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Languages Platforms

The Significance of AlphaGo: Has a golden age for artificial intelligence just dawned?

In recent years artificial intelligence (AI) has returned to the forefront of technological debate. That debate has moved on from when, and even whether, computers will ever display intelligent behaviour to how smart they will get, how quickly, and what the implications are for society. Although there are multiple approaches to creating AIs, the ones that involve machine learning from large datasets are generally outperforming all others. The results from such systems are often so impressive that large companies are rushing to hire data scientists, collect more data, and apply the latest machine learning techniques to inform their management decision making. Google’s DeepMind team recently demonstrated that without any human in the loop they can build a system that makes complex strategic decisions better than a human expert. Their approach suggests a way forward for building such systems in many diverse fields.

Machine_learning&artificial_intelligence

The game computers couldn’t beat

The announcement from the DeepMind team that their AlphaGo program had defeated the European champion at the game of Go was a highly significant landmark in AI. Not only did they accomplish a long-standing ‘grand challenge’ in AI and surpass rival Facebook’s efforts by an enormous distance, but the way the system works is in many ways very human-like. At first glance it’s easy to dismiss game-playing AI systems as not immediately applicable to real-world problems. The ‘world’ the AI operates in is incredibly simple compared to our physical world – in the case of Go, a 19×19 board where a black or white stone can be placed on each intersection. However, [tweetable]advances in AI from the pursuit of better Go playing programs are already being used[/tweetable] in real-world applications elsewhere. Also, the ‘deep convolutional neural networks’ that AlphaGo uses to ‘perceive’ the board are similar to those currently being employed to push forward the state-of-the-art in image and speech recognition, as well as natural language processing.

It’s different this time

Back in 1997, IBM’s Deep Blue beat the world Chess champion, Garry Kasparov. How is this different? First, Go is significantly more complex than Chess. There are nearly an order of magnitude more moves possible from every position and each move can have a bigger impact on the strength of a player’s position. Second, Deep Blue used a supercomputer and some hand-crafted heuristics to effectively do a brute force search of all reasonable future move combinations to pick the best move to make next. This was nothing like the way a human would play Chess and also not generalisable to other problems.

In contrast to Deep Blue, AlphaGo combines two deep convolutional neural networks with a Monte Carlo Tree Search algorithm to select moves in a way that’s quite similar to the way a human would play. The first neural network, called the policy network, picks a few promising positions for the next move. A human player doesn’t systematically evaluate all possible moves, rather through experience they develop an intuition for moves that should make their position stronger. They would struggle to explain why they selected a specific move over others in many cases. This suggests they’ve developed a model for how to play that exists below their conscious awareness. AlphaGo’s policy network is trained to predict the moves that expert players would make using a dataset of 30 million different positions from real games. The second neural network, called the value network, estimates how strong any given position is. It was trained, simplifying slightly, using the results of the policy network alone playing against itself from 30 million distinct positions. The Monte Carlo Tree Search is then used to look ahead from each move selected by the policy network at the opponent’s likely responses and AlphaGo’s subsequent moves. However, rather than search all the way to the end of the game, the value network is used to evaluate the end position after a sequence of moves. This is also similar to human play, looking a handful of moves ahead to assess the probability of gaining an advantage with each possible move. The lookahead searches are shallow (constrained by the processing power and time allowed for a move) and yet the results are better than existing leading systems that look much further ahead but with much less sophisticated move candidate selection and position evaluation capabilities.

Widely applicable artificial intelligence

This might all still sound a long way from a truly human style of thinking but if we abstract and generalise it slightly then it becomes more familiar. For any goal-oriented behaviour in a complex or changing environment we can assess our current situation versus our goal and generate some options for moving towards the goal. We can then simulate or predict the results of taking those actions and evaluate the new situations we could get into. We choose the option that moves us closest to our goal, or has the highest probability of moving us closer to that goal. This is just a description of iterative planning.

AlphaGo has shown that we can train a machine-learning system to emulate the options a human would select in a relatively-complex environment. If we simulate the immediate results of those selections we then just need to evaluate where we get to with each option. Again: machine learning comes to the rescue. If we can acquire or generate enough data we can train another machine learning system to perform the evaluation. None of this is really a new idea but now it has been demonstrated to be good enough to beat a professional at Go, it’s a fair bet it can be made to work for a huge range of other problems too. This is possibly why it’s such a landmark for AI research. It’s a challenge that until very recently was thought to require a completely new breakthrough in AI and probably another decade of research (and Moore’s Law) to get us there. It turns out the techniques we’ve already invented, when suitably combined, can achieve very intelligent behaviour.

Dawn of a golden age?

There’s an outside chance Go just happened to be a lot easier than we thought, or just unusually suited to these ‘deep learning’ techniques. However, given the progress that’s being made with deep learning on other longstanding AI problems it seems more probable that [tweetable]we’re about to enter a golden age for AI[/tweetable]. In this context it’s interesting to note that AlphaGo beat the European champion a month before Google opened the source code for their TensorFlow deep learning framework (which prompted Microsoft to follow suit with theirs). These open source moves can be seen as part of a land grab for talent and mindshare. The techniques are the subject of published research and efficient implementations are valuable but nowhere near as much as the data required for training and the talent to utilise it. Then of course, Google, Microsoft, Amazon and a bunch of startups will all offer managed solutions for training and running these kinds of framework on their clouds. As the significance of DeepMind’s accomplishment sinks in, more researchers and developers will rush to jump on the machine learning bandwagon and there will be no shortage of tech giants waiting to welcome them aboard.

