Points Of Convergence

I’ve been studying the Android operating system and ecosystem recently, out of boredom, and one thing struck me as very odd. That is, Google’s AI applies (or is supposed to apply) to Google’s services, but that is not necessarily the case for third parties.

For example, the Calendar app has an option to scan Gmail and extract event information (presumably using clever AI), which is then automatically added into your calendar. However, although the Android Gmail app can now comfortably connect with Microsoft Exchange servers, Android cannot touch email coming out from these.

This is not the case with iOS. Mail.app analyses all email, regardless of where it came from, applies the same algorithms to extract date information, and suggests events to add to the calendar (it will automatically add events if there is an attachment with the “.dat” extension). Mail.app can do this legitimately because everything is done on the device, without sending the emails to Apple servers. (Note that Google is still facing litigation regarding scanning of email for advertising purposes, which questions their scanning non-Gmail originating email.)

From a technical point of view, features like Google Now-on-Tap may allow Google to analyse data that resides in third party services. However, these third parties may be reluctant due to competitive concerns. Furthermore, privacy policies at least in Japan are very sensitive about sending data to other entities. I expect the same policies or at least expectations exist in many other countries as well, and the above Gmail litigation suggests that this is indeed the case.

This means that iOS will be able to analyse and learn (locally) from emails stored in third party servers like Microsoft Exchange, whereas Gmail will not. In other words, the iOS Mail.app can stand at the crossroads where information from multiple sources come together, and learn from each of them. The iOS Mail.app will be able to benefit from being at the point of convergence. On the other hand, Gmail will have to be separated and isolated.

Gartner has reported that only 4.7% of public companies use Gmail for work. This is based on email routing records, and is likely to be quite reliable. Therefore, in terms of the treasure trove of corporate email data, Gmail is mostly insignificant. For Google to really access this information, it most likely needs to move away from cloud computing and towards AI on the device, because the device is where the data converges.

The interesting to note here is that the point of convergence from a purely technical point of view, will not necessarily be where it will be in real life. Whereas technically it makes sense to accumulate all data in the cloud, privacy concerns alone could force convergence to occur solely on the device.

Who Will Win The Next Big Thing?

Many people seem to think that the next big thing in tech will be artificial intelligence, and that Google is much better positioned to win than Apple. Other people think that VR/AR is the next big thing, and again, at least one of the companies that is currently announcing hot new VR/AR gadgets is going to win (and not Apple).

However, history has clearly shown that this discussion is without merit. In fact, when a next big thing does come along, the most unexpected company or a company that simply did not exist before, is the one that actually wins. Very rarely if ever, does the company that invests tons of money on the early stage research emerge as the victor.

Google did not exist yet when Yahoo, Lycos, Altavista and many others were first battling to become the telephone directory of the web. Apple was just a failed PC company that was finding success in music when Blackberry, Palm, Microsoft and Nokia were battling to bring smartphones to the masses. Again Apple was a company that was fighting a losing war against IBM when Steve Jobs visited Xerox PARC which had invested heavily in next generation computing research. Compaq did not exist when IBM introduced the IBM Personal Computer. Microsoft was not even in the OS market when IBM knocked on the door looking for an OS for the x86 CPU.

Time and time again, history has shown that when something really new comes along, the companies that seem to have the strongest position from both market and technical standpoints, are rarely the ones that win in the end. The companies that do win are those that we would not even think about, or the ones that didn’t exist. This is what Clayton Christensen’s Disruption Theory is all about.

Therefore from a historical standpoint, if AI or VR/AR succeeds in disrupting tech, it is actually very unlikely that Google, Microsoft of Facebook would win in the end. These companies are in the exact same positions regarding AI and VR/AR as were Blackberry and Palm prior to iPhone, or as were Yahoo, Lycos and others were prior to Google Search. They have invested heavily into research and also into developing the early market. However, they have not yet discovered the formula that would propel them into the mass market.

