Hail Mary (Meeker)!

Hail Mary (Meeker)



On the 29th of May, Mary Meeker released her annual compendium of the digital state of the world – the KPCB Internet Trends. For those who may not remember, Mary Meeker was a veteran who survived the dot.com crash and also the financial crisis of 2008, as the head of tech research for Morgan Stanley. She was named as among the 10 smartest people in Tech. She now serves as a partner at KPCB (Kleiner Perkins Caufield and Byers) and has been publishing her annual opus for a few years now.

The problem is that when you’re Mary Meeker, you can get away by putting out a deck with 294 slides. For us mere mortals, reading and absorbing this encyclopaedia of information is a challenge by itself. Every year I get this and carefully save the deck to read in detail and of course, it never happens. So this year, with the benefit of a relatively free weekend, I thought I would do a first pass and pull out some of the most interesting things that I found in the report. So here are my top 10 interesting things to take away from the Mary Meeker report – some of them confirm what we know, while others are what we didn’t know, or are truly counter-intuitive.

What I knew or suspected.

1. The devices story mobile device shipments growth has shrunk to zero. This confirms what we’ve known for a while – device evolution has stalled since Steve Jobs. And since Samsung, the largest manufacturer has a ‘follow Apple’ strategy. Will we see a new device redefine growth or will the we see a decline in shipment numbers next year? HMD – are you watching? (Slide 6)

2. The decline in desktop use despite overall growth. While mobile internet growth is expected, it’s the ‘other devices’ that is interesting. This will presumably include netbooks, etc. but also smart things. I expect in future this category will be broken out to reflect the detail on Internet of Things. (Slide 11)

3. The privacy paradox will be one to watch – after all data is how every single provider improves their services, while keeping prices low, which leads to user spending more time and sharing more data. Versus the regulators needs to protect consumers and protect data use. This will be a key axis of debate going forward and will determine the balance between innovation and protection. Unfortunately Meeker’s slides don’t carry too much insight on this by way of data. (Slides 31-36)

What I didn’t know (I’m intentionally using the singular, as you may well be aware of this)

1. While we’re aware that big tech now dominates the market cap list, what should worry the rest of the pack is how they dominate the R&D spending list, which points to a continuation of their dominance at the top. The top 15 R&D investors list is dominated by 6 technology firms, with 2 each from automotive, petroleum, telcos, Pharma), with GE as the only conglomerate. The top 5 in the list are Amazon, Alphabet, Intel, Apple, and Microsoft. Also, tech firms report the highest growth in R&D, with 9% CAGR and 18% YoY growth. (Slides 40-41)

2. We know that image recognition is an area where AI has now passed the human levels of accuracy leading to all kind of applications across scan analysis in healthcare, and more controversial applications such as face recognition. Now, voice-based natural language recognition is another areas as also demonstrated recently by Google. This should drive a revolution in customer contact centres and in human-computer interfaces in general. (Slide 25)

3. The extent to whichAmazon & Google are getting to dominate the enterprise AI race. To be honest, we know instinctively that the AI race will be one by players with the largest data stockpile. But the range of services being offered for enterprise customers is still an eye-opener. We’ve just started playing around with Google’s Dialogflow, but they also have Tensor (cloud-based H/w), the recently announced AutoML (machine learning), and Vision API (Image recognition), while Amazon has AWS based tools such as Rekognition (image recognition), Comprehend (NLP), Sagemaker (ML framework), and of course their AWS GPU clusters. (Slide 198 – 200)

4. The growth of Fortnight and Twitch on the gaming front – pushes forward what we saw with Pokemon Go. The sweet spot between the hardcore platform based gamers and the casual gamers and kids where millions of people get just a little bit more involved about game, that does not need a special platform – is the story behind Fortnight (Slide 24)

What I didn’t expect

1. The highest increase in spending in enterprise IT is in networking equipment. This is a surprise. I haven’t found the data on this yet, and while the 2nd and 3rd place results don’t surprise me, (AI and hyper-converged infrastructure), my curiosity is definitely piqued by why companies are spending more on networking equipment – connecting to cloud environments from the enterprise perhaps? More connected devices and environments?

