Five 2018 Predictions — on GDPR, Robot Cars, AI, 5G and Blockchain

Predictions are like buses, none for ages and then several come along at once. Also like buses, they are slower than you would like and only take you part of the way. Also like buses, they are brightly coloured and full of chatter that you would rather not have in your morning commute. They are sometimes cold, and may have the remains of somebody else’s take-out happy meal in the corner of the seat. Also like buses, they are an analogy that should not be taken too far, less they lose the point. Like buses.

With this in mind, here’s my technology predictions for 2018. I’ve been very lucky to work across a number of verticals over the past couple of years, including public and private transport, retail, finance, government and healthcare — while I can’t name check every project, I’m nonetheless grateful for the experience and knowledge this has brought, which I feed into the below. I’d also like to thank my podcaster co-host Simon Townsend for allowing me to test many of these ideas.

Finally, one prediction I can’t make is whether this list will cause any feedback or debate — nonetheless, I would welcome any comments you might have, and I will endeavour to address them.

1. GDPR will be a costly, inadequate mess

Don’t get me wrong, GDPR is a really good idea. As a lawyer said to me a couple of weeks ago, it is a combination of the the UK data protection act, plus the best practices that have evolved around it, now put into law at a European level with a large fine associated. The regulations are also likely to become the basis for other countries — if you are going to trade with Europe, you might as well set it as the baseline, goes the thinking. All well and good so far.

Meanwhile, it’s an incredible, expensive (and necessary, if you’re a consumer that cares about your data rights) mountain to climb for any organisation that processes or stores your data. The deadline for compliance is May 25th, which is about as likely to be hit as I am going to finally get myself the 6-pack I wanted when I was 25.

No doubt GDPR will one day be achieved, but the fact is that it is already out of date. Notions of data aggregation and potentially toxic combinations (for example, combining credit and social records to show whether or not someone is eligible for insurance) are not just likely, but unavoidable: ‘compliant’ organisations will still be in no better place to protect the interests of their customers than currently.

The challenges, risks and sheer inadequacy of GDPR can be summed up by a single tweet sent by otherwise unknown traveller — “If anyone has a boyfriend called Ben on the Bournemouth – Manchester train right now, he’s just told his friends he’s cheating on you. Dump his ass x.” Whoever sender “@emilyshepss” or indeed, “Ben” might be, the consequences to the privacy of either cannot be handled by any data legislation currently in force.

2. Artificial Intelligence will create silos of smartness

Artificial Intelligence (AI) is a logical consequence of how we apply algorithms to data. It’s as inevitable as maths, as the ability our own brains have to evaluate and draw conclusions. It’s also subject to a great deal of hype and speculation, much of which tends to follow that old, flawed futurist assumption: that a current trend maps a linear course leading to an inevitable conclusion. But the future is not linear. Technological matters are subject to the laws of unintended consequences and of unexpected complexity: that is, the future does not follow a linear path, and every time we create something new, it causes new situations which are beyond its ability to deal with.

So, yes, what we call AI will change (and already is changing) the world. Moore’s, and associated laws are making previously impossible computations now possible, and indeed, they will become the expectation. Machine learning systems are fundamental to the idea of self-driving cars, for example; meanwhile voice, image recognition and so on are having their day. However these are still a long way from any notion of intelligence, artificial or otherwise.

So, yes, absolutely look at how algorithms can deliver real-time analysis, self-learning rules and so on. But look beyond the AI label, at what a product or service can actually do. You can read Gigaom’s research report on where AI can make a difference to the enterprise, here.

In most cases, there will be a question of scope: a system that can save you money on heating by ‘learning’ the nature of your home or data centre, has got to be a good thing for example. Over time we shall see these create new types of complexity, as we look to integrate individual silos of smartness (and their massive data sets) — my prediction is that such integration work will keep us busy for the next year or so, even as learning systems continue to evolve.

3. 5G will become just another expectation

Strip away the techno-babble around 5G and we have a very fast wireless networking protocol designed to handle many more devices than currently — it does this, in principle, by operating at higher frequencies, across shorter distances than current mobile masts (so we’ll need more of them, albeit in smaller boxes). Nobody quite knows how the global roll-out of 5G will take place — questions like who should pay for it will pervade, even though things are clearer than they were. And so on and so on.

