Facebook – Lead bullet.

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A problem that humans can’t solve.

  • There is a silver bullet to deal with the fake news issue, but the problem is that Facebook is not even close to being able to produce one and is having to rely on old, ineffective bullets instead.
  • This problem has been around for a while but really came to light in the summer of 2016, following a move to automate the selection of trending stories on Facebook.
  • Simply put, Facebook’s AI is incapable of working out which stories are fake and which are true which led to false stories being highlighted by Facebook as treading.
  • Facebook’s reaction to this problem has been to throw humans at the problem and a Bloomberg investigation has indicated that this is not working well at all.
  • Facebook has outsourced fact checking to PolitiFact, Snopes, ABC News, factcheck.org and the Associated Press for the period of 12 months but this has been problematic.
  • In order to be flagged as disputed on Facebook, two of the contracted organisations have to mark the story as false at which point the number of users seeing the story is cut by around 80%.
  • This manual process takes about three days to complete in many cases, it takes much longer.
  • On Facebook this is effectively useless as many stories will have trended, been seen by millions of users and disappeared again long before the humans can mark the story as false.
  • Consequently, the only way to solve this problem is to have AI that scans stories as they begin trending and can accurately weed out the fake ones.
  • This is where Facebook comes unstuck as RFM research has found that when it comes to AI, Facebook’s position is very weak (see here).
  • This is not because Facebook does not have good employees in this area but merely because it has not been working on it for long enough.
  • I believe that currently, excellence in AI has very little to do with how many big brains one has on the bench but how long one has been crunching the data.
  • This is where Facebook really suffers as it has only been working on AI for a couple of years whereas Google, Baidu and Yandex have all been crunching data for over 20 years.
  • To be fair, Facebook has shown some progress on image and video recognition (see here) but on the recognition and elimination of fake news, I have seen none whatsoever.
  • As a result, I think that Facebook’s contention that there is no silver bullet to deal with the fake news problem is incorrect.
  • There is a silver bullet but the real problem that Facebook has is that it has no idea how to make it.
  • Until it figures this out, it looks to me like the fake news problem is here to stay.
  • This weakness in AI is not limited to fake news but shows up everywhere across Facebook’s services making it the biggest challenge that Facebook is facing.
  • This problem has to be solved properly for Facebook to achieve its long-term potential as a fully-fledged ecosystem offering deep and intuitive services to 2bn+ users.
  • It is based on this that I can make a case for liking Facebook long-term meaning that this has to be fixed at all costs.

Google Pixel – Damage done.

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Software updates won’t fix reputation.

  • The seemingly endless problems with Google’s latest Pixel devices can most probably be completely resolved with software updates, but these will not repair the reputation damage which is likely to keep the few potential buyers that there are at bay.
  • The problems are legion:
    • First, Screen burn in: Because OLED pixels emit their own light (like plasma), they also have the potential to suffer from burn-in.
    • This refers to damage that occurs to pixels where a bright static image has been displayed for too long resulting in a residual ghost image.
    • All OLED screens have the potential to suffer from this problem but through the clever use of software, Samsung has managed to virtually eliminate this problem from its portable devices.
    • Google has no experience with OLED or screen technology in general which has resulted in the bad feedback from users seen.
    • Second, dull colours and blue cast: Since the device made it into the hands of users there have been complaints that Pixel’s OLED is dull with an odd blue cast compared to those in Samsung devices.
    • Third, clicking sounds: There have been numerous reports of clicking sounds coming from the device which is caused by the activation of the NFC receiver.
    • Fourth, audio quality: Some of the recordings that the device makes appear to play back with very poor audio quality.
  • These problems are all surmountable and look to me to have been mostly caused by a lack of hardware experience and the rush to bring the device to market.
  • Consequently, there is a massive software update that Google says will address all of these issues but I think that will not fix the biggest issue of all.
  • This is the damage that has been done to Google’s reputation for building good quality hardware.
  • At the price that Google is charging for its smartphones, there is no real margin for error as it is competing head on with Samsung’s flagships and iPhone 8.
  • I suspect that the end result will be that the Pixel 2 ships much lower volume than it would otherwise have done as there are plenty of very high-quality alternatives.
  • This will put yet another crimp on Google’s ambition to become more vertically integrated and it appears that the best way to get the most value from Google services is still to use them on another device.
  • It comes as no surprise to me that Google continues to generate more revenue per device from iOS than Android.
  • I think what it really needs to work on is fixing the Android user experience on all of the other devices out there as this is how it can close the gap on iOS which could have a significant upward impact on revenues.
  • Until then, I think Google will continue to underperform its Android potential leaving me pretty indifferent to an investment in the shares.

