open source – Business Architecture & Consultancy BAC

Can Google AMP optimize mobile web?

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Technology has made things faster and easier, smartphones put internet in everyone’s pocket. Mobile has officially eclipsed desktop in terms of usage numbers, and is cementing itself as the go-to platform for connecting, engaging, shopping and general consumption. According to comScore Media’s research, the number of mobile-only internet users has excess desktop-only users in the US since last year. Mobile users tend to be less patient on browsing and surfing, 47% of mobile users expect a web page to load within 2 seconds (Soasta). Advertising and server latency limitation could be burdens for web loading speed. If the user experience isn’t spectacular on these platforms, however, consumers are likely to drop off.

Google together with dozens of other publishers and technology companies launched the Accelerated Mobile Pages (AMP) project in February 24, 2016. AMP is an open-source framework that enables publisher to easily improve speed for their mobile readership without sacrificing any as revenue that they may rely upon. When AMP downloads resources, it optimizes downloads so that the currently most important resources are downloaded first. Moreover, AMP store static content like text and images by caching, so Google can serve them almost instantaneously since the pages are sitting on their servers — servers that are closer and much faster to users. Any changes in content updated within publishers’ CMS will be recognized by Google’s cache in few seconds. Apart from that, AMP compliant content always gets displayed in high priority among the Google search results. Google claims that the loading speed of AMP based web can be 4 to 10 times faster than conventional JavaScript based web.

Google is still optimizing the web-advertising frame in AMP. Majority web ads contains complex author-written JavaScript package, which are excludes from AMP standard web. At this moment, AMP only allow asynchronous scripts to keep JavaScript from delaying page rendering. Therefore, it still leaves publishers in a dilemma of sacrificing part of the advertising revenue or improving customer experience. In other words, if Google AMP is not able to create possibility for more type of ads, the level of acceptance of AMP among small scale publishers, who are mainly supported by advertisement revenue, would be very low.

https://www.ampproject.org

At StarEAST, desktop takes a back seat to mobile

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Why robots did make it into factories but not (yet) in our lives

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robot traffic

Already in the late 70’s robots were to be seen in Star Wars movies, leaving the hint that sooner or later they would be part of our daily lives. Now almost 40 years later from the first movie (1977 to be precise) robots still find their role in society behind the scenes, in the factory where repetitive jobs are fulfilled by those machines. In our lives, we witness a lot of innovation on a yearly basis and we see video’s of Google and Uber trying out their self-driving cars. Yet robots helping us cook, clean, walk or any of those basic daily activities do not make it in our lives. Why not? and how far is the most advanced technology with autonomous robots ?

Read more if you would like to know the answer to those questions.

First off, as humans we are aware of our environment. We realize if something is too hot, dangerous, hard, heavy. It is like we have thousand of different sensors all over our body and with experience we learn how to deal with those situations. It takes us 1 year to stand on our feet, some more years to avoid dangerous situations of any kind that would jeopardize our existence. We can also make decisions very quickly and are very flexible in our movements.

For robots to be in our lives, they should be like us mostly to interact with the same reality and with the same things. If the robot is very small for example, it will never reach the door handle or a high shelf, making it useless of very limited. It could have only wheels, but what happens when there are some stairs?

The most modern robots, tested only in the lab can accomplish the task of walking, riding a car, walk on not flat surfaces and some more tasks, like opening a door, use a drill with much difficulty. This is because the robot does not learn very fast and every time a new color, height or property of a surface appears it might freeze or be unable to stand and fall on the side. The costs of its delicate components make falling extremely dangerous and expensive. Last but not least they are not autonomous. Even though through pattern recognition, a lot of objects can be recognized and more tasks accomplished, the robots are really far from situational awareness, like little babies. They can damage themselves by exerting too much power in a step, fall down and not be able to stand up. In real life they could damage other people as well. Basically, they can do only tasks they are acquainted with in a safe environment, so that if something happens, an operator can take over and fix the issue.

Somewhat of a delusion for many, we will have to wait 10-20 more years before robots will be able to carry out some basic tasks in a safe way and for an affordable price. From a commercial point of view, I think that robots should be used first in homes, where they are somewhat supervised and can carry out simple tasks that still require a lot of time. Other duties such as helping children, elderly people or emergencies (such as putting down a fire) are still too far for the technology or just not commercially viable. But maybe you, as a reader could have more ideas or input on how robots could improve our lives in the short term? Leave a comment !

