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The Nexus 6P, where the P stands for Premium, was one of the most anticipated and heavily rumored smartphones of this year. It was released on September 29, and is the result of a partnership between Google and Huawei. The new naming convention also shows how the Nexus lineup is now separated into two segments, base (Nexus 5X by LG) versus premium (Nexus 6P). As with any other Nexus device, Huawei’s 6P is the product of a collaboration between different suppliers and due to the central role of Nexus smartphones in promoting the newest version of the Android OS, rumors related to its development stages were closely followed by the Android community.

Looking back to the pre-release months and the final product, these are my thoughts on what I think we should learn from the Nexus 6P partnership.

Information leaks

For the past few months, the Nexus 6P was in the spotlight of information leakers and rumor mongers. Fueled by Huawei’s interest in importing dual edge screens from Samsung, it was even rumored at one point that the Nexus 6P would be released in Q1 of 2016 with a dual edge screen. Although, in the end the leaked CAD images (the blueprints outlining how the device would eventually look) turned out to be accurate, the leaks relating to some of the key components of the device like the SoC, RAM and the camera specs were quite off target. The most frequently articulated rumor was that the Nexus 6P would ship with a Snapdragon 820, 4 GB RAM and 20+ MP camera (which could have been an “overkill” device in 2015). Looking back to the pre-release months, it seems like information leakers have lost a good degree of credibility in terms of the information they were pitching to the Android community.

Nexus vs the OEM’s own flagship

But what of the Nexus 6P itself, have Google and Huawei missed an important opportunity to dominate the market by choosing not to include those “overkill” specs I have just mentioned? Are we actually getting a lesser device?

Generally, Google seems to be happy with its strategy to team up with a different OEM each year to build a new Android flagship Nexus device. While the rest of the products in the premium segment like the iPhone, Galaxy and Xperia series are gradually evolving and being refined from one year to the next, Google is holding its position as a key player by promoting devices which are, unlike the majority of the other devices on the market, not evolving from one generation to the next. This happens because whenever Google changes to a new partner OEM, the design language of the Nexus flagship also changes dramatically. It seems that the idea is to base the new Nexus on the flagship of the partnering OEM, which brings us to the question of a relative specs comparison between Huawei’s flagships and the Nexus 6P.

Last year, there was a general consensus that the Nexus 6 was an upgraded version of the Moto X 2014; simply put, a better SoC, more RAM and greater screen resolution. Although we have to acknowledge that the specs wars are gradually ending, due to market saturation, still one of the key comparisons that we need to make is how the Nexus 6P compares to Huawei Mate S.

The new Nexus 6P comes with a QHD AMOLED screen and a 3450 mAh battery, whereas the Mate S has a HD AMOLED screen with a smaller 2700 mAh battery. Also the 6P sports Qualcomm Snapdragon 810, with four Cortex-A57 cores and four Cortex-A53 cores, compared to octa-core Cortex-A53 Kirin 935 processor in the Mate S.

Other than clear superiority in these domains, the two devices are mostly comparable in terms of the camera specs (for example, the Nexus has larger pixels, but the Mate S has optical image stabilization), RAM capacity; so the differences are more subtle this year and it will boil down to the real-life performance of these devices. Although there are some users who are eager to see another Google-Samsung (or a new Google-Sony) partnership, from a business point of view, this seems unlikely as designing a Nexus phone that is superior than the other key premium flagships in the market would make it highly expensive for the majority of the consumers.

Surely, delaying the release of the Nexus 6P to build a device with superior specs could have been an option, although this could also damage the sales of the Mate S, as it is still the pricier of the two, and also contradict with Google’s well-established timetable to release the Nexus smartphone(s) with the latest version of the Android OS on board, in autumn. Nevertheless, there were some vocal opinions in the Android community, that the Android Marshmallow should be released simultaneously with Nexus 5X; and ideally Huawei’s 6P to follow just a few months later with higher specs. Perhaps, due to the initial set of high spec rumours, the users had greater expectations and simply wanted more killer specs from the Nexus flagship this year.

Here, we need to question whether a delay or putting in higher specs are necessary for market success? In order to understand the decision to not delay the Nexus 6P, we need to look at the wider picture from the perspectives of Qualcomm, Google and Huawei.

Qualcomm

Qualcomm is clearly one of the winners in the Nexus 6P deal

The reputation of the original Snapdragon 810 was damaged by users reporting overheating issues. Following the deal with Sony, for the Xperia Z5 lineup, convincing Google that these issues were solved was a great achievement for Qualcomm, and important for it to hold its market position. So far, Android users seem to be quite excited about the new Nexus device, which means that Qualcomm has managed to ward off the negative publicity associated with the Snapdragon 810, all without renaming the chipset!

Meanwhile, Qualcomm started to promote the Snapdragon 820 chipset (which is clearly superior to 810 in many respects). Due to its market share of available SoC’s for the Nexus (Exynos and Kirin were not really considered seriously), Qualcomm gets a good degree of control over the pace of the market transition and consequently gains a big advantage to optimise its stock discharge for the Snapdragon 810. From this point of view, Qualcomm is clearly one of the winners in the Nexus 6P deal.