2. I’m seeing a lot more confirmation of the models of lifelong learning. This is repeated by Meeker, but her really interesting insight is around how much more learning freelancers invest in compared to their presumably complacent employee counterparts. Perhaps unsurprisingly the top courses sought include AI & related subjects, cryptocurrency, maths and English. (Slides 236 and 233)

3. Meeker makes a great point but Slack and dropbox and I wouldn’t have picked these 2 companies as the flagbearers of consumer-grade technology in the enterprise. But clearly, they are among the most penetrated consumer style tools in the corporate environment. (Slides 264-268)

Meeker has a big section on the Job market, on-demand jobs and future jobs. She also makes the same point others have made about how all technologies so far has created net new jobs. While I agree with this backlog, history is not always the best predictor of the future. And the fact that there will be net new jobs tends to gloss over the significant short-term and geographical disruption in livelihoods that is likely to occur. Think Detroit or Sheffield. There may be more automotive and steel manufacturing jobs today than in 1980 but they are in China, not in Detroit or Sheffield. And so of not much solace to the unemployed factory worker and his / her family in these towns. This may well be the story of AI – but potentially at a larger scale and possibly in a shorter time frame. (See slides 147-163).

There are also useful slides on the gig economy and on-demand jobs now being a scaled phenomenon. (Slides 164-175)

There are also entire sections on China, Immigration and Advertising – which I’ve not delved into as they are currently of less interest to me personally. The E-commerce section also didn’t have anything that jumped out at me as noteworthy. Happy to be corrected!


Seven in 7: Amazon’s Infinite Monkey Theorem Defence, GDPR Impact on Innovation, Ocado’s Successful Transformation, and More…

Seven for 7: Alexa sends the wrong message; does GDPR take us backwards? Uber crash – design flaw; future gazing with Michio Kaku; AI Winners; Ocado transformation and Energy Industry Updates.

(1) Amazon Echo: message in a bottle

The technology story of the week is undoubtedly the one about Amazon Echo and the message it inadvertently sent. ICMYI, a couple in Oregon had a call from an acquaintance to say that Alexa had sent them a recording of a private conversation of the couple, without their permission, or even knowledge. Amazon’s explanation is that this is the rare combination scenarios where a normal conversation between the couple somehow triggered all the keywords and responses that made Alexa record, validate and send the conversation to the acquaintance. This feels like the equivalent of the money, typewriter and Shakespeare problem, only, it’s not an infinite amount of time.

Here’s Amazon’s explanation: https://www.recode.net/2018/5/24/17391480/amazon-alexa-woman-secret-recording-echo-explanation

(2) GDPR  – impact on marketing and innovation.

I’m sure you’ve all received hundreds of emails in the past week exhorting you to stay in touch and re-sign up for all the emails you’ve been getting from people you didn’t know were sending you emails. But now that the moment has come, how will marketing work in a GDPR world? In one way this will take marketing backwards – as there is now a ban on algorithmic decision making based on behavioural data. It’s a moot point whether advertising falls into this category but companies may want to play it safe and in any case, the confusion will create a speed breaker in the short term. We may now be back in the world where if you’re watching or reading about champions league football you will see a beer ad irrespective of who you are. Not just marketing – a lot of innovation will also come under fire – both because of safety first practices, but also because some organisations will use GDPR as a shield for enabling innovation stifling practices, as highlighted by John Battelle of NewCo Shift. He argues that the regulation favours ‘at scale first parties’ – large tech platforms that provide you with a direct service such as Netflix, Facebook, or Uber – where users are likely to still give consent for data use more readily than to smaller, upcoming or relatively new and unproven services.

Dipayan Ghosh in the HBR – GDPR & advertising: https://hbr.org/2018/05/how-gdpr-will-transform-digital-marketing

John Battelle on GDPR & Innovation: https://shift.newco.co/how-gdpr-kills-the-innovation-economy-844570b70a7a

(3) Driverless / Uber/ Analysis

The analysis of Uber’s recent driverless crash has now thrown some light on what went wrong. And the answers aren’t great for Uber. In a nutshell, the problem is design and not malfunction. Which means that all the components did exactly what they were designed to do. Nothing performed differently and no components were at fault for failing to do their job. But as a collective, the design itself was flawed. The car had 6 seconds and 378 feet of distance to do something about the pedestrian crossing the street with her cycle. But it was confused about what the object was. The human in the car only engaged the steering 1 second before the crash and started breaking 1 second after the collision. The car was not designed to warn the human driver about any possible threats. A lot of the inbuilt safety systems in the Volvo vehicle including tracking driver alertness, emergency braking and collision avoidance, were disabled in the autonomous mode. In a nutshell, the responsibility lies with Uber’s design of autonomous cars. Uber has stopped testing in Arizona but has now started exploring flying taxis. Not a project that might fill you with confidence!