PS. A nice and short documentary about robots can be found here https://www.youtube.com/watch?v=1wxwSdQpjHk

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Internet connected toys suspected of spying on kids

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Privacy is becoming an issue for the internet of things topic. However, a more unexpected field are internet connected toys. Over 18 privacy groups have been or are filing complaints with the European Union as well as the US Federal Trade Commission concerning Genesis Toys and speech recognition company Nuance for deceptive practices and violating of privacy laws. It is argued that i-Que and My Friend Carla, both pictured, do not only capture voices without notice or approval, it is also not clear what Nuance does with the information that is sent. As an added problem, the organizations are also accusing the companies of not making sure that other Bluetooth connected devices cannot access the toys. Evermore, if not properly managed the speech information that is recorded and sent to nuance could be sold to third parties. There is even another problem that hackers could gain access to these products and the microphones in those devices. Future scenarios could even go as far as “predatory stalking and physical danger”. All in all concerns are plenty, and stakes are high. However, chances are that speech recognition is going to be used more and more in future toys, especially in dolls.

It is unsure yet whether and to what extend the European Union and the US Federal Trade Commission are going to do something about these practices in themselves. It is extra complicated as these products are marketed to kids, who are obviously less able or responsible to manage privacy concerns themselves.

I am curious about how you think about these toys developments. Do you think we should ban them or develop rules? Then again, if we develop rules, how can we enforce them? And in the case of hacking, how should we manage the security of such hardware and the software behind it? Please comment below.

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Creating Compelling Customer Experience through Social Media

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Westerman et al. taught us that a company has to become a digital master to generate more revenue, gain more profit and increase their market value. As you all know by now, this can be reached by improving the digital and leadership capabilities of an organization.

In this blog I will take a closer look to what social media trends an organization must adapt to create a compelling customer experience.

The first one is focusing on social media on mobile. The previous years have shown us that social media on mobile has become more and more important. But for 2017 it is going to be mobile only! The users of Facebook and Twitter come for more than 85% of mobile users, but there are even networks which are mobile only (think of Snapchat and Instagram). So it is important for organizations that they develop webpages which are mobile friendly, to keep the customers satisfied.

The second one is social selling: this trend is spotted at least two years ago, but the consumer wasn’t ready for it yet. More and more social media platforms introduce the direct order options with “Buy now” buttons. See an example of Pinterest in the photo below. For organizations, this trends means that they have to work together with these kinds of platforms. This trend will boost the sales and attract new customers.

And the last trends I want to address are the live videos. In 2017, live streaming will be more important. This means that companies have to be more creative with their updates. Short impressions of the work floor (think of the Coolblue video’s), live instructions, live Q&A and much more direct interactions with the customers.

Adopting these trends will lead in more costs of social media marketing, but this is needed to compete in the very competitive market. At least, that is what I think. What about you?

Resources:

www.shopify.com/retail/4-ways-to-use-pinterest-to-attract-new-customers-boost-sales
www.emerce.nl/achtergrond/dit-d-social-media-marketing-trends-2017
onlinemarketeer.tv

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Deep learning: the new edge of machine learning

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Machine learning has reached a new frontier in technology: deep learning, which is an algorithm inspired by how the human brain works. It is a new way to predict the future and makes machine learning closer to Artificial Intelligence. From a technical perspective, a lot could be discussed to understand the architecture and engineering of deep learning. However, this article aims to describe some applications which rely on this new algorithm.

This new technology arose few years ago, and many tech companies have already made big investments in it to improve some of their products, as self-driving cars. Deep learning is mainly about making better representations and creating models from large-scale unlabeled data: in simple terms, it relies on creating patterns of objects and classifying them based on common features. So far, the most relevant application that deploys deep learning techniques is image recognition.

Image recognition in our daily activities

As of 2012, deep learning allowed computers to recognize traffic signs twice as good as humans. Google made several experiments with it, and was able to map every single location in France in two hours. Facial recognition is also based on this approach: when Facebook is suggesting to tag specific people in the photos that you post, deep learning algorithms are in action. This is completely different from what happens with Google image searches: it is not anymore about grouping pictures based on the text that describe them on a website. It is about actually recognizing the objects in the photo, and grouping photos based on the features characterizing them. Experiments have shown that, when people are asked which caption they prefer, those created by computers win over those by humans.