Alphabet, Baidu & Amazon – West vs. East.

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US fares far better than China.

  • Alphabet and Amazon reported very strong results while Baidu struggled to deal with the shift in advertising from search to social media.

Alphabet.

  • Alphabet reported another very strong quarter but the requirement to share some of the spoils with its partners is putting upward pressure on costs.
  • Q3 17A revenue-ex TAC / EPS were $22.3bn / $9.57 compared to consensus at $22.1bn / $8.32.
  • The better than expected profitability was largely driven by the reduction of losses at Other Bets as costs at the fibre init were cut and other investments were more fiscally prudent.
  • Revenues were once again mainly driven by mobile advertising which carries a much higher traffic acquisition cost (TAC) as Google has to share revenue with its partners.
  • This climbed to 23% of revenues up from 21% a year ago.
  • This combined with many fewer rumblings of dissent coming from Android handset makers these days and automakers saying that Google is being nicer to them, leads me to believe that Google is sharing more of the spoils with its long-suffering partners.
  • Alphabet admitted as much on the call mentioning that some of the agreements with its partners had been changed.
  • I suspect that this also has something to do with the prospect of the EU forcing Google to change its business model which is likely to be less severe if its partners are happy.
  • I suspect that this trend is likely to continue and the outlook for Alphabet going into Q4 17 and 2018 remains healthy.
  • That being said, the valuation has kept largely in step with the fundamental improvement in its business leaving me indifferent to the shares.

Amazon.

  • Amazon’s haphazard approach to making money surprised the market once again but I suspect that investments in Q4 17 will once again depress earnings.
  • Q3 17 revenues / EBIT were $43.7bn / $347m compared to estimates of $41.3bn / $223m.
  • It was the unexpected profit that once again lifted hopes that Amazon has become sustainably profitable.
  • As usual it was AWS that drove profits with revenues of $4.6bn and margins of 25.5%.
  • This masked ongoing massive investments outside of the US where losses mounted to $936m (6.8%) from $541m (5.1%) one year ago.
  • I suspect that the vast majority of this is being spent in India where Amazon is absolutely determined not to lose out to local players following its ignominious defeat at the hands of Alibaba in China.
  • This is why I am extremely cautious on the outlook for Flipkart and Snapdeal as Amazon has the financial resources that its rivals lack despite huge investments from Softbank.
  • Amazon is guiding for strong sales in Q4 17 but I think that it could easily miss its profitability forecasts as has become customary.
  • Q4 17 revenues / EBIT are expected to be $56.0bn – $60.5bn / $300m – $1.65bn slightly ahead of consensus at $55.5bn / $1.5bn.
  • Amazon is continuing to grow its revenue base very successfully but I still can’t get comfortable with investing in shares where one is already paying for profitability that remains random and illusive.

Baidu.

