be offering services by now.

Another satellite launch

If there is sufficient demand for in-flight broadband services, it might make it more attractive for the NBN to launch a third satellite to meet the growing demand.

In addition, NBN could look at expanding the roll-out of fixed wireless services. This would migrate some customers out of satellite, and relieve the satellite bandwidth for in-flight and other applications.

ViaSat is also building its own satellite constellation to offer high speed inflight internet across major international flight routes. The company seeks to cover 90% of the routes.

Qantas hopes to complete onboard Wi-Fi infrastructure installation across its fleet of around 80 aircraft (737s and A330s) by 2018. It is not clear how the fleet would be split across domestic and international routes.