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Business Tips

Best Practices for a successful IoT Developer Program

Events and training programs are a main component in many IoT developer programs. But just how effective are they?

This infographic sheds some light into the effectiveness of training and events. Insights are based on our Best Practices for IoT Developer Programs report.

Best Practices for an IoT Developer Program
Infographic
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Business

Developer stories: Mobile Development Runs Deep

At VisionMobile, we believe in the people behind the numbers. While it’s important to understand numbers, trends and segments, it’s equally important to understand the people we’re trying to reach with our research. This developer profile is one in a series designed to help us get to know some of the people behind the statistics.

MobileDevelopmentRunsDeep_Levent_Gurses_interview

Developer Profile:
Levent Gurses

Company, job title and duties:
Movel: CEO, developer entrepreneur. Movel is an enterprise development company, and Levent says, “I code on a daily basis because other people are doing the less interesting stuff.”

Country/Area:
Virginia, US

Development Focus:
Movel focuses on mobile, but that’s too easy of an answer. They work on both native and cross-platform apps (iOS, Android, Windows Mobile, Phonegap, and more.) Levent emphasizes that mobile development doesn’t mean just the front-end app. The back end, he points out, is the biggest part of a mobile project, particularly one with multiple front ends. The back end includes key capabilities such as RESTful, secure APIs and identity and transaction management.

Levent explains that when building enterprise apps, most of a mobile app’s back end applies to a Web app/client’s back end as well. As he builds enterprise solutions, he’s able to build a “21st century back end.” Everything that applies to a mobile app backend applies to a Web app as well, bringing Web apps up to speed for 2016.

levent-gurses

Languages used:
While some developers have a specific language they prefer, Levent and Movel use a mix of languages and clients. AngularJS, however, is a favorite. He’s also fond of Google’s Polymer framework and feels it’ll be a standard in 6-12 months … if Google doesn’t shut it down.

While there’s something to be said for using established frameworks and languages, when a new, promising technology comes along, he takes a pragmatic approach. If a new technology provides sufficient promise, he discusses the potential risks and rewards with the client, along with the backup plan. If the client agrees, they’ll try those less established technologies on a new product.

Favorite devices:
As with some people, Levent is frustrated with the Apple ecosystem, and frustrated by Apple. And like many of us, he says, “I can’t live without my IPhone 6 Plus.” But he uses a variety of devices for testing and exploring. He contrasts iOS devices to Android devices like this: “If I want to use a small computer, I’ll use Android. If I want to use a phone, I’ll use my iPhone.”

He also has an Internet of Things (IoT) shop with about 20 Raspberry PIs running office projects like presentations, dashboards, and temperature sensors. The Raspberry PI is his favorite of this genre for “general, light computing power.” In fact, he says, these eliminate the need for desktops in many applications with the open source Raspbian OS. Arduinos, by comparison, are more limited, but useful for training.

They don’t need any Windows computers, he says, since their MacBooks and Macs run Parallels.

Favorite project built recently:
His favorite recent project stands out to him not because of the technology used but because of the solution. Built for an educational nonprofit, the solution streamlines the application process for college. US high school students use the app to more easily apply to multiple colleges.

Favorite tools:
“Nothing can touch the power of the Chrome developer tools,” even simulating slow connections, network traffic and simulated security issues.

But Movel doesn’t lock its developers into a particular toolset. “That’s what’s beautiful about development nowadays … it’s all open unless it’s Adobe (PDF).” Some prefer no IDE at all, others love heavier IDEs. “Use whatever makes you more efficient.”

They do, however, enforce backend standards like Ansible and Docker.

Best developer-related advice ever heard
“Premature optimization is the root of all evil,” commonly attributed to Donald Knuth. He explains, we need to understand the art of creating the minimum viable product that addresses the business problem.

levent-gurses-2

Best developer-related advice ever given
“Get involved in local meetups and hackathons.” He continues, “Here’s what happened to a lot of developers with the Internet. Everything became impersonal, even resumes. But it takes away the joy. Get out to talk with like-minded people to discuss tools and techniques. You’ll learn stuff you wouldn’t come across in your usual stream, be that Twitter, GitHub or other social media. Everyone you follow is likely like-minded. This takes away the coincidences – local encounters, conferences, meetups, hackathons – all give you a chance to get out of your comfort zone.”

This advice applies to not just new but to experienced developers. He counsels to not get too comfortable: instead, build a trusted network of real people you meet and spend time with. “We grow based on our environment and who we know. When we increase the caliber of people we know then we can grow in leaps and bounds.”

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Platforms

Facebook Messenger: All your numbers are belong to us

Facebook started 2016 with the bold claim that it intends to eradicate phone numbers and replace web browsing, but the Social Network has a mountain to climb before Facebook Messenger becomes the centre of our online world.

