Facebook tests ‘floating’ videos in your News Feed
Pop-Up Video: it’s not just the greatest VH1 show ever, it’s also Facebook’s latest feature. The social network is rolling out floating videos for desktop users that can sit anywhere in your window while you continue browsing your News Feed, just like on Tumblr. You can activate the feature by clicking on a new button at the bottom-right of video embeds, which looks like this:
First spotted by The Next Web, it seems like the feature is slowly rolling out to the majority of users. In our informal poll, four out of five people were already seeing the button in their feed. Facebook has been steadily improving its video options in an effort to muscle in on YouTube’s lucrative business of placing ads on user videos. If pop-ups gets more users watching more videos for more time, that can only be a good thing when it comes to selling marketing space to potential advertisers.
Filed under: Facebook
Via: The Next Web
How the BBC’s Micro:bit came to be
In the early eighties, the BBC started a computing revolution with the launch of the Micro. The heavy, light-brown box, created with help from Acorn and ARM, was designed to complement the broadcaster’s ongoing computer literacy project. It was intended to give children a grounding not only in programming, but also graphics, sound and gaming. In the thirty-plus years that have passed, the BBC has remained committed to educating Britain’s youngsters in the same fields, but never returned to hardware — at least until a few years ago.
In 2012, a small team inside the BBC Learning department began work on a new project aimed at tackling the technology skills gap in the UK. It was the very start of what we now know as the Micro:bit. It was developed with the idea of encouraging children to think about computers and tablets not as things you simply use, but as devices that can be used to create.
The team hacked together prototypes, creating rudimentary circuit boards that demonstrated what they wanted to achieve. But, it looked out of place in a world filled with Raspberry Pis, Arduino boards and other education-focused programmable microcomputers. The BBC knew it couldn’t do it alone, and so had the idea of collaborating with UK partners to put its vision into the hands of one million Year 7 (11- and 12-year-old) students. The response was enormous.
At today’s launch, the BBC counted 29 partners, ranging from manufacturers, software makers, retailers and educators. Microsoft, Samsung, ARM (a company full of executives who cut their teeth on the BBC Micro), the Bluetooth SIG, Element 14, Lancaster University and more have pooled their resources to hold the hands of teachers, children and an emerging young maker community.
Microsoft, for example, has modified its beginner-friendly TouchDevelop platform specifically for the Micro:bit. TouchDevelop lets developers of any skill level create apps for smartphones, tablets or PCs, whether they’re using Windows, Mac, Linux, iOS or Android. For the new initiative, it’ll host the code and projects of all one million developer boards. The Micro:bit supports up to five different programming languages, which include JavaScript, C++ and Block, with Microsoft providing two of them.
The Micro:bit itself hosts 25 red LEDs, all of which can be programmed to display messages, deliver the graphics for games or other feedback. The two push-buttons on its rear can act as inputs for a game controller, or help children create basic rewind and fast-forward buttons on a music player. The built-in accelerometer detects movement, which is perfect for creating programmable “robots,” while a compass tells it which way it’s facing.
Indeed, the BBC’s demonstration area was filled with clever creations. Micro:bits were fixed to all manner of household items, including a frying pan that tells you when to flip a pancake or when your omelette might be burnt. Another company had outfitted a toy car with the BBC microcomputer, letting you drive it around a ready-made track with a smartphone app. One internal BBC project involved modified ping-pong bats that lit up a strip of coloured LEDs when the ball was hit.
The exhibits give a small taste of what is possible with the Micro:bit, but the BBC knows that when the devices reach Britain’s Year 7, the real fun will begin. With a lot of early insight from teachers, the BBC and its partners have created a microcomputer that aligns closely with the curriculum. Before launch, the broadcaster seeded a small number of prototypes to schoolchildren, who created a basic version of Rock, Paper, Scissors, and a pizza tracking bot. With one million units in kids’ hands, the possibilities are infinite.
The BBC’s commitment to openness is key here: the first batch of Micro:bits will reach teachers in September, who will have time to create learning environments ahead of a large-scale rollout in October. Once distributed, the technology will be licenced so companies all over the world can make their own Micro:bits for schools. The BBC has formed a non-profit company to do so, which will also open-source the board’s specifications. Educators will be spoilt for choice: they’ll have access to Raspberry Pis, Arduinos, Micro:bits and others, which can all provide a solid foundation for children to understand more about the technology they use, and perhaps influence the way it’s headed in decades to come.
