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This paragraph within an FT article tonight caught my attention. This is directly reminiscent of 2008 when a French Real Estate Fund froze redemptions.
On Tuesday, the pound shed 2 per cent after a handful of large UK commercial property funds froze redemptions by clients, stoking concerns the fallout from last month’s vote in favour of leaving the EU was gathering pace.
The “froze redemption” link goes to this:
Investors have been barred from cashing in their assets in two more big commercial property funds amid widespread disposals of UK assets on fears that the economic fallout from last month’s vote to leave the EU was gathering pace.
Not good. Liquidity is a given in markets, and Sept 2008 looms large. The world economy came to a stop on Sept 15th 2008 when no bank would transact with another bank for bank to bank liquidity transactions. Inter Bank trust broke down that day.
This is why the BoE is making extraordinary amounts of liquidity available but watch for other Central Banks to do the same.
Here is something I wrote in 2007. (Could Facebook Risk becoming another AOL). The context was different, ok, a lot different given that is 9 years ago and I was thinking about Lending Club who were only available within FaceBook, but I believe the conclusion stands. In fact the reality that has shown the shifts over those 9 years towards an open and mobile dominated internet supports the point. No-one has the final answer, because there is no final answer.
FaceBook are chasing their tails.
Here is the thing. AOL which was the US #1 internet source at one point, lost out because its mission was to retain users within the walled garden. It is not the first time this argument has been used but consider …. AOL strategy was all about building tools within their own garden, and as early as the 1990’s they even had their own browser and their own markup language (think proprietary version of HTML). They had their own CD which let you install AOL on your computer. The AOL ‘platform’ was a CD. Platform, tools, apps; the parallels are remarkably close.
How do make a walled garden successful over the long haul? How can you make people remain within a walled garden without them being constantly bombarded by “grass is always greener” incentives that is the internet today.
The graphic below is a chart of active users on different social networks. If we dig behind the words “social network” what we are looking at his how people communicate with friends and relatives, or at least that is how the “social network” got its name. Meanwhile along the way in an effort to make money, advertising is introduced and co-incidentally people seek different models, whether simplicity, lower bandwidth, mobile friendly, ad-free, etc..
One striking aspect of the names on the graphic below is that they all have different models, different ways to engage people, and most distinctively different was to adapt to mobile. Who will be there in 2025? How will that list look in 2025?
So reading this Techcrunch story today which is one of a succession of initiatives by FaceBook to adapt to the AOL problem just makes we wonder.
It seems to be that time again where we are on the cusp of a shift in internet behaviours and platforms.
I have been noting themes in my reading over the past few months, and two recent pieces in particular solidified them for me. Mary Meeker report, State of the Internet that I referred to a few days ago, and several recent articles by Ben Thompson.
The broad themes are:
1. Chat (as in texting) as an interface.
2. Natural Language Processing (NLP) (as in speaking) as an interface.
If we think about it, these directions are entirely rational especially #1. Over the last 10 years mobile has grown and grown with certain obvious characteristics.
– connectivity by mobile is not always perfect
– web on mobile is spotty especially with ads taking 10% of the screen
– everyone has a phone
– not everyone has a laptop or at least not handy
– the single largest use of mobile is chat – it is low bandwidth, fast, easy and simple.
So if we take the single most used method on mobile, why not make it the interface for other things such as search, shopping and banking. Here is a well explained piece on ChatUI for Banking. Watch for Apple maybe opening up iMessage to Android later today.
Siri has been around for 5 years, and not exactly getting many excited so far. Google/ Android are pressing on this UI now. However Apple have recently purchased a new company which has made express improvements in NLP with better understanding of accents (something I value) and picking out sounds despite background noise.
Enter Amazon Echo and they may have caught everyone by surprise with the Echo. Integrated hardware, speaker, powerful NLP and which has the power of Amazon.com suggests they are on to a winner. It may be a stretch to suggest that Echo killed the Google Nest strategy, but it has to be fair to say the Nest strategy has now been refined to the “Home” strategy, and Amazon Echo success must take some significant credit here. Echo makes a point of differentiating between voices in the home and learning over time. The power of Amazon cloud comes to bear here; once Echo is in the home, that home is now part of the Amazon cloud and both can learn from that. Something that held up Siri is that vehicle use is the only practical one so far. Introduction of Home as a user platform takes voice to a whole new level.
Lastly the drive by large tech towards AI will support both these interfaces, and in fact is a requirement for complete success.
Relevance to Bankwatch:
Watch for Chat and Natural Voice Processing as a user interface that will become prevalent and I would predict will overtake web browsing as the primary access to internet over next 2 – 3 years.