New-Report_Final

That’s the stated intention of the Zuckerberg empire – to replace all our myriad internet communication systems with one interface.

Facebook claims that its Messenger app has been installed 800 million times, but at VisionMobile our latest research shows that those installations are very much concentrated into the lower end of the market.

If Facebook is going to recruit the shops, taxi companies and airlines it needs to make Messenger a one-stop internet shop it will need to get the app installed across the demographics before Microsoft (with Skype) steps in to take the cream.

[tweetable]Facebook has long known that the days of pokes and personal walls are fast disappearing[/tweetable], and has quite a history in struggling to adapt to whatever the future might bring. Facebook Gifts/Credits/Deals/Questions/Beacon haven’t lit up the future, so now the company is betting on messaging, and value-added messaging platforms.

Such platforms are proliferating in business. The bots that proliferate across Slack and Yahoo Messenger have turned those platforms into much more than messaging, but taking that functionality into the consumer sphere is much harder.

The medium is the Messenger

With that in mind, Facebook Messenger was forked from the main Facebook mobile app back in 2011, but messaging remained possible in the main app until 2014. These days, the Facebook app will notify you that a message has been received, but if you want to read that message then you’ll have to download and install Facebook’s new Trojan Horse.

That analogy isn’t perfect: the horse of Troy was disguised while Facebook has made no secret of its plan to migrate key internet functionality into the Messaging client. If Facebook can’t own the interface to your phone (it tried that), then it will own the interface to the internet, which the company believes will be Facebook Messenger.

The inspiration behind this idea isn’t hard to see. In China, where Facebook/Google/Twitter fears to tread, the competitive market created in their absence has driven huge innovation as companies strive to differentiate themselves with new features and functionality. Every month, 600 million Chinese are using Weixen, Tencent’s WeChat client, to book taxis, check into flights, play games, buy cinema tickets, make doctors’ appointments, and even manage bank accounts, all without touching the web browser.

[tweetable]In China, messaging has become the platform of choice for accessing a wide variety of services[/tweetable], and Facebook plans to replicate that model in the rest of the world – with it owning the messaging platform, obviously.

This process has already started with Facebook integrating Uber into its messaging platform. It’s worth noting that Uber isn’t integrated into the Facebook website, or the mobile client, but into the Facebook Messenger app.

vision_mobile_2

And Uber is just the beginning. As David Marcus, Facebook’s vice president of messaging products, makes abundantly clear: “We can help you interact with businesses or services to buy items (and then buy more again), order rides, purchase airline tickets, and talk to customer service in truly frictionless and delightful ways” – and that’s before Facebook becomes your personal assistant, Facebook M.

“Facebook M” starts listening in to all your conversations to suggest ways it can make your life more, as they say in such circles, “delightful.”

The Facebook wall will be supplanted by the Custom Conversation, providing a personalised interface (colour, style, emojis) for every chat thread. The visual equivalent of a ring-back tone, customised for every caller, will enable you to decide how both sides of the conversation see their interface, unless the other side has other ideas.

Walled garden of Zuck

In Facebook’s brave new world, everything is done through Facebook Messenger, and Facebook takes control of the delivery channel, removing that irritating “Open in Web Browser” which takes so much control away from the Social Network.

But that brave new world is predicated on the idea that people will install Facebook Messenger, rather than relying on the website, and email notifications, to stay in touch. Our research, in partnership with Celltick, looked at the top 10 applications installed on different handsets, and shows that while many low-end handsets do have Facebook Messenger installed, the application is almost invisible in handsets costing more than $200.

In high-end phones, Skype consistently rates top – well above the main Facebook application – and Facebook Messenger isn’t even in the top 10. In handsets costing less than $200, Facebook Messenger rates around four or five – a couple of positions below the main Facebook application, and very close to Skype.

What this means is that those who can’t, or won’t, invest more than $200 in a handset are happily installing Facebook Messenger, while those with a bit more disposable income are refusing to commit.

What it makes abundantly clear is the opportunity this presents to Microsoft. If messaging really is the future of mobile interaction, as Facebook seems to think, then Skype is perfectly positioned to grab the most important demographic.

If Microsoft were half as willing as Facebook to launch into value-added messaging, then it could make Skype into the messaging platform of the future, if indeed users really want such a platform at all.

You can read more in our free report, here (email address required.) ®

Article first published on the Register

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Business

The Internet of Things is about to reshape e-commerce

E-commerce as we know it is about to be fundamentally reshaped, as every connected object in the future becomes a potential commerce channel.

10 mobile commerce 03

Internet of Things – from smart home devices to connected cars – will transform e-commerce and allow it to stretch across the breadth of the customer journey – from awareness, to intent, to purchase. Billions of “things” will double as e-commerce points of sale (PoS), unbundling and extending PoS for e-commerce outside the web, app and product silos controlled by e-commerce players. But how will we get there?

infographic IoT in e-commerce

E-commerce is forecast to continue to grow fast, and m-commerce twice as fast for that matter, the latter poised to reach a value of $600 billion by 2018. The Internet of Things (IoT) is at last leaving the hype phase and is becoming a revenue-creating reality. By 2020, there could be as many as five connected objects per every smartphone user. And by then, the IoT market is set to reach a value of $1.7 trillion.