Uber crash analysis: https://sf.curbed.com/2018/5/25/17395196/uber-report-preliminary-arizona-crash-fatal

(4) A glimpse of the future: Michio Kaku & Jack Ma

The robotics industry will take over the automobile industry. Your car will become a robot – you will argue with it. Then your brain will also be robotised and brain net will allow emotions and feelings to be uploaded. You will be able to mentally communicate with things around you. Biotech allows us to create skin, bone, cartilage and organs. Alcoholics may be able to replace their livers with artificial ones. You may be able to scan store goods with a contact lens and see the profit margin on goods. The first 7 mins of this video tells you all of this through the eyes and experience of futurist Michio Kaku. Jack Ma (14 mins in) also talks about trusting the next generation. And how we are transitioning from the industrial era where we made people behave like machines, to a world where we are making machines behave like people. Believe the future before you see it, to be a leader, according to Ma.


(5) Who’s Winning The AI Game?

With the whole world hurtling towards an AI future, this piece looks at who exactly wins the AI game – across 7 different layers. It won’t surprise you to know that China is making amazing gains as a nation – their face recognition can pick out a wanted man in a crowd of 50,000. But it might surprise you to note that Nvidia’s stock is up 1500% in the past 2 years on the back of the success of their GPU chips. Meanwhile, Google is giving away Tensorflow free. All this points to a $3.9 tn market for enterprise AI in 2022. Are you ready for the challenge?

Who wins AI, across 7 layers

(6) Ocado – digitally transformed.

When Ocado launched in 2000, it was on the heels of Webvan, a category of providers who set up to focus on eCommerce fulfilment, as an arm of Waitrose. Cut to 2018, and Ocado is a story of successful digital transformation. Ocado is today a provider of robotic technology for warehouse automation. Having become profitable in 2014, it now has a valuation of $5.3 bn and is set to become a part of the FTSE 100.


(7) Understanding statistics: What medical research reports miss

When a drug is tested and the outcome suggests a 5% chance of a possible side effect, this does not mean that you have a 5% chance of being impacted if the drug is administered to you. It means there is a 5% chance that you will have the condition which leads to you having a 100% likelihood of being impacted. This is a subtle but very important distinction in how we interpret the data. But continuing down this stream of thought, it points to the lack of personalisation of medicine, not just the misinterpretation of data.


Why Are We Suddenly So Bad At Predicting the Future?

Imagine that a monkey got into the control room of the universe and spent the year clicking random buttons. Imagine him hopping about on the ‘one musician less’ button, stomping on the ‘auto-destruct’ lever and gurgling while he thumped repeatedly on the ‘introduce chaos’ switch. Close your eyes and picture him dropping a giant poo on the bright red panel marked ‘do not touch under any circumstances’. That my friends is the only way to think about 2016 – after all, it was the year of the monkey in the Chinese zodiac. It was the year when rational thinking took a beating, when meritocracy became a bad word, when liberalism escaped from the battlefield to a cave in the mountains to lick its wounds. And not surprisingly, a year when projections, predictions and polls made as much sense in the real world as an episode of Game of Thrones on steroids.
Given much of our lives are spent in productively engaging with the future and making decisions based on big and small decisions about the possible future, this last point is more important than just the schadenfreude of laughing at pollsters and would be intellectuals. The present passes too quickly, so really every decision you’ve ever made in your life is counting on future events to turn out in ways that are favourable. Getting this wrong is therefore injurious to health, to put it mildly. And yet our ability to predict the future has never been under such a cloud in living memory. Why is this so?

Fundamentally, we’re wired to think linearly in time, space and even line of sight. We are taught compound interest but we get it intellectually rather than viscerally. When you first encounter the classic rice grains and chessboard problem, as a smart person, you know that it’ll be a big number, but hand on heart, can you say you got the order of magnitude right? i.e. the total amount of rice on the chessboard would be 10x the world’s rice production of 2010? Approximately 461,168,602,000 metric tons? This problem of compounding of effects is incredibly hard to truly appreciate, even before you start to factor in all the myriad issues that will bump the rate of change up or down, or when the curve hits a point of inflexion. The Bill Gates quote  – ‘we over-estimate the impact of technology in 2 years, and under-estimate the impact over 10’ – is a direct reframing of this inability to think in a compound manner.