ICYMI: 3D-printed art, a Pac-Man satellite and more
Today on In Case You Missed It: The giant robot duel challenge response is in from a Japanese mecha-manufacturer (aimed at some lippy Americans with a super paintball gun) and it’s throwing hella shade y’all. Switzerland’s EPFL space agency realized its old cubesats were cluttering up space so it came up with a hungry hippo of a satellite that should start gobbling up its smaller kin by 2018. And an architect hacked a 3D printer with LEDs and is creating beautiful paintings with light.
Today’s happy bonus video is more like a night terror: Google’s Artificial Neural Network is being used to distort images like this scene from Fear and Loathing in Las Vegas. No thanks.
From the cutting room floor: I’m way into the idea of this stretchable mesh that conforms to your body and soothes sore muscles. It didn’t make the cut because there aren’t any videos of the thing, but if you stumble across any similarly interesting clips or stories, we’d love to see them! Just tweet us with the #ICYMI hashtag @engadget or @mskerryd.
Filed under: Cellphones, Misc, Robots, Science, Internet, Google
Galaxy S6 Edge demand is to blame for Samsung’s poor Q2
Earlier in the day we reported on another lacklustre quarter for Samsung’s mobile division, as the company prepares to report its seventh consecutive quarter of declining profits. It turns out that the Galaxy S6 Edge might be to blame for much of Samsung’s weaker than expected earnings.
According to the preliminary report, Samsung is expecting 48.0 trillion Korean won in consolidated sales and an operating profit of 6.9 trillion Korean won, which translate to a 4% decline over Q2 of 2014. As Samsung’s semiconductor and TV business are expected to grow, the blame is being laid squarely at the mobile division. More specifically, sales of the company’s latest flagship smartphones – the S6 and S6 Edge.
Samsung lack of production capacity for the Galaxy S6 Edge’s display have been well documented and the company has been attempting to address the issue for months. However, the problem is not so much that Samsung isn’t able to keep up with Galaxy S6 Edge demand, but rather that the Galaxy S6 Edge has had a direct impact on sales of the regular Galaxy S6.
Samsung was not expecting similar demand for both Galaxy S6 versions
According to sources familiar with the matter who spoke to The Wall Street Journal, Samsung misjudged the type of smartphones that consumers would be after. The company expected to sell four Galaxy S6 handsets for every S6 Edge variant and setup production accordingly. However, demand has ended up being much closer to a 50/50 split between the two.
As a result, Samsung has been left with Galaxy S6 stock that simply isn’t selling. Apparently the white variant is particularly overstocked. Even if the company could produce more Edge units, it would still have incorrectly invested large sums of money into excessive production of the regular Galaxy S6.
Samsung has been left holding lots of Galaxy S6 stock, as customers wait for more S6 Edge production.
Since launch, Samsung is said to have reconfigured its manufacturing operations to help produce as many Galaxy S6 Edge units as are needed. Samsung has previously stated that it would be able to meet demand more accurately by the end of June, which would have just missed out on the Q2 figures.
Sales and profit figures could rebound in the third and fourth quarters, providing that the Galaxy S6’s popularity holds up. Even so, this is likely to be a costly miscalculation for Samsung, which was hoping to improve its profitability this year after the sharp declines of 2014.
What is machine learning?
One area of technology that is helping improve the services that we use on our smartphones, and on the web, is machine learning. Sometimes, the terms machine learning and artificial intelligence get used as synonyms, especially when a big name company wants to talk about its latest innovations, however AI and machine learning are two quite distinct, yet connected, areas of computing.
The goals of AI is to create a machine which can mimic a human mind and to do that it needs learning capabilities. However the goal of AI researchers are quite broad and include not only learning, but also knowledge representation, reasoning, and even things like abstract thinking. Machine learning on the other hand is solely focused on writing software which can learn from past experience.
What you might find most astonishing is that machine learning is actually more closely related to data mining and statistical analysis than AI. Why is that? Well, lets look at what we mean by machine learning.
One of the standard definitions of machine learning, as given by Tom Mitchell – a Professor at the Carnegie Mellon University (CMU), is a computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.
A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.
To put that a bit more simply, if a computer program can improve how it performs a task by using previous experience then you can say it has learned. This is quite different to a program which can perform a task because its programmers have already defined all the parameters and data needed to perform the task. For example, a computer program can play tic-tac-toe (noughts and crosses) because a programmer wrote the code with a built-in winning strategy. However a program that has no pre-defined strategy and only has a set of rules about the legal moves, and what is a winning scenario, will need to learn by repeatedly playing the game until it is able to win.