IoT and e-commerce have until now evolved in parallel. They are now embarking on a common journey where every connected object becomes a potential e-commerce real estate. With IoT, washing machines can now not just deliver detergent just in time by knowing when your supplies run out, they can also recommend the right detergent, based on your usage or type of clothes, on demand. Car makers can recommend where you buy your gas, by understanding your drive journey, availability of gas stations, pricing on-demand discounts, and gas station commission – in fact Google’s Waze does this already. Watchmakers can command a commission from health insurers, as they can monitor your heart rate, temperature, fitness habits and determine what risk zone you are in. Moreover, makers of connected devices can now afford a negative BOM (bill of materials) “à la Dell”, by subsidizing the cost of hardware with the revenues from bundled e-commerce services.

E-commerce is already the biggest revenue generator among mobile developers, yet only a small minority have acknowledged it and few have seized it with both hands. Mobile developers using e-commerce (for physical or digital goods) have median monthly revenues of $1,000-$2,000 compared to a measly $200-$350 median monthly revenue for mobile developers across all revenue models.

Yet, only a small share of mobile developers, 9%, have chosen to work with e-commerce, based on our 9th Developer Economics survey wave of May 2015, of more than 13,000 software developers globally.

We expect however that this number will grow as off-the-shelf fulfilment and payment platforms ease the pain of managing inventory, customers and transactions. Scaling up will become easier and therefore e-commerce a less daunting and more appealing option for an increasing number of developers.

Services such as Dash Replenishment Service (DRS) and Pinterest’s buyable buttons are all early, and telling, examples of the commerce things to come. They show how e-commerce is evolving towards letting customers make purchasing choices based on impulse and context instead of having to browse and select among a myriad of items. They also show how a purchasing decision is vastly simplified when discovery and payment friction has been removed.

The e-commerce of things journey has only started but it will have far-reaching consequences for e-commerce, IoT, and overall how goods and services are consumed in the future. For an in-depth analysis of how developers and IoT are shaping e-commerce, download the free VisionMobile report on the Commerce of Things.

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Tools

The state of UI and Interaction Prototyping tools in 2015

The UI design process has changed radically over the past few years. With the addition of innumerous tools for wireframing and prototyping, designers are spoilt for choice. Which is the best tool to use?

One thing is for sure, static designs simply won’t cut it any more. A designer ought to employ animation and interactive elements to stand-out from the crowd, now more than ever.

Why Prototype?

A prototype is an early sample, model, or release of a product built to test a concept or process or to act as a thing to be replicated or learned from.

The most obvious reason to incorporate prototyping in your design process is the ability to evaluate the interaction pattern before moving to development phase. This is extremely important especially for mobile applications, where implementing an advanced animation or interaction usually takes a significant amount of time compared to desktop websites. Prototyping will solve your design problems before they even arise.

The other major reason is to enhance intercommunication between designers and developers. While an animation might be very clear in the designer’s mind, a developer will often struggle to actually visualise and implement it. That’s where prototyping comes into play. Instead of trying to verbally explain how the UI design should look or feel like, the designer can use a visual prototyping tool to communicate to the development team exactly what they have in mind.

Flow Prototyping

The most basic form of prototyping that every designer needs to know is flow prototyping, which can be used to create an interactive and functional screen-to-screen prototype. Flow prototyping can help showcase a product and thus act as the basis of communication between designers and developers.

What you should look for in a proper flow prototyping tool is ease-of-use, speed, collaboration features (e.g. user/team management, comments), and version history.

Invision & Marvel

For basic screen-to-screen prototyping, the two most popular choices are InvisionApp and MarvelApp. Both apps allow designers and product teams to quickly come up with working prototypes for their web or mobile applications by simply uploading screens (or working designs), adding hotspots and transitions from one page to another, and forming solid prototypes that can be used for collaboration and/or developer handoffs.

invision-screenshot

A large amount of transitions between screens is provided out-of-the-box, therefore allowing users to create high-fidelity prototypes with an extremely easy-to-use interface that requires little to no learning time. It’s worth noting however, that none of these apps provide a way to transition or animate individual elements of the UI (with the exception of the overlay feature of Invision that can mimic such behaviors up to a point).

In terms of collaboration, Invision is a clear winner because of its sharing options, user and team management, project management tools, and moodboards. However, the Invision free plan allows for one project only, as opposed to Marvel which has an unlimited projects free plan and is perfect for designers who are just looking for a tool to get the job done without a price.

UI Design: Advanced Interaction Prototyping

When it comes to advanced screen transitions or in-screen animations and interactions, Invision and Marvel are not enough. Τools like Framer, Principle, Quartz Composer and Form make advanced interaction prototyping easy for designers and developers.

Principle

Principle is probably one of the easiest-to-use tools out there, giving designers the ability to create high-fidelity prototypes in a very short period of time, with the great addition of a timeline viewer for better animation handling. If you’ve ever used Keynote for prototyping, you’ll find yourself at home, with an out-of-the-box “Magic Move” transition as well as a variety of tools for advanced transition handling.