  • Baidu reported poor results that triggered a big sell off creating what is probably the cheapest AI investment on the planet.
  • Q3 17 revenues / net income were RMB23.5bn / RMB7.9bn beating estimates of RMB23.5bn / RMB4.4bn but the better than expected profits were driven by a non-operating gain of RMB4.2bn.
  • Removing this and adjusting for tax reveals a much more sombre picture and the reality that R&D spending is outstripping sales growth as these investments have yet to bear fruit.
  • At the same time, the company guided weakly for Q4 17 with RMB22.2bn – RMB23.4bn of revenues expected, again missing estimates of RMB25.0bn.
  • This weak performance came on top of a 7% fall in the total number of advertisers using Baidu to 486,000 raising legitimate concerns around long-term growth.
  • These advertisers are becoming more interested in spending their money on social networking platforms where the likes of Tencent have woken up to the revenue potential that their services create.
  • Consequently, the short to medium term outlook for Baidu remains uncertain which resulted in the big sell off seen following the numbers.
  • However, it is not all bad news as RFM ranks Baidu as No. 2 globally in AI which is currently the most sort after (and hence the most expensive) skillset in the technology industry today.
  • This capability has been created from 20 years of crunching data which has allowed Baidu to create the best digital assistant in China (Duer) as well as the most advanced Chinese autonomous driving offering.
  • Unfortunately, all of these investments have yet to bear fruit in terms of tangible revenues meaning that short-term minded investors will continue to ignore them.
  • This creates an opportunity for those wanting to invest in AI to get into something at a very reasonable price.
  • The issue is that without any visibility on when these investments will bear fruit and the uncertainty around the core business, the right time to make this investment is clearly not now.
  • I have liked Baidu given is relative valuation to its Chinese peers and leadership in AI but these results indicate that it is likely to be very volatile for the next few quarters.
  • Tencent looks like a safer place to be for now.

Tokyo Motor Show – Not invented here.

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Existential challenge ahead.

  • The star of the Tokyo Motor Show is an electric sports vehicle designed by Toyota which has at its heart an assistant that I think neither Honda nor any other automaker has any chance of ever creating themselves.
  • The best hope is for automakers to licence or buy an assistant from elsewhere meaning that it is unlikely to provide them with an exclusive, differentiating product.
  • The problem is that digital assistants require a high level of AI in order to function properly which is a skill that none of the automakers, not even Tesla, posses.
  • RFM has defines three stages of speech recognition (see here):
    • First: High word accuracy.
    • This has largely been achieved by most speech recognition systems, but it is one thing to know what the user said but quite another to know what he meant.
    • Second: understanding what it is the user is asking for regardless of word order or manner of speech.
    • Third: the ability to understand context and circumstance.
    • I think that it is quite clear that not until machine understanding reaches this third stage that voice can have any hope of providing a user interface that would obviate the use of a screen and be really useful in a vehicle.
    • The two leaders in this space (Google Assistant and Amazon Alexa) both rely heavily on screens and both have products with screens either in the market or in development.
  • This is particularly relevant in the automotive industry where for the foreseeable future, the driver will have to have both his hands and his eyes occupied elsewhere.
  • Furthermore, it is clear that all of the user interfaces designed by the car makers, Apple and Google are not appropriate for use in the vehicle.
  • This is a main reason why I think that users still predominantly use their smartphones for digital services in the vehicle meaning that the best infotainment unit is still the one in the driver’s pocket.
  • In my opinion this represents a very serious risk for the car makers long-term.
  • This is because all of the value-added services that they are hoping to provide are likely to be delivered via embedded systems in the infotainment unit.
  • Consequently, unless the vehicle’s embedded infotainment unit can compete effectively with the smartphone, there is a real risk that all of their digital aspirations will come to naught.
  • In this case, the net result is likely to be the big ecosystems taking over the digital experience in the automobile causing the automakers to become little more than handsets on wheels.
  • This is a bleak outlook because I think that the automakers badly need revenue from digital services to help offset the weakness in their traditional business likely to be caused by the migration to electric vehicles.
  • Failure is not an option for those that wish to survive.

Snap – Reality of fad.

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Snap learns a hard lesson.