This doesn’t only apply to games, it also true of programs which perform classification and prediction. Classification is the process whereby a machine can recognize and categorize things from a dataset including from visual data and measurement data. Prediction (known as regression in statistics) is where a machine can guess (predict) the value of something based on previous values. For example, given a set of characteristics about a house, how much is it worth based on previous house sales.
That leads us to another definition of machine learning, it is the extraction of knowledge from data. You have a question you are trying to answer and you think the answer is in the data. That is why machine learning is related to statistics and data mining.
Types of machine learning
Machine learning can be split into three broad categories: Supervised, unsupervised and reinforcement. Let’s look at what they mean:
Supervised learning is where you teach (train) the machine using data which is well labeled. That means that the data is already tagged with the correct answer (outcome). Here is a picture of the letter A. This is the flag for the UK, it has three colors, one of them is red, and so on. The greater the dataset the more the machine can learn about the subject matter. After the machine is trained, it is the given new, previously unseen data, and the learning algorithm then uses the past experience to give a result. That is the letter A, that is the UK flag, and so on.
Unsupervised learning is where the machine is trained using a dataset that doesn’t have any labeling. The learning algorithm is never told what the data represents. Here is a letter, but no other information is given about which letter. Here are the characteristics of a particular flag, but without naming the flag. Unsupervised learning is like listening to a podcast in a foreign language which you don’t understand. You don’t have a dictionary and you don’t have a supervisor (teacher) to tell you about what you are hearing. If you listen to just one podcast it won’t be of much benefit, but if you listen to hundreds of hours of these podcasts your brain will start to form a model about how the language works. You will start to recognize patterns and you will start to expect certain sounds. When you do get hold of a dictionary or a tutor then you will learn the language much quicker.
One of the buzzwords that we hear from companies like Google and Facebook is ‘Neural Net.’
The key thing about unsupervised learning is that once the unlabeled data has been processed it only takes one example of labeled data to make the learning algorithm fully effective. Having processed thousands of images of letters, processing one letter A will instantly label a whole section of the processed data. The advantage is that only a small set of labelled data is needed. Labeled data is harder to create than unlabeled data. In general we all have access to large amounts of unlabeled data, and only small amounts of labeled data.
Reinforcement learning is similar to unsupervised training in that the training data is unlabeled, however when asked a question about the data the outcome will be graded. A good example of this is playing games. If the machine wins the game then the result is trickled back down through the set of moves to reinforce the validity of those moves. Again, this isn’t much use if the computer plays just one or two games. But if it plays thousands, even millions of games then the cumulative effect of reinforcement will create a winning strategy.
How does it work
There are lots of different techniques used by engineers building machine learning systems. As I mentioned before, a large number of them are related to data mining and statistics. For example, if you have a dataset which describes the characteristics of different coins including their weight and diameter then you can employ statistical techniques like the ‘nearest neighbors’ algorithm to classify a previously unseen coin. What the ‘nearest neighbors’ algorithm does it look to see what classification was give to the nearest neighbors and then give the same classification to the new coin. The number of neighbors used to make that decision is referred to as ‘k’, and so the full title for the algorithm is ‘k-nearest neighbors.’
However there are lots of other algorithms that try to do the same thing, but using different methods. Take a look at the following diagram:
The picture on the top left is the data set. The data is classified into two categories, red and blue. The data is hypothetical, however it could represent almost anything: coin weights and diameters, number of petals on a plant and their widths, etc. Clearly there is some definite grouping here. Everything in the upper left belongs to the red category, and the bottom right to blue. However in the middle there is some crossover. If you get a new, previously unseen, sample which fits somewhere in the middle, does it belong to the red category or to blue? The other images show different algorithms and how they attempt to categorize a new sample. If the new sample lands in a white area then it means it can’t be classified using that method. The number on the lower right shows the classification accuracy.
Neural Nets
One of the buzzwords that we hear from companies like Google and Facebook is “Neural Net.” A neural net is a machine learning technique modeled on the way neurons work in the human brain. The idea is that given a number of inputs the neuron will propagate a signal depending on how it interprets the inputs. In machine learning terms this is done with matrix multiplication along with an activation function.
The use of neural networks has increased significantly in recent years and the current trend is to use deep neural networks with several layers of interconnected neurons. During Google I/O 2015, Senior Vice-President of Products, Sundar Pichai, explained how machine learning and deep neural networks are helping Google fulfill its core mission to “organize the world’s information and make it universally accessible and useful.” To that end you can ask Google Now things like, “How do you say Kermit the Frog in Spanish.” And because of DNNs, Google is able to do voice recognition, natural language processing, and translation.