Integration with Sketch is excellent, allowing direct copy-paste of layers and groups, which saves time from importing/exporting particular elements – a time-consuming, repetitive task most designers prefer to avoid.

principle-screenshot

Framer

Framer is one of the most advanced prototyping tools out there, mainly because it’s based on code. Unlike Principle, there is no fancy WYSIWYG editor and Drag & Drop interface.

All the interactions and animations are done through CoffeeScript/JavaScript. This naturally results in a steeper learning curve, but on the bright side it means designers can prototype pretty much anything they like.

http://share.framerjs.com/a0aaba2lyu5l/

Framer has a very strong community and an unending collection of examples and tutorials to learn from, which makes it one of the most solid tools for prototyping for people who aren’t afraid of code. It features integrations for both Photoshop and Sketch, allowing for easy asset importing straight from the designs. Prototypes can be viewed on an actual device as well, like all of the other popular tools out there.

Quartz Composer, Origami, Form

Besides purely code-based tools like Framer, and completely WYSIWYG tools like Principle, there is another set of tools that utilize the so-called Visual Programming or Node based Programming. Tools like Quartz Composer or RelativeWave Form (now acquired by Google) let users prototype through building blocks (called patches) that are connected through noodle-like arrows, in order to describe interaction and transitions between states. Although these tools have a much steeper learning curve than Principle, they also allow for more advanced animations and interactions between states – making them an alternative for code-based tools like Framer.

Summing it up

Product Company Cost Advanced animation features Requires coding skills Overall
Invision Invision Free for 1 project, up to 25$/mo for unlimited No No For quick flow prototypes and simple animations. Good collaboration features.
Marvel Marvel Free with limited features, up to 15$/mo No No For quick flow prototypes and simple animations.
Framer Framer 99$ one-off Yes Yes Very detailed prototypes. Steep learning curve. Based on code (Javascript/Coffeescript)
Principle Principle 99$ one-off Yes No Easy to create prototypes and export video. Uses a Visual/WYSIWYG Editor.
Quartz Composer Apple Free (included in the Xcode Development enviroment) Yes No Very detailed prototypes. Steep learning curve. Based on visual programming (nodes).
Form RelativeWave, acquired by Google Free Yes No Very detailed prototypes. Steep learning curve. Based on visual programming (nodes).

For the majority of designers who want basic UI flow prototyping and team collaboration, Invision or Marvel will cover most of their needs, while requiring little to no time to pick up and enabling them to start prototyping right away. When it comes to more advanced transitions and animations, Principle is an excellent choice, taking into account the exceptional ease-of-use and time needed to come up with a solid result. For even more advanced interactions designers can use either Framer if they’re into coding or a Node-based tool like Quartz/Origami or Form if that type of visual programming appeals to them.

One thing is for sure, modern designers should master prototyping and interaction design as soon as possible. Tools might change, but incorporating rapid prototyping and motion design in their workflow will change their perspective and potential and undoubtedly help them create outstanding experiences.

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Languages

So… is HTML really a programming language?

Earlier this year we polled more than 13,000 developers during our biannual Developer Economics survey (updating now), and 11% of those developers told us that HTML is their primary development language – that’s Hypertext Markup Language to the uninitiated. This response immediately begs the question: can HTML really be considered a “programming language” at all, or if we should consign to being a tool for the layout of JavaScript functions?

promo

Which is your favourite programming language? Take the DE survey and be the judge of which language will sit on the throne.

Developers answering our survey were asked to pick from a list of languages, HTML5 was on that list, along with JavaScript and more-traditional languages including C and Java. Most programmers work in more than one language, so perhaps those who selected HTML5 as their primary language really meant that they were JavaScript programmers who used a lot of HTML? It’s a nice thought, but the idea breaks down when look at those additional languages and see that only 13% of those who said their primary language was HTML admitted to also using JavaScript, so how are these people creating applications?

14% said they also use ActionScript, which can also come wrapped in HTML, but 12% of those primarily using HTML said they also program in C/C++, which is a combination we’re unlikely to see in the same project.

HTML was never designed as a programming language – the original 18 tags permitted the most-basic of layout options. The only interesting tag was the hyperlink itself; the revolutionary concept that created the web as we now know it, the rest are trivial. HTML was based, loosely, on SGML, which is another bastard offspring of XML – the eXtensible Markup Language – but the key word across these is “markup”: all three are intended to provide syntactical data to accompany textual information*, not applications as we know them.

But HTML has come a very long way since then, and has capabilities we would normally associate with a development language. Drag and Drop, Geolocation, and Local Storage, are blurring the line between applications and web sites, allowing cross-platform development where the only way to spot the difference is the title bar at the top of the window (and sometimes not even then), and there are a host of applications which bear testament to the fact that HTML can be used to create real applications.

Zero Lines JS is a fine example. A graphical game, requiring the player to navigate their ship between approaching enemies at increasing speed to a suitably-irritating soundtrack. It might not be the next Watch Dogs, or even the next Candy Crush Saga, but it would be hard to deny that it is a real application and one which (as the name infers) is written entirely in HTML with a few Cascading Style Sheets (CSS).