But when all’s said and done, it will set the baseline for whatever people use it for, i.e. everything they possibly can. Think 4K video calls, in fact 4K everything, and it’s already not hard to see how anything less than 5G will come as a disappointment. Meanwhile every device under the sun will be looking to connect to every other, exchanging as much data as it possibly can. The technology world is a strange one, with massive expectations being imposed on each layer of the stack without any real sense of needing to take responsibility.

We’ve seen it before. The inefficient software practices of 1990’s Microsoft drove the need for processor upgrades and led Intel to a healthy profit, illustrating the vested interests of the industry to make the networking and hardware platforms faster and better. We all gain as a result, if ‘gain’ can be measured in terms of being able to see your gran in high definition on a wall screen from the other side of the world. But after the hype, 5G will become just another standard release, a way marker on the road to techno-utopia.

On the upside, it may lead to a simpler networking infrastructure. More of a hope than a prediction would be the general adoption of some kind of mesh integration between Wifi and 5G, taking away the handoff pain for both people, and devices, that move around. There will always be a place for multiple standards (such as the energy-efficient Zigbee for IoT) but 5G’s physical architecture, coupled with software standards like NFV, may offer a better starting point than the current, proprietary-mast-based model.

4. Attitudes to autonomous vehicles will normalize

The good news is, car manufacturers saw this coming. They are already planning for that inevitable moment, when public perception goes from, “Who’d want robot cars?” to “Why would I want to own a car?” It’s a familiar phenomenon, an almost 1984-level of doublethink where people go from one mindset to another seemingly overnight, without noticing and in some cases, seemingly disparaging the characters they once were.  We saw it with personal computers, with mobile phones, with flat screen TVs — in the latter case, the the world went from “nah, thats never going to happen” to recycling sites being inundated with perfectly usable screens (and a wave of people getting huge cast-off tellies).

And so, we will see over the next year or so, self-driving vehicles hit our roads. What drives this phenomenon is simple: we know, deep down, that robot cars are safer — not because they are inevitably, inherently safe, but because human drivers are inevitably, inherently dangerous. And autonomous vehicles will get safer still. And are able to pick us up at 3 in the morning and take us home.

The consequences will be fascinating to watch. First that attention will increasingly turn to brands — after all, if you are going to go for a drive, you might as well do so in comfort, right? We can also expect to see a far more varied range of wheeled transport (and otherwise — what’s wrong with the notion of flying unicorn deliveries?) — indeed, with hybrid forms, the very notion of roads is called into question.

There will be data, privacy, security and safety ramifications that need to be dealt with — consider the current ethical debate between leaving young people without taxis late at night, versus the possible consequences of sharing a robot Uber with a potential molester. And I must recall a very interesting conversation with my son, about who would get third or fourth dibs at the autonomous vehicle ferrying drunken revellers (who are not always the cleanliest of souls) to their beds.

Above all, business models will move from physical to virtual, from products to services. The industry knows this, variously calling vehicles ‘tin boxes on wheels’ while investing in car sharing, delivery and other service-based models. Of course (as Apple and others have shown), good engineering continues to command a premium even in the service-based economy: competition will come from Tesla as much as Uber, or whatever replaces its self-sabotaging approach to world domination.

Such changes will take time but in the short term, we can fully expect a mindset shift from the general populace.

5. When Bitcoins collapse, blockchains will pervade

The concept that “money doesn’t actually exist” can be difficult to get across, particularly as it makes such a difference to the lives of, well, everybody. Money can buy health, comfort and a good meal; it can also deliver representations of wealth, from high street bling to mediterranean gin palaces. Of course money exists, I’m holding some in my hand, says anyone who wants to argue against the point.