Currently Google is using 30 layer neural nets, which is quite impressive. As a result of using DNNs, Google’s error rate for speech recognition has dropped from 23% in 2013 to just 8% in 2015.
Some examples of machine learning
So we know that companies like Google and Facebook use machine learning to help improve their services. So what can be achieved with machine learning? One interesting area is picture annotation. Here the machine is presented with a photograph and asked to describe it. Here are some examples of machine generated annotations:
The first two are quite accurate (although I am not sure there is a sink in the first picture), and the third is interesting in that the computer managed to detect the box of doughnuts, but it misinterpreted the other pastries as a cup of coffee. Of course the algorithm can also get it completely wrong:
Another example is teaching a machine to write. Cleveland Amory, an American author, reporter and commentator, once wrote, “In my day the schools taught two things, love of country and penmanship — now they don’t teach either.” I wonder what he would think about this:
The above handwriting sample was produced by a Recurrent Neural Network. To train the machine its creators asked 221 different writers to use a ‘smart whiteboard’ and to copy out some text. During the writing the position of their pen was tracked using infra-red. This resulted in a set of x and y coordinates which were used for supervised training. As you can see the results are quite impressive. In fact, the machine can actually write in several different styles, and at different levels of untidiness!
Google recently published a paper about using neural networks as a way to model conversations. As part of the experiment the researchers trained the machine using 62 million sentences from movie subtitles. As you can imagine the results are interesting. At one point the machine declares that it isn’t “ashamed of being a philosopher!” While later when asked about discussing morality and ethics it said, “and how i’m not in the mood for a philosophical debate.” So it seems that if you feed a machine a steady diet of Hollywood movie scripts the result is a moody philosopher!
Wrap-up
Unlike many areas of AI research, machine learning isn’t an in tangible target, it is a reality that is already working to improve the services we use. In many ways it is the unsung hero, the uncelebrated star which works in the background trawling through all our data to try and find the answers we are looking for. And like “Deep Thought” from Douglas Adam’s Hitchhiker’s Guide to the Galaxy, sometimes it is the question we need to understand first, before we can understand the answer!
At just £39, EE’s Rook handset is the UK’s cheapest 4G smartphone
The UK carrier, EE, has released a bunch of own-branded devices in recent months, ranging from the Harrier smartphones and Tab to the 4GEE Action Cam. Not forgetting the Power Bar external chargers that are available for all EE customers. If this isn’t enough, EE has today announced the launch of the Rook, the UK’s lowest priced 4G smartphone.
The Rook is priced at £49 on Pay As You Go for new customers while current EE customers can buy the handset for just £39. Besides 4G connectivity, the Rook offers a surprisingly decent range of specifications.
Specifications:
- Android 5.1 Lollipop
- 4-Inch display with FWVGA resolution
- MediaTek Quad-core processor @ 1GHz, 64-bit
- 1GB RAM
- 8GB Internal storage
- MicroSD card support (up to 32GB)
- 5MP Rear camera
- .3MP Front camera
- 1,500mAh Battery
- 5 Hours talk time
For £39/49, that isn’t a bad phone at all. The Rook isn’t going to challenge the Galaxy S6 or G4 flagship devices, but then it wasn’t designed to. The Rook is a phone with 4G connectivity for those on a budget, possibly a child’s first handset or even a grandparent’s. EE has said that the Rook will be available on both its Pay As You Go plans as well as its corporate accounts. There’s also a 20% discount available on select EE accessories if you purchase a Rook handset. What do you think of the Rook smartphone?
Full Press Release:
EE announces the Rook 4G smartphone
7th July, 2015 – EE, the UK’s most advanced digital communications company, today launched the Rook, the UK’s most affordable new 4G smartphone at just £39 for existing EE customers* and £49 for new EE customers. The Rook is available immediately from EE stores, EE telesales and via the EE online store and will allow a new sector of UK pay as you go customers to enjoy the benefits of superfast 4G.
With 44 per cent of UK pay as you go customers currently spending up to £50 on a handset, the Rook will be the only new handset in this price range to offer a super fast 4G experience – opening double-speed 4G to over 2.5 million UK consumers**.