Less gaudy is the aptly named “You Don’t Need JavaScript for That”, which demonstrates various techniques to accomplish programmatical tasks without recourse to programming languages. Examples include a tabbed panel (bringing content to the front based on the selected tab) and an image slideshow, all done entirely in HTML5.

Purists will moan, of course, that these examples don’t make it a “real” programming language, that HTML is nothing more than a markup language made to enrich documents, and there was a time when that was true. Developers aren’t as hierarchal as they used to be, but those closer to the metal still look down on those who’ve traded an intimate knowledge of the hardware for speed of development. C programmers consider objects to be unnecessary fluff, but concur with users of C++ that anything which isn’t run through a compiler is just improper (and that includes Java with its bytecode nonsense). Java programmers consider anything without proper encapsulation to be faking its object orientation, while JavaScript developers see no reason for strong typing, and consider HTML to be a layout tool.

Meanwhile those versed in Assembler look down from their ivory towers, stroke their beards, and concur that when performance really matters they will always get the gig.

But despite being at the bottom of the heap we can see that HTML5 is being used to create applications, and it must therefore be considered a programming language. We might argue whether validating a filled-out form constitutes an application, but when you can crash a spaceship into an oncoming armada then there’s little room for discussion.

At Vision Mobile we’re currently updating our survey, asking developers what language and tools they’re now using, including those who choose to program in HTML. It will be interesting to see if an increasing number think that the layout tool has evolved, or if a momentary fad is passing. Take a look at the survey, and use the feedback from at the end to let us know how you feel about HTML being included in the list of languages, and what you think might end up on that list next time.

* To be accurate, XML is intended to be a framework from which one can derive markup languages, but that’s not really pertinent here.

 

The Developer Economics survey is now Live.
Have your say in which should be the next most popular programming language and you may win amazing prizes and gear. Discover more.

Categories
Platforms

Self-driving cars are about platforms, not about cars

There is growing consensus that fully autonomous cars will become a reality by 2020. Google self-driving cars have driven over 1.2 million miles. Elon Musk, Tesla CEO, predicted in September 2015 that Tesla cars will have fully autonomous capability in 3 years. Zvi Aviram, CEO of MobileEye, a supplier of self-driving systems to many car makers, expects their technology will support fully autonomous driving by 2019.

Most traditional car makers still see autonomous driving as a feature of the car, rather than a market shift that will open the path to the creation of a completely new winner-takes-all industry. It’s just like PC makers focusing on adding connectivity to their products and missing the transition to the Internet platforms (Google Search, Amazon, Facebook). Or telecom operators focusing on adding always-on fast data connectivity to their networks and missing the transition to the mobile platforms (Google Android, Apple iOS).

Is the same about to happen in the car industry? Are car makers about to miss the transition to transportation platforms in the same way as PC makers missed the transition to Internet platforms and telecom operators missed the transition to mobile platforms?

The future transportation value stack will be very different from the existing automotive industry. It quite remarkable that only two companies, Google and Uber, are present in all layers of the stack that are necessary for creating a dominant transportation-as-a-service platform.

car-platforms-blog-image

The car hardware (the body, the power train, the wheels) increasingly becomes a commodity. Modern cars are good-enough for typical everyday use offering little opportunity for differentiation. Car commoditisation will only accelerate with the transition to electric vehicles. Electric vehicles are much simpler mechanically and easier to make, which opens the gates for new players, including such electronics and Internet services players like Apple, Google, LeTV and even Acer. It’s also notable that Tesla ‘open-sourced” their electric vehicle patents in 2014 pledging not initiate patent lawsuits against anyone who, in good faith, uses Tesla’s technology.

Autonomous driving is about guiding the car along the road, following the rules while avoiding obstacles and crashes. It involves lots of sensors, computing power and sophisticated software, but the most important part here is the ‘data’. Self-driving systems are machine learning systems that are trained to evaluate the environment and make fast decisions on how to react.

The ‘data’ represents all the collective experience learned by multiple cars driving in test and real-world conditions. The more cars you have on the road and the more miles these cars have driven in all possible conditions, the more experienced, safe and precise the self-driving system becomes. Google is undisputed leader here having its fleet of test cars driven over 1 million miles. Tesla’s Autopilot feature introduced in October 2015 on Model S cars will allow Tesla to start training its self-driving system in real-life conditions on tens of thousands of cars.

Uber seem to be behind in terms of putting real self-driving cars on the roads. The company poached 40 researchers and engineers from the Carnegie Mellon’s robotics lab in March 2015 and partnered with University of Arizona on optics research for self-driving cars.

Navigation is about figuring out which roads and streets the car should drive on in order to get from point A to point B. Google is again is a clear leader here with Google Maps and Waze. A consortium of German carmakers (Audi, BMW and Daimler) is trying to uphold an alternative acquiring the Here Maps business from Nokia in August 2015 for $3.1 Billion. Uber also works to create a proprietary mapping platform winning independence from Google and Here Maps. The company acquired San Jose-based deCarta in March 2015, absorbed part of Microsoft Bing mapping assets in June 2015 and has partnered with TomTom in November 2015 to use its mapping and traffic data. (Is Microsoft about to miss the huge opportunity in the future automotive and transportation markets?)