No matter how unlikely it may seem today, history is actually quite unequivocal on this. The large and established companies that pioneer an early market, do not reap the rewards when disruption happens and the market goes mainstream. The odds are against Google for winning in AI, and the odds are against Microsoft and Facebook for winning in AR/VR (assuming though that AI and AR/VR do end up being disruptive technologies and not simply sustaining).

Although it is almost impossible to predict what will happen, I will just end this post highlighting a couple scenarios under which the Google might find itself vulnerable for illustrative purposes only.

  1. What if privacy became a block for AI penetrating the mainstream? What if consumers started to feel uneasy with the suggestions that Google’s AI made. What if a data breach at a major internet advertising company made it clear to mainstream customers that far more information was being collected about them than they had ever imagined? What if the technology emerged that made machine learning possible without compromising privacy? Would Google invest in this technology, or would it try to improve the AI results with its current privacy compromising methods? It is likely that Google will invest in the latter, which might be a bet on the wrong horse.
  2. AI could actually become the biggest threat to Google’s business model. What would happen if somebody came along with a good enough AI service which made web search obsolete, and which was combined with a monetisation scheme that was far less profitable than Google’s search advertising? Would Google copy that scheme, or would it wait until it found something that was at least as lucrative as the search business that it was cannibalising? What if this service took off, while Google was still looking for ways to maintain profits?

BYOD And Hardware Sales Growth To Enterprise

In a recent article, Jan Dawson called the enterprise markets “The fastest-growing segment in mature smartphone markets”. Tim Cook had said in 2015 that enterprise markets had seen annual growth of 40% for Apple revenue, and this is indeed massive growth. The magnitude of the revenue was $25 billion annually, only 9% of total Apple revenues in the same period, but nonetheless huge. To put this into perspective, Dell’s peak revenue in 2012 was $62.1 billion annually.

The question is, if corporate adoption of mobile was driven by BYOD, wouldn’t Apple not see revenue growth? If all that was being done was adapting iPhones that the employees already owned to the corporate network, why would Apple see increased sales of iPhones to the enterprise?

My guess is that either of the following is happening in the marketplace;

  1. Despite continued popularity of BYOD, there is a significant portion of employees/employers who prefer to separate work and private devices. Hence purchases of company-owned devices.
  2. The popularity of BYOD itself may be on the decline, due to a shift towards corporate-owned-personally-enabled (CoPE) or choose-your-own-device (CYOD) scenarios.

Either way, it does not seem unreasonable to predict that within a few years time, Apple may be the largest IT hardware vendor to enterprise customers in the world.

Apple’s Hidden Privacy Agenda

Is Apple being reckless?

One observation that some Apple pundits like throwing around is that Apple tends to add features with a broader future implementation in mind. For example, Apple added TouchID initially for unlocking your phone only. Then after a year or two, they added Apple Pay.

Although I think it would be wrong to expect Apple to be doing this for every feature, I do consider it very helpful to keep this in mind. That is, do not dismiss their actions unless you have throughly considered the possibility of a hidden agenda that will only reveal itself a few years into the future.

Apple’s stance on privacy is one of these actions.

  1. Most people have commented that Apple’s focus on privacy will strongly hinder, maybe even cripple their artificial intelligence efforts. This is very dangerous for Apple’s future because it is predicted that artificial intelligence will be a huge part of future personal computing.
  2. The plus side of a privacy focus is that it becomes a selling point for their products. However, we also know that today’s consumers do not care too much about privacy; at least, they seem to be happy to post photos on Facebook and search on Google.

Taking the two points above, it would seem reckless for any tech company to take the privacy position that Apple is holding today. The demerits are huge while the merits look benign. It looks like a totally irrational move for Apple that maybe enforced only because of Tim Cook’s personal beliefs in human rights. It does not make any sense, that is unless Apple has a larger agenda for the future; an agenda in which privacy plays an essential role.