Yet, still, it doesn’t. It is a mathematical construct originally construed to simplify the exchange of value, to offer persistence to an otherwise transitory notion. From a situation where you’d have to prove whether you gave the chap some fish before he’d give you that wood he offered, you can just take the cash and buy wood wherever you choose. It’s not an accident of speech that pond notes still say, “I promise to pay the bearer on demand…”

While original currencies may have been teeth or shells (happy days if you happened to live near a beach), they moved to metals in order to bring some stability in a rather dodgy market. Forgery remains an enormous problem in part because we maintain a belief that money exists, even though it doesn’t. That dodgy-looking coin still spends, once it is part of the system.

And so to the inexorable rise of Bitcoin, which has emerged from nowhere to become a global currency — in much the same way as the dodgy coin, it is accepted simply because people agree to use it in a transaction. Bitcoin has a chequered reputation, probably unfairly given that our traditional dollars and cents are just as likely to be used for gun-running or drug dealing as any virtual dosh. It’s also a bubble that looks highly likely to burst, and soon — no doubt some pundits will take that as a proof point of the demise of cryptocurrency.

Their certainty may be premature. Not only will Bitcoin itself pervade (albeit at a lower valuation), but the genie is already out of the bottle as banks and others experiment with the economic models made possible by “distributed ledger” architectures such as The Blockchain, i.e. the one supporting Bitcoin. Such models are a work in progress: the idea that a single such ledger can manage all the transactions in the world (financial and otherwise) is clearly flawed.

But blockchains, in general, hold a key as they deal with that single most important reason why currency existed in the first place — to prove a promise. This principle holds in areas way beyond money, or indeed, value exchange — food and pharmaceutical, art and music can all benefit from knowing what was agreed or planned, and how it took place. Architectures will evolve (for example with sidechains) but the blockchain principle can apply wherever the risk of fraud could also exist, which is just about everywhere.

6. The world will keep on turning

There we have it. I could have added other things — for example, there’s a high chance that we will see another major security breach and/or leak; augmented reality will have a stab at the mainstream; and so on. I’d also love to see a return to data and facts on the world’s political stage, rather than the current tub-thumping and playing fast and loose with the truth. I’m keen to see breakthroughs in healthcare from IoT, I also expect some major use of technology that hadn’t been considered arrive, enter the mainstream and become the norm — if I knew what it was, I’d be a very rich man. Even if money doesn’t exist.

Truth is, and despite the daily dose of disappointment that comes with reading the news, these are exciting times to be alive. 2018 promises to be a year as full of innovation as previous years, with all the blessings and curses that it brings. As Isaac Asimov once wrote, “An atom-blaster is a good weapon, but it can point both ways.”

On that, and with all it brings, it only remains to wish the best of the season, and of 2018 to you and yours. All the best!


Photo credit: Birmingham Mail

GTA 6: release date, news, map, characters, cars and every other rumour and leak

Everyone wants a piece of Grand Theft Auto 6.

Whenever Rockstar updates GTA Online heads swivel and the inevitable question returns – when is GTA 6 coming out?

Unfortunately Rockstar has barely hinted about a new Grand Theft Auto game, and the majority of leaks have been rumours at best, guess work, or just straight up lies at worst. A cottage industry creating GTA 6 YouTube videos has sprung up, but these are no more legit than your friend who’s uncle works at Rockstar and has played the alpha. Dude, no one has played the game.

There is hope that it exists in some form though. Back in March 2016 we reported that GTA 6 was in production. This was before Rockstar said it was concentrating so heavily on GTA Online though, so schedules will have no doubt changed. But GTA 5 has shipped 85 million copies. Of course GTA 6 is going to be in production in some form.


GTA 6 release date – when is GTA 6 out?

Look, we’ll be brutally honest with you. GTA 6 doesn’t have an official release date yet, and even when it does, Rockstar has a history of delays. GTA 5 was held back, and the PC version was also delayed a couple of times. The next big game from Rockstar is Red Dead Redemption 2, and that’s already been delayed. So when GTA 6 does eventually get its first release date, don’t put money on it.

GTA 6 map – where is the next GTA game set?

Everyone has their own idea of where the next GTA 6 map should be. And it’s not just fans of the series – this real estate company recreated their own map of Portland complete with pins pointing out knocking shops and tattoo parlours for a few clicks. Aside from London, GTA games aren’t set in real-world locations although each of their maps are based on largely populated cities. Liberty City was based on New York, while Los Santos incorporates LA and the surrounding county. Expect a map for GTA 6 to have bigger size goals then, and to suck up familiar parts of the United States.