Fleet routing this is where it gets much more interesting. Self-driving cars combined with Uber-style on-demand services make individual car ownership less and less attractive. Some people even claim that hardware-as-a-service is the end game for Tesla. The shared usage models will turn car market into something that looks like a public transport platform, where operators will match in real-time the demand for transportation with the location and the capacity of self-driving vehicles. In other words, fleet guidance is about deciding in real-time where every car needs to go. Which car needs go to a specific pick up point? Shall the car drive to where the demand is expected in the coming 15 minutes? What is the optimal time to recharge or refuel? When and where to go to do the service and maintenance? Where to park, and more.

This is a very complex computational problem to solve at the scale required to support fleets of thousands of self-driving cars. Bill Gurley, one of Uber’s early investors, gives a glimpse into how difficult it is in his blog explaining why UberPool is the new Uber’s “Big Hairy Audacious Goal.” (BHAG). UberPool helps the company to build capabilities that will be directly relevant for the optimal routing of large autonomous fleets.

I’m sure Google is not standing still here as well. Being a machine learning company, it has the scale and the technical depth to become the leader in this space. Add to that real-time bidding capabilities with extremely complex optimisations that Google has mastered for its online ad business. One can even argue that building such transportation platform is the reason for Google’s interest in self-driving cars.

It’s very difficult to see how traditional car makers will be able to compete with software-centric companies in this space.

Finally, the transportation platform is the most intriguing part of the value stack. Moving people around Uber-style is not the only use for self-driving cars. What else can we do with the fully autonomous fleet of robotic vehicles, given that they don’t not have to look as Uber or Google cars of today? These robotic vehicles can be specialized delivery vehicles (see this Domino’s Pizza car as a hint for how they may look like), small delivery drones like Transwheel or StarShip or even autonomous motorbikes, like Motobot by Yamaha.

The number of possibilities and applications for autonomous transportation is mind boggling. No single company, even as nimble and well-funded as Google or Uber, will be able to address all possible needs and use cases by themselves. The recipe for addressing these yet to be known needs and use cases is in plain sight. It is a platform connecting vehicle manufacturers, vehicle operators, service providers and application developers with users (much like Google did with Android).

The platform will harvest permissionless innovation by startups and developers to discover and deploy new services and applications we cannot even imagine today – in the same way that no one could predict Instagram, Snapchat or WeChat on smartphones. Uber already works with developers extending its service into a platform. Google also has a long history of relying on permissionless innovation by developers to win its competitive battles, from Google Maps to Android. It’s only natural that Google will use the same approach to dominate self-driving cars.

It’s still too early in the game to say which companies will dominate the future transportation market. One thing is a safe bet: The future transportation ecosystem will look very different from the existing automotive industry. It will resemble modern technology ecosystems with their platform business models, permissionless innovation by developers, and domination of software-centric companies.

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Business

What we’ve learned by designing 10 developer surveys

The question in question is the question of questions

This week we launched our tenth biannual developer survey – asking thousands of developers around the world what they’re working on and how they’re doing it. If you’re involved in software development, in any way, then go and fill it out – it will only take you fifteen minutes and I’ll wait here while you do.

Answers are easy. It’s asking the right questions which is hard.
Doctor Who – the fourth one

At VisionMobile we spend a lot of time composing questions, especially when we’re compiling a survey like this one. The process sounds easy enough – phrasing 30 questions we’d like answered to provide insight into the developer ecosystem, but it turns out to be a surprising challenge.

promo

For a start we have to create a lot more than 30 questions: the survey tailors itself to ask each person about the industry in which they work, based in the first round of questions. The survey can thus be designed to last around fifteen minutes, but the whole industry can be covered.

Some questions we repeat every six months, choice of language, mobile platforms, and so forth, so we can spot developing trends, but sometimes an old question will need new options as the industry changes. A year ago we added Swift to our language list, and were surprised to see how quickly it had gained popularity, now we’ll be waiting to see if that growth has been sustained and at what cost.

Other questions are created from scratch: the technology behind the Internet of Things might not be entirely new, but the developer interest is. For the first time we’re asking about Open Source in IoT, drilling down to see how this new industry is evolving.

After the questions are written the task is far from over, for once the words are down then the “discussions” can begin. How many options should be listed? Which toolkits are worthy of mention? Whose products should be used as examples? How many IDEs can one developer realistically use? VisionMobile employs experts in many fields; with practical experience developing software and an intimate knowledge of the challenges involved, but like most developers these people are driven by a passion for their subject, and have strong opinions on the tools and techniques they consider important. The survey has to be impartial so we try to ensure that all the experts are equally unhappy, for balance.

Software development is a global industry these days, so the survey has to reach a global audience. Once the questions have been written, discussed, dismantled, and rebuilt to a mutually-acceptable level of dissatisfaction, then they have to be translated into almost a dozen languages, always ensuring that the clarity of the original remains intact.