Looking at Apple’s future markets

As I have mentioned previously, Apple cannot grow significantly larger than it is today without expanding into markets outside of tech. The market that tech can directly address, the market to which Apple can sell its current devices, is limited by the size of the economies in the countries which it sells to, and the amount of money each household is willing to spend on communications and entertainment. Apple has to move into different household buckets of spending. Furthermore, these buckets have to be large enough to drive revenue that can significantly contribute to Apple’s huge earnings.

Looking at what households actually spend their money on, one obvious contender is health. US households spend a huge proportion of their income on health, and for the countries which have an adequate healthcare system in place, health is a huge proportion of their government expenditure. There is a lot of money in health, and as populations in both developed and developing countries age, it is only going to get larger.

Apple is already actively involved in health. Not only does Apple have HealthKit, it also has ResearchKit which allows researchers to easily conduct large studies on patients and CareKit which allows patients to track and manage their own medical conditions. Importantly, privacy of health information is taken very seriously (unlike web history or location tracking data), and although I am no expert, it seems that there are rules and laws even in the USA for this.

For any company that seriously wants to get into health, data privacy is a hugely important issue. In particular, IT giants like Google or Apple will be held to higher standards, and expected to develop the necessary technologies if not yet available. They will be scrutinised by not only the authorities, but also by the regular press. If Apple wants to go further into health, prove the value of their services, and to extract revenue from this huge market, then they have to get the privacy issues sorted out first, and apply leading edge technology to protect patient privacy. This will be the prerequisite.

This is where I find Apple’s hidden privacy agenda. Apple does not need to have strict privacy to compete in the tech world against Google and Amazon. In fact, its privacy stance is detrimental for cutting edge artificial intelligence since server hardware will always be much more powerful than tiny smartphones for machine learning, and differential privacy will always negatively impact what patterns can be observed. However, to impact some key non-tech markets that Apple needs to venture into, privacy will be important and essential. Apple’s stance on privacy should be viewed not by which markets they are selling now, but on which markets they intend to sell to in the future.

Doing The Hard Things In Tech

When observing all the mega-hits that Apple has brought to the market the past 40 years, there is one consistent theme. Apple tries to do the things that are considered hard or even impossible at that time.

With the original Mac, they created a GUI-only computer that had a mere 128K bytes of memory. With the iPod, they synced 1,000 tunes (5GB’s worth) to your PC in an age where the predominant I/O (USB 1) was woefully inadequate (and tiny hard drives had just become available). With the iPhone, they shrunk a full blown PC into the size of a chocolate bar. With Mac OS X, they implemented a radically new graphical rendering system (Quartz Compositor) that taxed memory and CPU power and was unbearably slow on the hardware at the time, which only became usable years later with powerful new GPUs (MacOS X 10.2).

In all these cases, Apple was not shy to do something that most people at that time considered very difficult, if not impossible. Sometimes even Apple failed to do it well enough, and suffered the consequences of an inadequate product (low early Mac sales, super slow MacOS X 10.0, 10.1). But in the end, that is why they managed to differentiate, because others had not even started.

Apple’s approach to privacy can be seen in the same way. Whereas the common narrative was that you needed huge servers and massive data sets for good photo recognition, Apple has implemented machine learning on a smartphone that fits into your pocket. Of course they may be taking shortcuts, but so did the Mac 128K. What is important is that they took the challenge while everybody else was doing machine learning the old way (on powerful servers with less regard for privacy). Similarly, Apple has implemented a differential privacy approach which still has no guarantee of success. Even experts in the field are split and some say that the privacy trade-offs between machine learning effectiveness might result in a product that won’t work. Apple made the bet nonetheless. Apple chose to take the hard, possibly impossible way, by hobbling itself with the self-imposed shackle that is a privacy focus. They have thought different.