GTA 6 news

Who’s always got the GTA news for you? We have. We’ve got an extensive library of all things GTA 5, GTA Online and GTA 6 speculation. Bookmark this page because if anything important breaks, we’ll be on it like a tramp on chips.


GTA 6 characters – can we expect Franklin, Trevor or Michael to return?

We’re pretty certain the stories of GTA 5’s protagonists are over, as they never did make it into the promised GTA 5 single-player story DLC. But when GTA 6 does surface you should expect a few familiar faces, names, companies and locations to crop up. There’s history here; Lazlow Jones has been knocking around GTA games since GTA 3, Ken Rosenburg has represented Tommy from Vice City and CJ from San Andreas, and CJ, Sweet and Ryder all make a fleeting appearance in GTA 5.

GTA 6 cars – what cars will be in GTA 6?

The list of vehicles in GTA 5 and GTA Online is extensive, to say the least. If it exists in real-life then you can bet your ass Rockstar will recreate something similar for a GTA game. That goes for cars from proper manufacturers, military vehicles and fiction – like this Batmobile inspired Vigilante.

GTA Online currently supports racers, tuners, rally, muscle, sedans, off-roaders, bikes, emergency vehicles and a jetpack. So the simple question to what cars will be in GTA 6? All of them.

Looking for help with GTA Online? Why not dig our guide to becoming a CEO, VIP or bike gang leader and stacking loads of cash?

Can driverless cars be safe? Grand Theft Auto helps Penn scientists find out

A sporty black sedan speeds dangerously close to a cliff on a road winding through an arid landscape.

The car recovers and swerves back onto the cracked asphalt, but another sharp turn is coming. It straddles the edge of the cliff, its tires spinning through pale, sunburned sand. Then it falls. Sage brush and rock outcroppings blur past as it plummets.

No driver emerges from the car. No police show up. A virtual reality sun keeps beating down.

The crash occurred in a modified Grand Theft Auto video game, an example of the virtual simulations researchers at University of Pennsylvania are running to evaluate autonomous vehicles, a technology that in the coming years could transform the way Americans get around.

“We can crash as many cars as we want,” said Rahul Mangharam, associate professor at University of Pennsylvania’s Department of Electrical and Systems Engineering.

Mangharam and his team of six are pursuing what they describe as a “driver’s license test” for self-driving cars, a rigorous use of mathematical diagnostics and simulated reality to determine the safety of autonomous vehicles before they ever hit the road.

Complicating that task is the nature of the computer intelligence at the heart of the car’s operation. The computer is capable of learning, but instead of eyes, ears, and a nose, it perceives reality with laser sensors, cameras, and infrared. It does not see or process the world like a human brain. Working with this mystery that scientists call “the black box” is a daunting, even spooky, element of the work at Penn.

“They’re not interpretable,” Mangharam said. “We don’t know why they reached a certain decision; we just know they reached a certain decision.”

Clarity on how safe driverless vehicles can be is a critical step to maturing a technology many think will some day save thousands of lives.

Last year, 37,461 people died in vehicle crashes in the United States, the National Highway Traffic Safety Administration reported — enough to fill more than half of Lincoln Financial Field. About 94 percent of crashes happen because of human mistakes, NHTSA has found, and self-driving cars hold the promise of preventing many of those deaths.

The technology is not yet ready for prime time, most experts agree, and a premature introduction could result in deaths. Experts fervent in the belief that driverless cars eventually will be life savers fear fatal crashes caused by autonomous system failures could scare the public and delay adoption of the technology for years. 

“They need to be very transparent in the development of this technology,” said Leslie Richards, Pennsylvania’s transportation secretary. “To get the public buy-in, people do need to understand.”