The Mary Meeker annual report is always fascinating and full of facts for the wonks amongst us.
This particular slide pasted below from the 2016 report is one of the better I have seen at quickly summarizing the large generations and their value differences; in particular the financial view of the world which is very different between Boomers and Millennials.
I watch and listed to Google I/O today. The stuff about the new communications app Allo and new emojis was a bit underwhelming but I sensed a deliberate shift under the guidance of SEO Pinchai towards commercialization with the likes of Google Home coming this year. This is going right after the Amazon Echo market, no doubt with a view to address and expand upon the earlier narrow view exemplified by the Nest purchase.
But one comment from Pinchai on “Move 37” came closer towards the end of I/O struck me as prescient with regard to Artificial Intelligence (AI) and that hooked me.
If you want to now more about the status and implication of AI, I recommend this two piece analysis at waitbutwhy. Tim Urban explains very clearly AI using a three level model. If you have any interest in AI, this is a must read. It is neither scary nor technical. It simply and carefully (for our human brains) explains the inevitability and implication of AI:
Artificial Narrow Intelligence (ANI): Sometimes referred to as Weak AI, Artificial Narrow Intelligence is AI that specializes in one area. There’s AI that can beat the world chess champion in chess, but that’s the only thing it does. Ask it to figure out a better way to store data on a hard drive, and it’ll look at you blankly.
AI Caliber 2) Artificial General Intelligence (AGI): Sometimes referred to as Strong AI, or Human-Level AI, Artificial General Intelligence refers to a computer that is as smart as a human across the board—a machine that can perform any intellectual task that a human being can. Creating AGI is a much harder task than creating ANI, and we’re yet to do it.
AI Caliber 3) Artificial Superintelligence (ASI): Oxford philosopher and leading AI thinker Nick Bostrom defines superintelligence as “an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom and social skills.” Artificial Superintelligence ranges from a computer that’s just a little smarter than a human to one that’s trillions of times smarter—across the board.
Let us return to Pinchai’s reference to
I had followed the AlphaGo vs Lee Sedol Go match series in which AlphaGo won 3 of 4 games. Go is generally accepted as the most complex board game with so many alternative moves as to be almost unlimited. Unlike chess it is not possible to program a series of moves and responses.
During Game 2, AlphaGo made a move at Move 37, that left all the observing experts aghast. So much so that Lee spent 15 minutes considering how to respond.
Move 37 was a move that no human would have considered. It turns out in this analysis at Wired, that AlphaGo had uncovered a move that no human would have considered because it had a 1/ 10,000 likelihood of being deployed, yet AlphaGo realized Move 37 had a high change of success.
It seems to me that in the Urban model AlphaGo may have jumped right over Level 2 AGI (which is yet to be created) and straight to level 3 ASI.
Here is an extract from the Wired Article which I recommend to all.
A One in Ten Thousand Probability
Following the game, in the control room, Silver could revisit the precise calculations AlphaGo made in choosing Move 37. Drawing on its extensive training with millions upon millions of human moves, the machine actually calculates the probability that a human will make a particular play in the midst of a game. “That’s how it guides the moves it considers,” Silver says. For Move 37, the probability was one in ten thousand. In other words, AlphaGo knew this was not a move that a professional Go player would make.
But, drawing on all its other training with millions of moves generated by games with itself, it came to view Move 37 in a different way. It came to realize that, although no professional would play it, the move would likely prove quite successful. “It discovered this for itself,” Silver says, “through its own process of introspection and analysis.”
Is introspection the right word? You can be the judge. But Fan Hui was right. The move was inhuman. But it was also beautiful.
I just made my first Apple Pay transaction at Tim Hortons in Toronto. Very smooth – double press the home button on your locked phone. This has the double effect of unlocking the iPhone, and activating Passbook. Then simply hold over the merchant device to pay.
Despite the naysayers, it is actually easier than debit card tap to pay, because the phone is usually more accessible than debit card, and the activation levers the finger print authentication.
Now we just need more merchants in Canada to accept Apple Pay.
I was pleasantly surprised after a long wait to see RBC add debit and credit card functionality to Apply Pay today. I had lost touch with the Big 5 Canadian Banks efforts to develop a co-ordinated front on Apple Pay but I see now that they must have agreed on something. They are deploying on their own schedules with RBC and CIBC out first.
Here is the RBC page.
And here is my Apple Wallet that I had almost given up on for Canada. Now I have to go and buy a Tim Hortons coffee tomorrow. Hopefully the merchant sign up will get into a different gear now.