Designing developer surveys once more

And then it is done. Perhaps not quite a joy forever, as Keats would have it, but certainly a thing of utility. Questions laid out, check boxes ready to be checked, radio buttons ready to be… radioed(?). Everything waiting for the thousands of developers such as you (what do you mean you haven’t done it yet? Get over there now, this minute). They are drawn by the desire to contribute to the project, or get access to some of the results, or win a prize in the draw, or just know that their opinion matters to the companies and organisations which will be referring to the data over the next six months before the whole process kicks off again.

Shakespeare’s Hamlet asserted that “To be, or not to be” was “the question”, but in these days of Continuous Delivery the questions will never end, and we have turn to a pair of Hamlet’s school friends (Rosencrantz and Guildenstern, with the help of Tom Stoppard) to see where that might lead us:

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Business

App Usage Surpasses TV: Traditional Media Companies Slowly Wake Up

We spend a lot of time on our mobile phones (that’s no surprise). But, what’s changing yearly about the way we use these devices? Simon Khalaf, Flurry’s CEO, wrote an interesting post that breaks down the above question and much more:

Last year, on the eve of the sixth anniversary of the mobile revolution, Flurry issued our annual report on the mobile industry. In that report, we analyzed time spent on a mobile device by the average American consumer. We ran the same analysis in Q2 of this year and found interesting trends we are sharing in this report.

After putting the desktop web in the rear view mirror in Q2 2011, and eclipsing television in Q4 2014, mobile and its apps have cemented their position as the top media channel and grabbed more time spent from the average American consumer. In Q2 of 2015, American consumers spent, on average, 3 hrs and 40 minutes per day on their mobile devices. That is a 35% increase in time spent from one year ago and a 24% increase from Q4 2014. In just six short months, the average time American consumers spend on their phones each day increased by 43 minutes.

mobile-time-spent

To put things in perspective, there are 175 million Americans with at least one mobile device. This means that, in aggregate, since November 2014, the US connected population is spending an extra 125 million hours per day on mobile devices. This growth rate is especially astonishing after seven consecutive growth years.

The Browser: Sidelined

Looking at the chart above, today only 10% of the time spent on mobile is spent in the browser, down from 14% a year ago. The rest of the time, 90%, is spent in apps. Effectively, the browser has been sidelined on mobile. This has major implications on the digital industry in general and the content and media industry in particular. Historically, the media industry has relied almost entirely on search for user and traffic acquisition, building entire teams around SEO and SEM on the desktop web. But search engines are predominantly accessed from a browser. If mobile users aren’t using browsers, the media industry will have to look for new approaches to content discovery and traffic acquisition.

The Media Industry: Absorbed by Apps

The chart below takes a closer look at app categories. Social, Messaging and Entertainment apps (including YouTube), account for 51% of time spent on mobile.

app-distribution

Entertainment (including YouTube) grew from 8% of time spent last year, or 13 minutes per day, to 20% of time spent, or 44 minutes per day this year. This is 240% growth year-over-year, or an extra 31 minutes. That is more than the time it would take to watch an additional TV sitcom for every US consumer, every day!

gaming-loses-ground

Messaging and Social apps grew from 28% of time spent last year or 45 minutes per day to 31% of time spent or slightly more than 68 minutes per day this year. This is a 50% year-over-year increase. However, the majority of time spent inside messaging and social apps is actually spent consuming media, such as videos on Tumblr and Facebook or stories on Snapchat. A study by Millward Brown Digital showed that 70% of social app users are actually consuming media. While we can’t correlate the 70% directly to time spent, we firmly believe that media consumption, either articles read in the web view in app, or video consumed in the feeds, constitute the majority of time spent in social apps. This is a big trend and one that will be watched very carefully by traditional media companies. These companies have to adjust to a new world where consumers act as individual distribution channels. The growth in entertainment on mobile proves once again that content is in fact king and is beating the gaming industry in its own game.

The Gaming Industry: Time is Money

The completely unexpected result of our analysis this year is the dramatic decline in time spent for mobile gaming. Gaming saw its share decline from 32% last year (52 minutes per day) to 15% of time spent (33 minutes per day) this year. This is a 37% decline year-over-year. We believe there are three factors contributing to the decline.

  1. Lack of new hits: Gaming is a hit driven industry and there hasn’t been a major new hit the past 6 to nine months. The major titles like Supercell’s Clash of Clans, King’s Candy Crush, and Machine Zone’s Game of War continue to dominate the top grossing charts and haven’t made room for a major new entrant.
  2. Users become the game: Millennials are shifting from playing games to watching others play games, creating a new category of entertainment called eSports. This summer, Fortune named eSports, the new Saturday morning cartoons for millennials. In fact, some of the most watched content on Tumblr is Minecraft videos created and curated by the passionate Minecraft community.
  3. Pay instead of play: Gamers are buying their way into games versus grinding their way through them. Gamers are spending more money than time to effectively beat games or secure better standings rather than working their way to the top. This explains the decline in time spent and the major rise in in-app purchases, as Apple saw a record $1.7B in AppStore sales in July.

What the mobile industry in general and the app industry in particular have achieved in the past seven years is amazing. Flurry now measures more than two billion devices each month and sees more than 10 billion sessions per day. That is 1.42 sessions for every human being on this planet, every day. And that is just Flurry! If there is anything to say about the mobile and app industry it is this: Mobile is on fire and it is showing no signs of stopping.