The simple reason why Apple’s approach has worked even once, is Moore’s law. Moore’s law is the central source of rapid technical progress and disruption, and it makes what is impossible today into something easy to achieve tomorrow.

No one who has seen the progress of silicon would doubt that Moore’s law will eventually make the processing tasks done exclusively on high power servers today, possible on the smartphones of tomorrow. We should also consider that the amount of data collected from smart devices must be growing even faster than Moore’s law (thanks to the shrinking size and ubiquity made possible by Moore’s law in the first place). Tomorrow, we will have many times more data than we collect today, and it is totally possible that the sheer vastness of data will make it possible to infer meaningful conclusions from differential privacy data, even when anonymised under very stringent noise levels.

Therefore, I predict that even though Apple’s approach to privacy may lead to a worse experience for the next couple of years, as Moore’s law kicks in, the difference will end up being negligible. By the time the general public become acutely aware for the need for privacy, Apple will have a powerful solution that in terms of user experience is just as good as Google’s.

The boldness to go all-in on a technology that just barely works, based on the hope that Moore’s law will save them in the next couple of years, is a defining feature of Apple’s hugely successful innovations. This is a formula that has worked for them time and time again.

This is what I see in Apple’s current privacy approach, and this is why I find it so typically and belovingly Apple.

Thoughts on WWDC 2016

Here I want to jot down some of my key thoughts after viewing Apple’s WWDC 2016 keynote.

Core Apps as platforms

We saw a lot of the core apps being opened up to developers. We saw this for Siri, Maps, Messages and even the regular Phone app. Developers can now write code that directly extends the functionality of these core apps. This makes each app its own platform.

  1. This provides a path through which Apple Maps may become much better than Google Maps for many parts of the world. Third parties can innovate on how to provide better shop recommendations/information, transit information, rather then replicating core functionality.
  2. The same can be said of VoIP apps. I have never had a VoIP app that had nearly as nice a UI as the iOS default Phone app. Now VoIP apps can simply focus on providing good connection and voice quality.
  3. Ditto for Siri and Messages.
  4. This approach is only possible in some cases because Apple’s business model does not rely on advertising. For example, Google Maps could have trouble integrating information from Yelp, because this would conflict with their business model of profiting from the recommendations.

Differential Privacy

This is still a bold experiment. It has not yet been proved that this will allow sufficiently advanced artificial intelligence. In the following months, this will be put to the test. Differential privacy may prove to be just as useful as the lax privacy that companies like Google employ.

More importantly in my view though, is that differential privacy will allow Apple to get the most valuable data.

Privacy of health data is considered to be very important, especially genomic data. In genomic experiments using human-derived samples, great care is often demanded to defend the privacy of the donor. Google’s approach would probably be considered too relaxed to entrust such data, whereas Apple’s differential privacy may be sufficient. As a result, people might be very hesitant to give Google their DNA sequence information but not so for Apple (it might even be an FDA recommendation).

If this becomes the case, then Apple will have a huge advantage, not because it has better AI algorithms or more data, but because it has the most valuable data.

The same may occur with many other types of data. If this becomes that case, then Apple may gain preferential access to the more valuable and important data (that is not readily available by spying on your interactions with your phone). This will benefit Apple in the kind of conclusions that its AI will be able to make.

Google’s Justification

At Google I/O 2016, CEO Sundar Pichai showed a future filled with their artificial intelligence (AI).   It is all very interesting, but I do have some questions.

How much data does Google’s AI need?

Google’s AI is backed by enormous amounts of data about us. Data that is collected from photos that are publicly posted onto the Internet, and from photos that we upload onto the Google Cloud services from our mobile phones. Data from our messages on Gmail or events on Google Calendar. Data from the GPSs on our Android phones which tell Google where we are every hour of the day. Data from our browsers which tell Google (often without us knowing it), which website we have been visiting. No other company has access to similar amounts of private information.

However, what has not been answered is how much data Google’s AI actually needs.