In Pennsylvania, much attention related to autonomous cars is focused on Pittsburgh, where last year Uber began operating self-driving cars and Carnegie Mellon University has positioned itself as a leader in the field. But Penn, along with CMU, is a key player in Mobility21, a five-year, federally funded, $14 million program to explore transportation technology, including self-driving vehicles. While colleagues at CMU experiment with their own autonomous car, Penn’s scientists work in a lab that looks like a very bright middle schooler’s rec room.

White boards are covered in complex equations, but the shelves hold jury-rigged toy cars, and the computer screens display video games. It’s all in service of rating robot drivers, how much variation in the environment and in the car itself the system can withstand without a failure. The researchers virtually drive cars in different weather and lighting — testing how well the software rolls with the changes it would face in the real world.

“You can never have 100 percent safety,” Mangharam said. “You can design a system that would not be at fault intentionally.”


Rahul Mangharam works with a team of six at Penn Engineering to test the safety of self-driving cars.

Mangharam describes autonomous vehicles as continuously executing a three-step process. The first step is perception, the system’s attempt to understand what is in the world around it. It should be able to spot a stop sign and other vehicles on the road. Then, data gathered is used to make a plan, which starts with the final destination, formulates a route, and then decides how to navigate that route. The car decides what speed, braking, and trajectory is needed to, for example, get around a slow-moving car on the highway while trying to reach an off-ramp. The third step is the process of driving, the application of brakes, gas, and steering to get where the vehicle is directed to go.

The Penn scientists run the autonomous driving software, called Computer Aided Design for Safe Autonomous Vehicles, through both mathematical diagnostics and the virtual reality test drives on Grand Theft Auto to see when the system fails. The video game is particularly useful because the autonomous driving system can be rigged to perceive it similarly to reality and because the virtual environment can be perfectly controlled by scientists.

The autonomous driver’s inscrutable nature can be challenging, though. Deep neural networks teach themselves how to identify objects through a process of trial and error as they are fed thousands of images of people, trees, intersections — anything a car may encounter on the road. It becomes increasingly accurate the more examples it is fed, but humans cannot know what commonalities and features a machine is fixating on when it perceives a tree, for example, and correctly labels it as such. They are almost certainly not the features a human uses — a trunk, leaves, the texture of bark — to distinguish between a tree and a telephone pole.

Because of the uncertainty about how the robot driver is identifying objects, researchers are concerned it might be coming to the right answer, but for the wrong reasons.

Mangharam used the example of a tilted stop sign. Under normal circumstances, the computer could recognize a stop sign correctly every time. However, if the sign were askew, that could throw off the features the computer uses to recognize it and a car could drive right past it. Scientists need to understand not just what the car does wrong, but at what stage of the driving process the error happens.

“Was the cause of the problem that it cannot perceive the world correctly and made a bad decision,” Mangharam explained, “or did it perceive the world correctly and make a bad decision?”


This split four-screen image shows how the self-driving program reads the terrain during the drive.

While talk of errors and failures invokes visions of flaming wrecks and cars careening off bridges, what is perhaps more likely is paralysis.

“The idea of plunking a fully autonomous car down in New York City or downtown Philly, it is very likely that given the current state of technology and the very, very conservative nature that an autonomous vehicle is going to take because of that liability … I would hearken to guess that car is never going to move,” said Greg Brannon, director of automotive engineering for AAA. “It’s going to look for a break in traffic that’s never going to exist.”

AAA is already doing safety testing on partially autonomous systems such as adaptive cruise control, lane keeping, emergency braking. Some scientists think autonomy will happen abruptly: One company will perfect a product that is born able to handle anything it might encounter on the open road. Brannon, though, sees autonomous systems being introduced gradually, so people would be less likely to see the concept as alien as today’s drivers do.

“People will experience things in bits and pieces,” he said, “and it will breed trust in these systems.”

Pennsylvania has passed legislation governing the testing of autonomous vehicles on the state’s roads, and Richards said she and her counterparts in other states frequently talk about what kind of regulatory framework might be needed as full autonomy becomes closer to a reality. A driver’s license test, as Mangharam proposes, is one possibility, though she said it would likely require cooperation between states and the federal government to decide on safety standards. The standard would have to consider that at least initially, she said, robot drivers would likely be sharing the road with many humans behind the wheel.