Previously, Jayce Broda from Android Authority commented on what the Nexus 6P deal could mean for both Google and Huawei:

So what are the underlying variables in the decision to release the Nexus 6P in Q3 2015, with its current specs, rather than in Q1 2016 with higher specs?

It is well known that Google wants to re-enter the Chinese market and partnering with a well-known Chinese OEM, like Huawei, for the production of the new Nexus flagship is a perfect gateway back to China. The Asian smartphone market is rapidly expanding and being excluded from this market is a great disadvantage for a company like Google, which makes the majority of its revenue from analyzing the big data collected from its users to refine its advertising strategies.

In terms of the value of the Chinese market, we should not be surprised if Google decides to keep on working with Huawei for another year

In the technological landscape of the 21st-century, data is perhaps one of the most valuable and profitable things for a global company. As an anonymous reviewer of other scientists’ scholarly work, sometimes I think to myself, “I wish we had this dataset, we could have made much more out of it”. Similarly, the data from so many users is so rich and has been turned into a profitable business in the hands of Google. The money Google makes in advertising is huge compared to the money it makes from smartphone sales alone. Consequently, any delay in terms of the release of the Nexus 6P would not impact Google’s profits in terms of handsets sales, but it might hamper Google’s growth in terms of big data and advertising.

In terms of the value of the Chinese market, we should not be surprised if Google decides to keep on working with Huawei for another year, which would not only provide it an opportunity to strengthen its roots in China, but also allow it to refine the Nexus 6P in 2016 based on the feedback from the users. For example, the rear camera bump received some initial negative reactions from the public and improving on such aspects could help increase user satisfaction.

Huawei

On the other hand, it is also well known that Huawei wants to gain traction in the European and the North American markets and there couldn’t be a better opportunity than working with Google for the new Nexus flagship. Obviously, increasing the brand recognition sooner rather than later is a key strategy. Although Huawei wants to improve its brand recognition in these markets, it is an interesting observation that Huawei is moving away from using its trademark logo, such as the one which was engraved on the back of the P8, and has opted to just display its name.

It is also well known that Huawei wants to gain traction in the European and the North American markets

Could it be that Huawei’s marketing department thinks that the trademark logo could lead to more scrutiny from potential consumers and work against the company’s long term goals? But surely having the trademark logo on the back, just like the Motorola dimple on the back of the original Nexus 6, would have been a better choice for improving brand recognition, and maybe it would have been more aesthetically appealing, but I guess that is subjective.

The Nexus users

Without any doubt, having different Nexus devices which run the latest version of the Android OS is great for Nexus device owners. Now, there are more options for different tastes. At the same time, consumers who are considering buying their first Nexus device are now faced with the decision of which Nexus handset to buy.

For example, the current price of the original Nexus 6 is now less than the new Nexus 5X and that personal experience has shown me that while the Nexus 6 does feels more exquisite than the original Nexus 5, it is hard to detect a real performance difference in everyday use. So which one is better? It will be an interesting comparison to see how all the Nexus devices stack up against each other while running Android Marshmallow. As far as I know, this kind of comparison hasn’t been done yet to show how these devices stack up against each other. But the key question boils down to whether the new Nexus 6P is $200 more a device compared with the previous generation Nexus 6. To be honest, there is a growing opinion from different, bipartisan reviewers that the answer is No.

In my opinion the other party, which is losing great deal of credibility is the tech reviewers who do not articulate these issues. I don’t find it useful to single out any specific names, but there are reviewers out there who have established themselves (one way or the other), who gives a “BUY” advice to Nexus 6P while saying that they will probably use it for a couple of months (perhaps 3 months?) themselves. Considering that there is no transparency of how much free goodies or funding these people receive from OEMs to talk positively about their devices, I consider their opinions to be hugely flawed; and their advice unethical.

Final Thoughts

It is great to see the Nexus line is expanding in new directions. Considering that, relative to its competitors, Google has less time to work on a new device with the partnering OEM, the Nexus phones are quite successful and longer partnerships with OEMs could only push this further.

In the end, different parties, including the consumers, have a lot to gain from the continuation of the Nexus smartphones; and, as we discussed here, the final product is pretty much shaped by the careful balancing of business strategies with what the users want to see in the next generation.

In this article, I will be covering a recent study published in Nature on robots which can adapt like animals using sophisticated machine learning algorithms and I will discuss what it could mean for us, the common man on the street. For the wider audience, Nature is regarded as one of the most prestigious scientific journals, published since 1869, usually communicating only the cutting-edge research.

Machine learning

As a brief introduction, you might want to watch this video by Gary Sims on machine learning.

Machine learning is becoming a part of our daily lives, particularly through the use of search engines and smartphone applications, where the applications are developing a sense of intuition to predict what kind of services or information we are trying to find.