  • Snap generated plenty of interest around its first hardware product but the fact that more than 50% users wore the spectacles for just 4 weeks indicates that the device was nothing more than a passing fad.
  • To add insult to injury a sizeable number of users got fed up with the glasses after just one week.
  • Snap sold around 150,000 units of the spectacles which was above its initial 100,000 target but the interest that it managed to generate in the first few days fooled it into thinking that it was something more than a fad.
  • When Snap launched the spectacles, it announced that vending machines would pop-up at undisclosed locations a clever strategy that generated long queues to purchase the product.
  • Unfortunately, this development led the hardware-inexperienced Snap to think that it had a hit product on its hands which meant that it ramped up manufacturing orders in anticipation of demand which was never real.
  • Snap has declined to disclose how large its inventories are, but it did say that as of Q2 17, it had irrevocable hardware purchase commitments of $29m related to the spectacles.
  • This will be on top of the inventory that the company already has.
  • I suspect that following launch, the company ramped up its orders to around 500,000 units which assuming 150,000 sold and a bill of materials of $110, would give an unsold inventory of 350,000 units with a total cost of $38.5m.
  • Snap has plenty of cash on its balance sheet ($2.8bn) and so writing down this inventory to $0 will not hurt financially but it is a real black eye for the company’s credibility.
  • Snap has also substantially reduced its resource commitment to hardware which I think spells the end of its efforts to compete in hardware (see here).
  • I have long held the opinion that Snap has no business being a hardware company (which would materially damage its valuation) and should instead concentrate on its core strengths.
  • These strengths are working out innovative ways for users to engage with each other over an instant messaging platform but unfortunately these innovations are very easy to legally copy.
  • Instagram now has a successful habit of copying all of Snap’s best innovations and pushing them out to its much larger user base pretty quickly.
  • This makes it extremely hard for Snap to compete as apps that offer communication are all about the network of users.
  • Metcalf’s Law of Networking states that the utility or value of a network increases by the square of the number of devices attached to it.
  • This would imply that Instagram (4x Snap’s size) should be at least 16x more valuable than Snap meaning that at Snap’s valuation, Instagram makes up more than half of the valuation of Facebook.
  • Instagram is an important part of Facebook, but I don’t think it is contributing more than 50% of Facebook’s value.
  • Hence, I would be inclined to believe that Snap remains meaningfully over-valued.
  • I think that fair value for Snap remains around $12.40 per share which is still 18% below where the shares are today.
  • I still think that negative sentiment could push the shares closer to $10 at which point acquirors could start to take interest.
  • Until then I still see no reason to get involved and would strongly prefer Twitter to Snap Inc.

Google & Amazon – Battle for the home pt. VI

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Opportunities to break in are fast disappearing

  • Google seems to be closing on in launching a Google Home based product with a touchscreen which indicates that Google’s understanding of the smart home user experience is improving quickly.
  • This is bad news for others like Essential (see here) that are looking to compete in this space as both Google and Amazon are starting to make progress on addressing the areas where they have been weak in the smart home.
  • If Google can now improve its position with the developers of smart home products, it will be in a good position to really take the fight to Amazon which still dominates with over 70% share.
  • Earlier this year I identified two major problems with using voice-based digital assistants in the home.
  • These were:
    • First, voice control: RFM research (see here) has found that voice communication with machines is very far from being good enough to work effectively without a screen for output.
    • The issue is that even the best machines are not yet intelligent enough to provide a useful experience using voice-only and often have to fall back to a screen.
    • In Google Assistant’s and Alexa’s case has meant using the screen of a smartphone which is not an optimal experience especially as most voice usage occurs when the hands are busy doing something else.
    • At launch Essential Products had taken this into consideration as its small device (Essential Home) has an attractive looking screen on the top.
    • This looks much better than hideous Amazon Show which seems to have been designed to be a jack-of-all-trades (master of none).
    • I think that Essential hit the nail on the head and its product should optimally fix the single biggest current problem with human machine voice interaction with its integrated screen.
    • However, should Google come up with an attractive take on Google Home but with a screen, I think this will lessen the appeal of Essential Home materially.
    • Second, fragmentation: Despite Amazon Alexa being able to talk to almost everything, the experience has been horribly fragmented.
    • Google Home has been no better and has also suffered from their being fewer compatible devices.
    • The real use case for the smart home is where all elements in the home are aware of each other and can be controlled together.
    • For example, the use should be able to say “I am going to bed” resulting in the doors locking, blinds drawn, heating turned down and so on.
    • Instead each separate device has had to be manually operated and adjusted.
    • With each launching a service called “routines” (see here and here) both Google and Amazon have moved to start addressing this issue.
    • How well these “routines” work remains to be seen but critically, both companies have recognised the biggest problems with their services and are moving to address them.
  • The net result is that the opportunities for small differentiated services to break into this space by doing something better is closing fast.
  • This combined with the fact that developers will be making their devices work with Amazon first (and maybe Google) will make it even more difficult for smaller players to break-in.
  • Market penetration remains very low which means there is still a chance, but new entrants need to act fast as the big players are moving much more quickly than their size would indicate.