The Rook runs the latest Android 5.1 Lollipop operating system, and features a 5 megapixel camera, a 4″ high resolution FWVGA display screen and 8GB internal memory, all powered by a fast and energy-efficient 64 bit MediaTek® 1GHz Quad-Core processor enabling faster web browsing, smoother gameplay, quicker multitasking and further improved battery life. The Rook also comes with a 1,500mAh battery, which is good for over five hours of talk time and over 400 hours stand-by-time on a single charge.
Sharon Meadows, Director of Devices at EE, said: “At EE, we believe everyone should have access to 4G and the experiences it offers on the go. The Rook provides a great 4G smartphone at a compelling price – allowing even more people to enjoy the benefits of our superfast mobile network from high-speed web browsing and downloads to gaming and streaming.”
The Rook builds on a range of own branded devices from EE designed to give consumers access to the UK’s fastest network, offering features and specifications traditionally associated with a higher price point.
As well as being on pay as you go, the Rook is available to EE corporate customers – providing a powerful and easily affordable smartphone for customers in medium and large enterprises.
Customers who purchase a Rook handset can also benefit from up to a 20% discount on select EE accessories. Further details on these, as well as more information on the Rook from EE is available at: www.ee.co.uk
Come comment on this article: At just £39, EE’s Rook handset is the UK’s cheapest 4G smartphone
Galaxy S6 and S6 Edge get Android 5.1.1 Lollipop in India
After releasing the latest Android 5.1.1 Lollipop update for Galaxy S6 and Galaxy S6 Edge users in several countries including the US and UK, Samsung has released the update to users in India. The details of the firmware update for the Galaxy S6 (model number SM-G920I) and Galaxy S6 Edge (SM-G925I) can be seen below:
Galaxy S6 Firmware Details:
- Model: SM-G920I
- Version: Android 5.1.1 Lollipop
- Changelist: 5228538
- Build Date: Thu, 25 Jun 2015 08:28:54 +0000
- Product Code: INS
- PDA: G920IDVU2COF8
- CSC: G920IODD2COF8
Galaxy S6 Edge Firmware details:
- Model: SM-G925I
- Version: Android 5.1.1
- Changelist: 5228538
- Build date: Thu, 25 Jun 2015 08:28:39 +0000
- Product code: INS
- PDA: G925IDVU2COF8
- CSC: G925IODD2COF8
The Android 5.1.1 update brings a host of tweaks, including the ability to finally sort apps by alphabetical order in the app drawer. Also on board is exposure control, support for capturing images in RAW format – although Samsung hasn’t yet enabled the feature in the ROM – and multi user support.
Galaxy S6 / Edge in Video:
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The update also lets you finally remove S Finder and Quick Connect from the notifications drawer, freeing up space in what can become a crowded notification area. Other notable changes in the update include the ability to enable or disable the wallpaper motion effect, new modes in the camera app and other under the hood tweaks and changes.
Interestingly, we’ve been using the Android 5.1.1 Lollipop update on the Galaxy S6 Edge and one thing that hasn’t been fixed yet is Lollipop’s aggressive RAM management. As many people have reported, the RAM management on the Galaxy S6 mean many apps are closed in the background and while there were rumours that this would be fixed in the latest update, it hasn’t as yet.
Have you got the update on your phone? What do you think of it? Noticed anything we’ve missed out? Let us know your thoughts below guys and don’t forget to check out the latest Android Authority Podcast where we answer a user question on the 5.1.1 update.
Microsoft re-brands its entertainment apps
As part of the build up to the launch of its latest OS, Microsoft is re-branding its entertainment apps to a more neutral naming scheme.
Gone is the old and confusing Xbox gaming branding for music and videos. I for one approve, I never quite understood why Microsoft was trying to encapsulate its entire media suite under a gaming title.
As part of the change, Xbox Music will be renamed to Groove, because “Groove describes what people feel and do with music,” says Microsoft. Despite the name change, the $9.99 a monthly or $99 yearly subscription for music streaming will remain as it was with Xbox Music, but track purchases will be moving over to Microsoft’s Windows Store. Those with an Xbox Music Pass will automatically be moved over to a Groove Music Pass.
Although the service doesn’t offer free streaming like many of its competitors, Microsoft is planning to update the application with the ability to upload your music collection to OneDrive. Your library will then be available to stream to other Windows devices, Xbox gaming consoles, and even our Android smartphones and tablets in the future.
Xbox Video is also being renamed to a much simpler Movies & TV title. Again functionality remains much the same as before, but Microsoft is adding support for new files formats, such as MKV. Some nifty features include contextual menus for your collections and you can also begin watching content on one devices and then just pick up where you left on another.