Robots which can adapt like animals

The article published in Nature, shows how scientists formulated a novel Bayesian learning algorithm, which enabled different kind of robots to recover from bodily injuries. Robots achieve this by performing a series of diagnostic experiments to understand how they should change their behavior to function like a brand-new robot. The digest of this research is nicely summarized in the video from Nature down below, and explains how the robot is mapping the results of its experiments to improve on its sub-optimal behaviour.

At 2:40 minutes, the robot moves like a wounded animal and almost resembles Arnold Schwarzenegger’s T-800 android robot crawling at the end of Terminator 2, after enduring severe bodily injuries. Thanks to the Bayesian optimization algorithm used by the authors, it will become possible for robots of the future to develop a sense of duty to accomplish their missions despite injuries they might suffer during the process. Of course, one should hope that the machines of the future will have a strong sense of duty for human friendly missions, which is emerging as a hot topic of debate (with inputs from people like Stephen Hawking).

An equally important finding of this research is that, the injured robot is shown to identify ways to move even quicker than its uninjured walking speed. This means that the robots of the future could also improve on their design specifications to remove parts of their bodies which they judge to be redundant to improve their efficiency.

Bayesian Learning

So, what is Bayesian learning? Although it may sound technical and sophisticated, Bayesian learning is a model of how people learn from their environments to make optimal decisions and it is based on the foundations of the statistical work done by Thomas Bayes, who lived in England in 18th-century.

It is based on the idea that people make decisions by combining their past experiences (called a “prior”) with the information they collect by observation and update their understanding about the current state of their environment (called a “posterior”). This model is quite intuitive and actually not so difficult to understand. Imagine you decided to quit your current job to work in a new environment. During the first week of your new job, you would be making observations about your new workplace which might have different implicit or explicit rules compared with the previous workplace. But until you feel like you have collected enough observations about your new workplace, you would also partially rely on your previous experiences to make executive decisions and depending on the accuracy of these decisions; you would update your understanding about the current workplace.

For example, a previous influential study showed that a Bayesian observer model makes decisions overlapping with real humans around 76% of the time, which is not so bad, considering that we are notorious for making sub-optimal decisions!

Potential implications for emerging mobile technologies

In the landscape of mobile technology, there are a number of ongoing developments which rely on similar machine learning algorithms in order to provide us with a better user experience. For example, Google’s Now on Tap feature, which is built-in to Android Marshmallow, combines the prediction capabilities of a computer algorithm with data about our search preferences to understand what kind of information we want to get next. Initial engagement with the “Now on Tap” feature seems to suggest that it is not 100% accurate all the time, but this is exactly where the machine learning algorithms will come into play, to improve accuracy by updating the intuitions of the software.

The second line of development is at the hardware front. For example, Google’s self-driving car and Japanese Softbank’s Pepper robot. When they are fully released for commercial use, these automatons, if they have a suitable price tag, may take over some of our daily responsibilities such as driving us to work or helping with house management.

The Bayesian learning algorithms highlighted in the published research would be crucial for these robots to find ways to recover from the potential damages, improving their longevity and reducing the overall maintenance costs for the users. Such abilities would be a must for consumers who are thinking about adopting these novel technologies, but concerned about their longevity, maintenance and price tag. The manufacturers will need to address these issues so that their novel products will be embraced by the market. Although we are probably used to upgrading our smartphones in 12-24 month cycles, longevity and autonomous damage recovery would definitely be an important marketing appeal for these larger and more expensive pieces of hardware.

Potential implications for disaster situations and space science

The final domain in which this robotics can help is in places which are beyond our reach, or for missions too dangerous for humans. In these domains, it is important for robots to have the ability to run diagnostic experiments and find adaptive ways to recover from injuries they might suffer while executing their jobs. For example, the robot that was sent to investigate the state of the reactor in the Fukushima Nuclear Power Plant, following the tragic earthquake and tsunami of 2011, failed to complete its mission because of extremely high levels of radiation (see the footage here), could it has benefited from these new learning algorithms?

What about space exploration to distant and hostile environments? The robots working in these far away places would benefit massively from employing these optimization algorithms. As some of you might already know, Google is promoting a lunar challenge for 2017 to put a rover on the moon and one of the competitors is under development by Audi:

Robots with such adaptive capabilities would help us to help us to push the boundary of the amount of data that we can collect from these ventures. Maybe one day we will have Google “Lunar” Maps, ahead of our potential colonization of our the Moon in the distant future; so that we will be able to study its surface and try to make the most accurate plans for such a day. Maybe along the way, we might also get lucky to have our hands on a a special “Lunar Launch” edition Nexus smartphone with design elements from the rover itself! Previously, Samsung released a limited addition Galaxy S6 Edge with the Iron Man theme; and release of more special edition smartphones would surely translate some of this excitement to the consumers, which would also help with raising public awareness for these cutting edge scientific ventures.

Although machine learning seems like a niche field studied by just a few people, it is in fact a growing area of research and one that will trickle down to touch all of our lives – both at home and far away. As research continues and being translated into the consumer market, we will see changes in our daily lives and we will look back in ten or maybe 20 years from now and wonder at how far things have progressed.

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