Essential Products – Long road home.

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Home is where the heart is.

  • Essential Products is clearly struggling with its Essential Phone which I think will probably lead to it ending up focusing on the smart home only.
  • Essential Products Inc. has used the only competitive weapon it ever really had and has cut the price of its flagship Essential smartphone by 29% from $699 to $499.
  • Those that have already purchased the device will get a $200 credit towards purchasing other devices within the Essential ecosystem such as the 360 camera.
  • There are two major problems with this move:
    • First: it will really annoy fans of the device who paid full price and
    • Second: it is an admission that there is nothing particularly special about this device leaving Essential Products in the same boat as everyone else in terms of competing on price.
  • I see this as a real climb down for the company because competing directly with the Chinese and LG directly on price, it means that the user experience and ecosystem that it spent so much time creating is getting no traction with users.
  • This fits exactly with my previous observation that Essential Products has created a great Google phone and nothing more (see here).
  • Essential’s strategy is to create an ecosystem of products and services around its smartphone that reach into smartphone peripherals and the smart home.
  • In the smart home, I think Essential has a good grasp of the real problems and has designed a product to address these issues (see here) but digital ecosystems are still completely defined by the experience on the smartphone.
  • Essential aims to differentiate in hardware, AI and the cross-device compatibility and consequently to get its innovations in the hands of users, it thinks that it needs a smartphone.
  • The aim with the price cut is obviously to drive volume and user numbers but I suspect that this will put real pressure on its gross margins meaning that the $300m recently raised by the company will erode much more quickly.
  • Furthermore, this action will almost certainly result in a hit to the company’s credibility as it makes much of the message it communicated at the time of launch look hollow.
  • I continue to think that the company has no differentiation in smartphones but its strategy in the smart home looks interesting (see here).
  • Consequently, I can see the smartphone being dropped with all the remaining focus and resources being placed on creating a position in the smart home.
  • This will be easier and said than done as it is up against two companies that sell good products at cheap prices and have both the means and the will to lose money for a sustained period to build the market position they are looking for.
  • Against this, Essential Products has little chance but its hope lies in its understanding of the smart home and moving to address it ways that its opponents are currently failing to do.
  • It has to move fast as both Amazon and Google are showing signs of realizing what it is they are missing in the smart home.

Artificial Intelligence – Go-getter.

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A breakthrough that Facebook badly needs.