Just as with music, film purchases and rentals will be moving over to the Windows Store, so everything will be housed in one convenient location rather than dotted across various applications. Sadly, Movies & TV content doesn’t appear to be heading to Android devices any time soon.
Microsoft is adding the final touches to its store and media applications ahead of the launch of Windows 10 on July 29th, but it remains to be seen if this will help the company compete with some of the established media services already on the market.
Three UK network review (2015): everything you need to know
Three is technically the UK’s second youngest network – having only been formed in 2003 – but considering that the youngest – EE – is made up of the second and third oldest networks – T-Mobile and Orange – many consider Three to be the youngest carrier in the UK. Its age matches its status; while other networks boast vast amounts of capacity at all levels of the spectrum, Three only offers 3G and 4G services, and its 4G network was built with a healthy donation of spectrum from EE following its creation.
Despite being the smallest in the market, Three is owned by one of the world’s largest communications company – Hutchison Whampoa – and its this backing which is allowing it to shake up the market. Let’s take a look at Three UK – the past, present and the future.
Network technology
Three’s network currently uses the following frequencies:
| Frequency | Protocol | Class | |
|---|---|---|---|
| 1800MHz | GSM / GPRS / EDGE | 3G | |
| 800MHz | LTE | 4G | |
Three’s UK network has always been data-focused with the network prioritising the data-capable 3G standard ahead of the voice-focused GSM 2G standard. While other networks offer 2G services as a backup plan, Three’s own network only offers 3G and 4G services but a partnership agreement with EE does mean Three customers can drop to EE 2G coverage when needed.
4G LTE
Three was the last mobile network to offer 4G LTE in the UK and has the smallest capacity, making it susceptible to congestion on the network. The likeliness of congestion is further increased by Three’s primary offering: 4G data at no extra cost.
Top LTE smartphones
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While its rival networks all introduced 4G services at a premium to customers – before almost dropping 3G contracts in their entirety – Three chose to tease its delayed network with a campaign that offers LTE to all customers with no extra premium to pay. Considering that the carrier’s All You Can Eat data proposition had drawn millions of customers looking for unlimited data, the promise of unlimited 4G data – including tethering until the tethering allowances were introduced last year – was enough to draw even more customers to the network.
Its 4G network will operate primarily on the 800MHz spectrum, although this is currently in the process of being rolled out and 4G was switched on using the 1800MHz obtained through the creation of EE. Although limited in capacity, the 800MHz rollout will mean that Three’s indoor 4G coverage is vastly improved; this fact also has telling ramifications for the future of Three, as we’ll touch on later in this review.
Pay Monthly Handsets
Three’s Pay Monthly handset (PAYM) plans offer a range of inclusive allowances, including up to unlimited minutes and unlimited data but the actual plans available and price depends on which handset you opt to go for.
Using the Galaxy S5 as an example, there are thirteen plans available including an unlimited all you can eat minutes, texts and data plan for £44 per month while the Galaxy S6 is only available on four plans, starts at £47.00 per month and costs £56 per month (and £49.00 upfront) for all you can eat minutes, texts and data.
Alongside unlimited 4G data (depending on your plan), the other key perk for Three’s post-paid customers is Feel At Home Roaming (FAH). FAH was the first roaming offer of its kind in the market and allows you to use your inclusive UK minutes, texts and data free of charge in 18 countries around the world.
While Three’s rivals do offer free or subsidised roaming in Europe, Three is the only one to offer completely free roaming outside of Europe, including popular destinations like the USA and Hong Kong. Simply put, Three’s FAH is the best roaming offer in the UK and a key selling point to buying a handset or SIMO from Three UK.
Overall, Three may not offer the bells and whistles that other networks do but what it does do is offer benefits and features its customers actually use. From no worries about going over data allowances to roaming abroad for free, the UK’s smallest network offers one of the biggest and best packages on the market.
Pay Monthly SIM Only
Like every network, Three also offers SIM Only packages for customers who prefer to buy their phones and contracts separately. Almost all of the same packages are available on both 1-month and 12-month contracts, with plans on the latter costing, on average, £3.00 per month less.