Can effective AI be created without too much data?

A recent article by Steve Kovach on Apple’s next generation AI system is very interesting.

Siri brings in 1 billion queries per week from users to help it get better. But VocalIQ was able to learn with just a few thousand queries and still beat Siri.

This suggests that it is possible to construct a advanced AI system with magnitudes smaller data sets; data sets that do not have to be aggregates of private user information, but can simply be collated from a relatively small number of people who were paid for the work.

Of course we need to see the results to be sure. At the same time, I find it interesting that IBM Watson was able to win Jeopardy without tapping into huge data sets like those that Google uses.

Does an intelligent assistant mean you have to give up your privacy?

Apple tries hard not to see your private data. Apple believes that your private data belongs to you only, and that you should be the only one who holds the keys. Many people have questioned this approach, based on the assumption that widespread access to private information from millions of people on the server level is the only way to create a sufficiently good AI system.

Apple’s approach does not preclude the storage and analysis of personal data, as long as it happens in a way that Apple itself cannot see. One way to do this is to handle analysis on the smartphone. This is what the NSDataDetector class in the Mac/iOS API does. It’s actually pretty neat, and Apple has a patent on it. Similar but more advanced approaches could easily be implemented in iOS, given the performance of today’s CPUs.

The question is, is this approach sufficient? Will analysing your private data on your device always be much less powerful than analysing it on the server? Furthermore, will there be a significant benefit in collating the private data from strangers to analyse your own? If so, then Google’s approach (which sacrifices your privacy) will remain significantly superior. If not, then Apple’s approach will suffice. That is, you will not necessarily have to give up your privacy to benefit from intelligent assistants.

Does Google need the data for other purposes?

Let us assume that there existed a technology that allowed you to create an effective intelligent assistant, but that did not require that you give up your personal data. Would Google still collect your personal data?

The answer to this question is quite obviously YES. Google ultimately needs your private information for ad targeting purposes.

Could Google be using the big data/AI argument to justify the collection of huge amounts of private data for ad targeting purposes? I think, very possibly YES.

How Large Can Apple’s Services Grow?

In a recent post, I discussed that Apple has to grow outside of tech to continue growing. I also mentioned that the reason why Google and Amazon continue to grow is because, although they are tech companies, what they are selling is actually non-tech products to non-tech audiences (they are selling stuff like advertising slots, books and diapers).

So even as we see Apple’s services growing at 20%, and that it makes more money from services than from Macs, I think the more important trend to look for is how much they are positioned to earn from non-tech products.

To clarify,

  1. Sales from the App Store are nice, but we have to be aware that the vast majority is from games, and most money comes from a small number of “whales” (online game junkies). It is overly optimistic to expect this segment to continue 20% growth in the mid-term. More likely, we will see a flattening of growth from games and maybe a slight increase do to healthy growth of the non-game segment (which will however not contribute too much to the total).
  2. Music is unlikely to grow rapidly.
  3. Other cloud business (probably mostly additional iCloud storage) may grow rapidly for a short time, but few people really need Terabytes of storage, and prices are likely to drop heavily with competition.
  4. Apple Pay is more interesting because people might use it to pay for all kinds of stuff, including non-tech stuff. It is easy to envision Apple Pay being used to purchase advertising slots, books and diapers for example. We know that VISA has revenues of almost 14 billion USD (and obviously, from its business model, a lot of that is profit).

In summary, to understand the growth potential of Apple’s services, I think it is important to look at the non-tech markets and to see how Apple could add a thin layer of their services on these. Apple Pay is a typical case, but I would not be surprised if they decided to play a more direct role in e-commerce, for example. In the long term, I expect that these will be the main contributors to Apple’s service revenue, not the App nor Music stores.

Update

Matt Richman has done a similar but much better analysis of the non-tech service opportunities for Apple.