  • Google DeepMind has reported substantial progress on one of the big three challenges of AI which is exactly what Facebook desperately needs but is unlikely to achieve anytime soon.
  • DeepMind has been able to build a new Go (AlphaGo Zero) algorithm that relies solely on self-play to improve and within 36 hours was able to defeat AlphaGo Lee (the one that beat Lee Sedol) 100 games to 0.
  • RFM has identified three main challenges that need to be overcome for AI to really come of age (see here).
  • These problems are:
    • First: the ability to train AIs using much less data than today,
    • Second: the creation of an AI that can take what it has learned from one task and apply it to another and
    • Third: the creation of AI that can build its own models rather than relying on humans to do it.
  • In my opinion DeepMind’s achievement represents a huge step forward in addressing the first challenge as AlphaGo Zero used no data at all.
  • I do not think that this represents a step forward against the third challenge as the system of board assessment and move prediction (but not the experience) used in AlphaGo Lee was also built into AlphaGo Zero.
  • Hence, I do not think that this system was building its own models but was instead using a framework that had already been developed to play and applying reinforcement learning to improve.
  • What will really have the likes of Elon Musk quaking in their boots is the fact that AlphaGo Zero was able to obtain a level of expertise of Go that has never been achieved by a human mind (see here figure 3).
  • It is almost as if the use human data limited the potential of the machine’s ability to maximise its potential.
  • That being said, it is one thing to become superhuman at Go and quite another to enslave the human race and so I continue to think that dystopia will continue to be thwarted by Dr. Moore (see here).
  • There have been many other attempts to address the data quantity problem but this is the first one that I have seen that has shown real progress.
  • Many of the other digital ecosystems have been trying to use computer generated images to train image and video recognition algorithms but there has been no real success to date.
  • I suspect that taking what DeepMind has achieved and applying it to real world AI problems like image and video recognition will be very difficult.
  • This is because the Go problem is based on highly structured data in a clearly defined environment whereas images, video, text, speech and so on are completely unstructured.
  • Hence, we are not about to see a sudden improvement in Google’s ability to recognise and categorize images and video (which is already world-leading) but the seeds are clearly being sown that will keep Google a long way ahead of everyone else.
  • This exactly the kind of advance that Facebook really needs to make.
  • This is because I have long been of the opinion that while Facebook sits on a massive treasure trove of data, it has very little idea of what any of it is or what it means.
  • This makes it very hard to spot fake news or offensive content which has been the source of many of Facebook’s most recent problems.
  • It also makes it much more difficult to understand what its users do and do not like and therefore much more challenging to tailor its service accordingly.
  • Finally, it will also make it much more difficult for Facebook to keep up with competition in terms of deep and rich services meaning that its users may begin to spend time elsewhere.
  • This is a breakthrough that Facebook badly needs but unfortunately it is Google that owns the IP meaning that it will be Google services that improve.
  • I continue to think that Google comfortably leads the world in AI but recent stock performance and the resulting high valuation keeps me indifferent to the shares.

Microsoft, Huawei & ZTE – Hardware heaven?

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3 big leaps but with potentially with fatal flaws?

  • Microsoft, Huawei and ZTE have both expanded their hardware ambitions but I question whether enough attention to details has been paid to really make these products really successful.

Microsoft Surface Book 2

  • Microsoft has launched a worthy successor to the Surface Book, substantially upping both the power and the size of the device.
  • Two versions are now available: a 13.5” device and a 15” device and on both, the hinge has been meaningfully reinforced to ensure that the screen does not wobble during typing.
  • Microsoft has included the latest Intel processors as well as graphics from Nvidia to ensure that the performance of these devices is top notch.
  • Both screens detach from the keyboard to become a tablet but it is here where my concerns lie.
  • The single biggest fault of the original Surface Book is the fact that when the screen is detached, the keyboard stops working.
  • In my opinion this removes the best use case for a tablet PC which is to turn it into a portable desktop experience. (see here).
  • This provides both a more productive and a much healthier computing experience.
  • One can attach a separate Bluetooth keyboard to the product, but when the user has already paid up for a great keyboard, this seems to be a slap in the face.
  • It is not clear if this functionality has been enabled on the Surface Book 2 but I think it will make the difference between the perfect product and one that continues to follow the obsolete laptop dogma (see here).

ZTE Axon M

  • After being very rapidly commoditised in audio, ZTE is having another go at differentiation with the launch of a dual screen device not very unlike the YotaPhone.
  • The main difference is that ZTE is using two full colour smartphone displays compared to the YotaPhone whose secondary display uses e-ink for an always on display that consumes no power.
  • The aim here is to provide the screen of a tablet in a form factor that can fit in one’s pocket rather than a back-up for when battery is running low.
  • Google Apps can recognise when the second screen is active and run in tablet mode across the two devices but how this works for other apps is unclear.
  • Furthermore, the screen bezels mean that there is a big black line in the middle of the larger display which will be very distracting.
  • I am a big believer in larger screens on pocket sized devices, but until a single screen can unfold or unroll into a large rigid display that is as good as a tablet, this segment is likely to struggle.
  • This has been tried several times in the past and every time the hardware and software compromises being made to get two screens onto a single device have fatally hurt its appeal.
  • I don’t see how the Axon M will be any different and consequently remain cautious on its outlook.