Three doesn’t limit its SIM Only plans meaning some SIM Only plans offer All You Can Eat data, although tethering is limited to a maximum of 4GB per month, like Three’s Pay Monthly handset plans. Here’s the current range of available Three SIMO plans:
| Minutes | Texts | Monthly data | 12-month price | 1-month price |
|---|---|---|---|---|
| 200 | All-you-can-eat | 500MB | £8.00/m | Not Available |
| 200 | All-you-can-eat | 2GB | £11.00/m | Not Available |
| 200 | All-you-can-eat | All-you-can-eat | £17.00/m | £20.00/m |
| 600 | All-you-can-eat | 1GB | £11.00/m | £14.00/m |
| 600 | All-you-can-eat | 4GB | £16.00/m | £19.00/m |
| 600 | All-you-can-eat | All-you-can-eat | £22.00/m | £25.00/m |
| All-you-can-eat | All-you-can-eat | 4GB | £21.00/m | £24.00/m |
| All-you-can-eat | All-you-can-eat | All-you-can-eat | £27.00/m | £30.00/m |
Pay as You Go Plans
Like many networks, Three splits its Pay As You Go (PAYG) offering into packs, offering different amounts of minutes, texts and data each month. However, to simplify its offering and make things easier for customers to understand, Three’s 3-2-1 package offers easy to understand call charges for customers who go over their allowances or choose not to use a pack.
3-2-1 is Three’s way of not overcharging customers and the carrier has a big point: if a single minute costs a fraction of a penny, why do some networks charge 40 pence per minute on PAYG? To this effect, 3-2-1 means you’ll pay just 3p per minute, 2p per text and 1p per MB of data if you go over your allowances or don’t have an active pack.
Compared to the competition, 3-2-1 is vastly cheaper (others charge up to 40p, 25p and 35p respectively) and a great reason to buy a Three PAYG plan, especially if you use your handset infrequently. Considering than even PAYG customers get access to 4G without charge and your PAYG credit never expires, the case to choose Three on PAYG is certainly large.
If you do choose to go for a Three PAYG pack, you’ll find there’s only two available; as the 3-2-1 offer is such good value for money, it renders most packs useless. The two plans are:
- All In One 10 Add-on: costs £10, lasts 30 days and gives you 100 minutes, 3000 texts and 500MB of data each month.
- All In One 15 Add-on: costs £15, lasts 30 days and gives you 300 minutes, 3000 texts and All-You-Can-Eat data each month.
If you’re undecided about the packs there’s something worth remembering: while customers using 3-2-1 can’t take advantage of FAH, those with a PAYG pack can; this means if you choose a pack and go to any of the included countries, you’ll be able to use your phone abroad without charge just like post-paid customers.
Overall, Three’s PAYG offer is arguably the best on the market, especially as it offers 4G without charge, gives you unlimited data for just £15 per month and lets you use your phone abroad.
Three Perks
For most customers on Three, the inclusive perks are up to unlimited 4G data and free roaming but Three does have a couple of other benefits it offers to customers.
One of the biggest problems with all networks is being able to use your phone when your phone signal is none existent and Three’s InTouch app aims to fix this, letting any Three customer use a Wi-Fi signal to call and text even when there’s no signal. Usage of the InTouch app is free with calls and texts coming out of your existing allowances and if you do go over your allowance, you won’t be charged any more than the standard rates of your plan.
The other perk to buying a phone from Three on PAYM or PAYG is that unlike other networks, Three phones either come unlocked or the network will unlock them for free without making you wait months after purchase. As an example, other networks charge up to £20 and make you wait up to 12 months to unlock your iPhone, Three will unlock it for free the same day you get the handset.
In a market where the majority of carrier revenue comes from add-on services, Three making it easy to use a different SIM in their phones is certainly refreshing. Overall, Three’s perks are similar to Three as a network; customer focused and offering real benefits as opposed to unuseful benefits.
Quad-Play
The drastic increase in demand for data-driven services has meant mobile networks are encroaching on traditional fixed-line service providers to offer their customers TV, broadband and landline services.
Unlike its chief rivals, Three does not offer any quad-play services to its customers nor has it mentioned any current plans to offer quad-play services in the near future. But it’s likely that Three will eventually enter the quad-play market, especially after the major UK shakeup where the network has a lot to gain.
UK Outlook: Who’s Buying Who?
We’ve been teasing the UK shakeup throughout this review and for good reason; in the biggest shakeup of the market for nearly a decade, Three is set to be the network that gains the most.
There are two major deals that will irrevocably change the UK market: the biggest network, EE, is being bought by one of the oldest communications companies in the world, BT, and Three is set to buy O2, and in turn, establish the UK’s largest mobile communications provider.
Image credit: Huffington Post
As mentioned, Three is currently the smallest network in the UK, but is backed by Hutchison Whampoa (HWL), owned by Li Ka Sheng, who happens to be the richest person in Asia with a net worth estimated to be $31.9 billion.