“We all know that any incidents of hazards tied to autonomous or collective vehicles will set everybody back,” said Richards, who is convinced the technology will ultimately save lives. “We really want to proceed as cautiously as possible to maintain this positive moment.”

A common question about driver-less vehicles is how soon the general public will start using them. As much as he believes in autonomous technology, Mangharam is worried by a tendency in our society to leave regulatory oversight in the dust as we embrace a new toy.

“I don’t think we should be focusing on a date,” he said, “until we reach some safety threshold.”

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Yandex, the ‘Google of Russia,’ is now testing self-driving cars in the snow

Hot off its joint venture with Uber, Russian tech giant Yandex is testing its cold-weather capabilities. The company often known as the Google of Russia is exploring many different industries and technologies, including that of the self-driving variety. And now that it’s forming a joint venture with Uber, it’s stepping up its autonomous capabilities even further. Over the November 25-26 weekend, Yandex conducted test drives with its self-driving taxis in a snowy scenario, ensuring that the autonomous vehicle would be able to keep passengers safe in wintry conditions. In total, the Prius prototypes traveled a total of 300 km during the test.

“We have been working to prepare algorithms for winter ‘at garage’ for a while, so last weekend tests in real world was just the first time we got all confirmations,” Dmitry Polishchuk, head of Yandex.Taxi’s self-driving project, told TechCrunch. Yandex certainly isn’t the first company to test its autonomous abilities in the snow. Just last month, Alphabet-owned Waymo announced that it was testing its own Chrysler Pacific hybrid minivans in snowy and icy conditions in Detroit.

The reason behind such tests is simple — while self-driving vehicles know what to do in ideal road conditions, understanding how to adapt to less than perfect roadways is key to being a good driver (human or otherwise). Snow is often seen as a particular challenge for motorists, as it not only creates a slick roadway, but can also hide road markings and signs. As such, guaranteeing autonomous vehicles’ safe operations in these situations is of the utmost importance.

Yandex has yet to test the self-driving cars on public roads, which means that they haven’t actually driven alongside humans. This, of course, will be a key step in bringing these autonomous vehicles to market. The company hopes to begin these trails in 2018, but this would require some legislation to be passed — as it stands, Russia forbids using self-driving cars on public roads.

For the time being, however, Polishchuk is pleased with the current tests. “There was nothing unexpected,” he said of the recent snow tests. “Computer vision algorithms should be specially tuned to work properly when the snow is falling and covering road surface, and driving technology should count slick surface when choosing speed mode. We will continue tests during the whole winter to make sure our technology for driverless car is reliable for such conditions.”

Arlington Police cars in Grand Theft Auto? Department cracks down on use

Arlington police logo spotted in violent video game

ARLINGTON – Arlington police are cracking down on what they say is theft of their intellectual property in the virtual world.

Realistic renderings of their police cars can be seen in the Grand Theft Auto V video game.  They’re not in the original version of the game, but created by third parties and added on.

“I guess you can download them into the game, and then you can do all kinds of stuff that we wouldn’t really approve of,” said Lt. Chris Cook, with the Arlington Police Department.

The renderings are called skins. A few screengrabs posted to Twitter this week show an Arlington police car and motorcycle that caught the department’s attention.

“Last night, we were alerted by a citizen that said, ‘Hey, your graphics are not only being used but being sold by this graphics company, just wanted to make you aware,'” Cook said.

Circumstances like these are why Arlington police filed for a copyright in 2010 that protects their vehicle graphics, patch, badge and other trademarks.  The department tweeted the creator, asking them to cease and desist with use of the imagery.

On Twitter, user @Stalker63Gaming wrote back to the department, “We were unaware and intended on honoring [law enforcement officers]. We apologize for this and have removed the likeness already!”

Whether they know it or not, many departments have skins in the Grand Theft Auto Game. On YouTube, there are clips showing renderings of Dallas and Fort Worth police vehicles in gameplay. Neither department responded to inquiries about the usage.

It’s just a game, but Arlington police say it’s important to enforce their copyright in order to protect their image.

“A lot of times people will take these images and use them in nefarious means,” Cook said.

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