Huawei Mate 10 / 10 Pro.

  • Huawei launched its 2017 flagship products with both devices sporting edge to edge displays pioneered by Samsung and copied by everyone else.
  • The main difference other than slightly different proportions between the devices, is that the Mate 10 is LCD while the 10 Pro uses OLED.
  • However, the main differentiator that Huawei is going for this year is AI where both devices use the Kirin 970 chip, developed in house at HiSilicon which have an onboard neural processing unit (NPU).
  • The idea is that using AI, Huawei claims to be able to prevent the inevitable performance degradation that occurs on all smartphones after months of usage.
  • This aims to compete with Apple’s Bionic A11 chip that also has an NPU but I don’t think NPUs are particularly difficult to produce.
  • AIs work best on processes that are massively parallel which is why GPUs are so good at running AI.
  • This not very difficult to achieve anymore.
  • What is far more difficult, is the creation of the AIs themselves to improve the user experience and here I think Huawei is badly lacking.
  • Huawei has no real AI expertise to speak of and on its own devices it will be competing against the global leader, Google.
  • Consequently, while Huawei may be able to win some short-term differentiation by providing an optimal place to run AIs, this will swiftly be copied leaving Huawei still struggling for differentiation.
  • To really make it, Huawei has to differentiate through the AIs itself and produce algorithms that provide rich and intuitive enhancements to services running on its phones.

Broadcast TV – Sword of Damocles pt. III.

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OTA broadcast given a second chance.

  • While Netflix and Amazon continue to make inroads into the cable TV subscribing population, the old dinosaur of over-the-air (OTA) broadcast seems to be winning a second lease of life.
  • Over the last 4 years I have been very negative on the outlook for broadcast (OTA and cable) as I have viewed the convenience and lower cost of on-demand viewing as a much better proposition for users (see here and here).
  • However, while this prediction has been largely accurate, what I failed to take into account was the fact the OTA is free (ad supported) which I think is largely what lies behind its renaissance.
  • A standard Cable TV subscription in 2016 cost on average $103.10 per month (Leichtman research group) for which a large number of channels come as a prepaid package.
  • However, in reality, most users watch only a few of those channels meaning that it if they could subscribe to those channels individually, they would be in a position to save a lot of money.
  • This is now becoming a reality as some of the most prized content now belongs to the streaming companies as well as other content creators making their content available as a subscription through the Internet.
  • The most obvious response has been the well documented and accelerating cord cutting by US households unless the cable TV industry takes immediate and drastic action.
  • The other effect appears to have been a substantial recovery in the number of households making use of OTA rather than cable.
  • According to a Nielsen study commissioned by Ion Media, OTA only households has grown by 41% over the last five years to 15.8m households although this may have slowed significantly since 2015.
  • Furthermore, this is not limited to older generations as the median age of households using OTA and not cable is lower at 34.5 years than the total households using TV at 39.6 years.
  • Although the total number of households switching back to OTA-only may have slowed, there has been real growth in households that also have a fast broadband connection (nScreenMedia).
  • This leads me to believe that users (young and old) are increasingly switching off cable and replacing it with a combination of premium streaming services and OTA TV.
  • This allows the user to have access to a wide range of channels, almost all the content he was watching on cable at a much lower price.
  • Consequently, while commentators are cautious on the outlook for TV advertising revenues in 2018 and beyond, I think that they could easily witness a recovery having been stalled for some time.
  • While this gives OTA a reprieve, I still think it needs to act to prevent itself from becoming obsolete in the long-term.
  • The obvious move is to make the entire selection of channels available on a single, free, ad-supported streaming service.
  • That way the valuable spectrum can be re-farmed for a more economically productive use and OTA can ensure that it has a place in the future of the media industry.
  • If it is really sharp, OTA will also seek ways to make its offering available in emerging markets which are highly price sensitive and willing to consume advertising in lieu of paying a subscription.
  • I still think cable TV is going the way of the Dodo but OTA looks like it has been given some time to reinvent itself.