The buyout of O2 for £10.25 billion (approx. $17 billion) will make Three the largest network in the UK with an estimated user base of nearly 40 million active monthly subscribers. As mentioned earlier, Three currently has a subset of 800MHz spectrum with which to deploy indoor 4G coverage and O2 will complement this, offering the largest allowance of 800MHz spectrum in the UK (as part of a deal it made to offer indoor 4G coverage to 97% of the UK by 2017).
It’s still likely to be 12 months before HWL completes the buyout of O2 and there’s very little known about what this will mean for customers but one thing is certain: Three has managed to make a lasting impression as the UK’s smallest network and once it becomes the biggest, it could dominate the industry for years to come.
Final thoughts
Three’s network has certainly undergone major transformations and improvements over the past few years; at first, the company had the worst coverage in the UK but over the past few years, this has changed drastically and the buyout of O2 will change this status forever.
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From All You Can Eat data to 4G at no extra cost and Feel At Home roaming, there’s a lot for Three to offer its customers and the buyout of O2 will give it a lot more bargaining power. I’ve personally used Three on and off over the past few years and have noticed the changes the network has undergone, with its network now proving a reliable, if not the fastest network.
As a network, Three ticks all the boxes and has enough unique points to make it an intriguing proposition for all customers. Feel At Home roaming and AYCE data alone are enough reasons to draw two segments of the market and with the additional benefits that O2 has to offer (which we’ll touch on in our O2 review on Thursday), Three is definitely a network to watch.
Are you a Three customer? Let us know your views on Three in the comments and don’t forget to vote in our poll below as well.
Note: you can vote in the polls anonymously.
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NASA funds low-cost probes and other futuristic space tech
Low-cost probes, an extraterrestrial submarine and spacecraft propelled by electric sails: these are but three of the seven projects moving on to Phase II of NASA’s Innovative Advanced Concepts (NIAC) program. All the entries have only just begun development, since the program’s specifically meant for early-stage research projects. NASA believes investing in those is crucial “for advancing new systems concepts and developing requirements for technologies to enable future space exploration missions.”
Here are the seven projects that stood out:
-
Swarm Flyby Gravimetry by Justin Atchison of Johns Hopkins University.
Atchison wants to send a big spacecraft loaded with small, low-cost probes to explore asteroids and other celestial bodies. The probes can figure out an asteroid’s/planet’s/moon’s porosity and gravity strength, among other things. -
3D Photocatalytic Air Processor for Dramatic Reduction of Life Support Mass and Complexity by Bin Chen of University of California Santa Cruz
Chen wants to make an air processor that uses titanium dioxide and high-energy light in space to generate oxygen. -
PERISCOPE: PERIapsis Subsurface Cave Optical Explorer by Jeffrey Nosanov of Nosanov Consulting, LLC
If successfully built, this “cave explorer” tool can shine laser pulses into lunar craters/caves while orbiting the moon and measure the amount of light the cave reflects back. It can then use the data it gathers to create an even more accurate map of the moon. -
Titan Submarine: Exploring the Depths of Kraken Mare by Steven Oleson of NASA Glenn Research Center
Oleson plans to use his grant money to develop a submarine made to explore Kraken Mare, the largest sea on Saturn’s moon Titan. -
SCEPS in Space – Non-Radioisotope Power Systems for Sunless Solar System Exploration Missions by Michael Paul of Pennsylvania State University
This project wants to use Stored Chemical Energy Power Systems, which currently powers torpedoes, as energy sources for landers in places without sunlight. -
Trans-Formers for Lunar Extreme Environments: Ensuring Long-Term Operations in Regions of Darkness and Low Temperatures by Adrian Stoica of NASA Jet Propulsion Laboratory
The Trans-Formers concept aims to use heliostats to shine sunlight into extreme environments like the inside of lunar craters. The idea is use the sunlight they redirect to power robots and other machines working within the environment. -
Heliopause Electrostatic Rapid Transit System (HERTS) by Bruce Wiegmann of NASA Marshall Space Flight Center
Wiegmann and his team want to create spacecraft propelled by electric sails.
The agency gave all 15 phase I projects $100,000 each, but those who got into phase II can get as much as $500,000 to fund the development of their ideas within the next two years.
[Image credit: L to R, B. Wiegmann/MSFC, A. Stoica/JPL, S. Oleson, J. Atchison]
Filed under: Science
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