Image recognition in medicine

Deep learning is having the most disruptive impact in medical imaging. For instance, a company called Enlitic examines millions of images to automatically learn to identify a disease. They are able to generate a new diagnostic test in 15 minutes, and get 90% of classifications right. Recent research not only has made predictions better, but also could create new insights on science. A study from Stanford looked at cancer tissues under magnification and discovered that cells around the cancer are as important as those characterizing the cancer itself: this is the opposite of what pathologists have been told. Many similar discoveries are being done by people who do not even have a medical background, even though the results are potentially changing the world of health. Plenty of new collaborations between medical companies and data scientists will keep on rising, and they may help to build a better world.

Sources

TED talk for Enlitic: https://www.ted.com/talks/jeremy_howard_the_wonderful_and_terrifying_implications_of_computers_that_can_learn#t-667980

Enlitic: http://www.enlitic.com/

Facial recognition: http://www.dailymail.co.uk/sciencetech/article-2958597/Facial-recognition-breakthrough-Deep-Dense-software-spots-faces-images-partially-hidden-UPSIDE-DOWN.html

Deep learning: http://deeplearning.net/

Deep learning: http://www.nbcnews.com/mach/technology/deep-learning-predicts-future-n690851

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Innovation in social media? Forget Facebook!

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Power of social media

In the current digital arena, social networks have touched the lives of almost every human being on earth, allowing us to share life’s novelties with friends and loved ones. However, social networks are not restricted to sharing and commenting on pictures, but giving rise to innovation among individuals to help make our world a better place.

Social media can be an excellent way to reach out to both existing and potential customers and take advantage of their creativity. There are two ways to involve your network in developing new products and services:

Crowdsourcing – asking your network to brainstorm solutions to a particular problem your company is experiencing, either on their own or in groups. The community collects, develops and ranks the contributions to reveal the strongest performers.
Open innovation – allowing people to submit their own competitive ideas and inventions for your company to harness.

Rise of new entrants

With so many minds able to network together, open innovation allow people to work together on a massive scale. Sites such as Facebook and Twitter have already become immensely popular for setting up robust platforms for online communities and many enterprises are using them as an effective medium to innovate. However, today there are very good examples of social networks where niche communities not only find work, but also hire a development team, innovate their business, and collaborate from different corners of the world.

The world of social media might be crowded, but that’s certainly not stopping new players entering the market. The success of Pinterest and Instagram has shown that it’s possible for relative newcomers to make a big impact. And while Facebook may boast close to a billion users, many alternatives are aimed at a more exclusive audience. The drop in organic reach has been apocalyptic for many businesses. Why? There’s too much content on Facebook and the company is forced to ratchet down the reach. We’ll have to either spend a lot more money on Hollywood-quality content, a lot more money on advertising or both. This will force some businesses to reconsider Facebook as a viable channel and enable a migration to less noisy venues.

Source: Cosenza 2016

Future of open innovation

Innovation and idea generation are no longer confined to the boundaries of office buildings now that niche social networks create room for like-minded people to come together and give their input to deal with particular challenges. Idea sharing on a global scale leads to innovative solutions in a shorter period of time. Businesses now also rely on niche social networks for innovative ideas to increase their sales, establish brand value and convert prospective customers into loyal ones.

Without a doubt, social networks posses incredible potential for innovation among individuals from all walks of life. Businesses, non-profit organizations and governments also realize the efficacy of social networks in making this world a better place, which is why they are all using niche social networks to connect with people of similar interests and innovate solutions to deal with specific challenges.

Sources:

Arno Ch. (2012), The rise of niche social networks. http://www.socialmediatoday.com/content/rise-niche-social-networks

Cosenza V. (2016), Social Media Statistics, https://vincos.it/social-media-statistics

Kind. C (2015), 28 Social Media Marketing Predictions for 2015 From the Pros. http://www.socialmediaexaminer.com/social-media-marketing-predictions-for-2015

NIBusinessInfo (2015), Online business networking and social networking. https://www.nibusinessinfo.co.uk/content/using-social-media-support-innovation

Singh M. (2016), How innovation develops among individuals in niche social networks. http://www.innovationmanagement.se/2016/02/11/how-innovation-develops-among-individuals-in-niche-social-networks