Is India Really The Next Big Opportunity In Tech

A lot has been made about how important India is to tech, and what a big opportunity the 1.2 billion population is.

While that maybe true, I think it is also important to contemplate the possibility that this may not actually be the case; that despite its huge population, India may not yet be an attractive investment.

Rakuten Ventures had this to say at Tech in Asia Singapore 2016.

While India has a population of 1.2 billion, there are only about 40 million to 50 million people who actually have “real” smartphones – and not those weird Android permutations – and who are at least in the middle class, earning about US$10,000 a year.

If you’re looking at ecommerce alone, you’re talking about a demographic that has been shrunk from 1.2 billion to 40 million or 50 million. That’s basically the addressable market […] For us, when we look at a market, we ask ourselves: ‘Can we get in at the price point we want? Can we actually see a lot of these platforms accrue the value that they want?’ We don’t see that yet.

Objectively, the International Monetary Fund puts India’s GDP per capita for 2015 at 6,162 international dollars, which is less than half of China’s at 14,107. While obviously growing quite quickly, it isn’t necessarily growing that much faster compared to other countries with similar absolute levels. Although macro data obviously does not tell the full story, it does support Rakuten Venture’s view to a certain extent.

If we do accept Rakuten Venture’s view that ‘while India has a population of 1.2 billion, there are only about 40 million to 50 million people who actually have “real” smartphones’, then it does seem like other markets which aren’t receiving as much hype, might actually hold larger potential.

I think this is something worth thinking about. It might be more important to look at metrics of usage like Web usage or Twitter usage to understand how many people do have “real smartphones”, or use the ones they have as such.

How Large Can Apple Grow

It has long been said that Apple earns more than 90% of all profits in the smartphone hardware business. Apple has also seen the first sales decline for more than a decade. It doesn’t take a marketing genius to see that it will be difficult from now on for Apple to grow this business in the future.

On the other hand, Google and Amazon are continuing to grow their businesses at a healthy rate. What is the difference here?

One perspective is to look at which buckets of spending each companies revenue is coming from. Take a look at the following fantastic chart that I took from The Economist; “How countries spend their money”

NewImage

Although I do have some issue with the figures in this chart (the spending on communications seems much too small, for example), it does illustrate the point that the whole economy is much more than tech. In fact, tech spending by the average consumer is probably only a bit larger than their cell phone bill.

Apple’s business is confined to tech. They only capture the expenditure that a person is willing to spend on communication and recreation. On the other hand, Google carries ads for everything from housing, transport, food transport, to education. Similarly, Amazon can capture a margin for every product sold through retail stores. Apple’s business in only tech, whereas Google and Amazon earn money from the mundane non-tech daily activities and necessities that have been part of the economy for hundreds of years. This is why Apple’s business currently has a hard limit whereas Google and Amazon are in markets that can enjoy growth for much longer. Consider that Google still have a very small portion of total advertising expenditure, and likewise Amazon has only a very small percentage of total retail.

Therefore, unlike Google and Amazon, Apple has to find new markets to enter if they want to continue to grow rapidly. Strengthening their position in tech profits doesn’t help them much if human beings only tend to spend so much on communications and recreation. They must enter markets like housing, transport, education and health. On the other hand, Google and Amazon do not. They just have to worry about being disrupted.

Another thing to note is that Amazon has much more business potential in physical goods than it has in digital. Digital goods like those that Amazon sell only serve the need for recreation and education. On the other hand, their physical goods serve recreation, health, clothing, furnishing and alcohol. These are collectively much larger buckets than the digital goods. It makes total sense that Amazon is not really interested in making money from digital goods, but is instead using them to attract customers for the physical ones.

Of course for Apple, entering new markets is something that it has done quite well in recent years. Recent activities and rumours suggest that it is going to enter transport and health. Its activities in education also should not be ignored. Personally, I would like to see enter housing since the housing market is often the centre of economic turmoil and Apple might do something good about that.