Then there’s the matter of space and line of sight. The way the future unfolds is dramatically shaped by network effects. The progress of an idea depends on it’s cross fertilisation across fields, geographies and disciplines, across any number of people, networks and collaborations. These collaborations can be engineered to a point or are the result of fortuitous clustering of minds. In his book ‘Linked’ – Ablert-Lazlo Barabasi talks about the mathematician Erdos who spent his life nomadically, travelling from one associates’ home to another discussing mathematics and ironically, network theory. Not surprisingly, a lifestyle also practiced for many years by a young Bob Dylan, if you substitute mathematics for music. Or consider the story of the serial entrepreneur in Rhineland in the 1400s, as told by Steven Johnson, in ‘Where Good Ideas Come From’. Having failed with a business in mirrors, he was working in the wine industry, where the mechanical pressing of grapes had transformed the economics of winemaking. He took the wine press, and married it with a Chinese invention – movable type, to create the worlds first printing press. His name of course, was Johannes Gutenberg. This kind of leap is not easy to predict, not just for the kind of discontinuity they represent (more on that later), but also because of these networked effects. Our education system blinkers us into compartmentalised thinking which stays with us through our lives. Long ago, a student of my mothers once answered a question about the boiling point of water by saying “in Chemistry, it’s a 100 degrees Centigrade, but in Physics, I’m not sure”. We are trained to be specialists, becoming more and more narrow as we progress through our academic career, ending up more or less as stereotypes of our profession. Yet human progress is driven by thousands of these networked, collaborative, and often serendipitous examples. And we live in a world today with ever expanding connections, so it’s not surprising that we have fallen behind significantly in our ability to understand how the network effects play out.

If you want to study the way we typically make predictions, you should look no further than sport. In the UK, football is a year round sport, so there are games every weekend for 9 months and also mid week for half the year. And with gambling being legal, there is an entire industry around football gambling. Yet, the average punter, fan or journalist makes predictions which are at best wilfully lazy. There is an apocryphal story about our two favourite fictitious sardars – Santa Singh and Banta Singh, who decide to fly a plane. Santa, the pilot, asks Banta, the co-pilot to check if the indicators are working. Banta looks out over the wing and says “yes they are, no they aren’t, yes they are, no they aren’t…” – this is how a lot of predictions are made in the world of premier league football today. Any team that loses 3 games is immediately in a ‘crisis’ while a team that wins a couple of games are deemed to be on their way to glory. Alan Hansen, an otherwise insightful pundit and former great player, will always be remembered for his one comment “You can’t win anything with Kids” – which he made after watching a young Manchester United side lose to Aston Villa in the 1995-96 season. Manchester United of course went on to win the season and dominate the league for the next decade and a half. Nobody predicted a Leicester City win in 2016 of course, but win they did. The continuous and vertiginous increase in TV income for football clubs has led to a relatively more equal playing field when it comes to global scouting networks, so a great player can pop up in any team and surprise the league. Yet we find it hard to ignore all the underlying trends and often find ourselves guilty of treating incidents as trends.

The opposite, is amazingly, also true. We are so caught up with trends that we don’t factor in the kinks in the curve. Or to use Steve Jobs’ phrase – the ding in the universe. You can say that an iPhone like device was sure to come along sooner or later. But given the state of the market – with Nokia’s dominance and 40% global market share, you would have bet your house on Nokia producing the next breakthrough device eventually. Nobody saw the iPhone coming, but when it did it created a discontinuous change that rippled across almost every industry over the next decade. The thing is, we like trends. Trends are rational and they form a kind of reassuring continuity so that events can fit our narratives, which in turn reaffirm our world view. And unless we’re close to the event, or perennial change seekers and nomads ourselves, it’s hard to think of countercyclical events. It’s now easy to see how in 2016 we were so caught up in the narrative of progressive liberalisation and unstoppable path to globalisation, we failed to spot those counter-cyclical events and cues that were right there in our path.

In fact there are any number of cognitive biases we are guilty of – on an everyday basis. This article just lists a dozen of them. My favourites in this list are the confirmation bias and the negativity bias. Both of these are exacerbated by social media and digital media. While social media has led us to the echo-chambers – the hallmarks of 2016, our projection bias is also accentuated by our ability to choose any media we want to consume, in the digital world, where access is the easy part. Similarly, bad news spreads faster on social networks and digital media today than at any time before in history. Is it possible that despite knowing and guarding against these biases in the past, we’ve been caught out by the spikes in the impact and incidence of a couple of these, in the digital environment we live in today?
To be fair, not everybody got everything wrong. Plenty of people I know called the Donald Trump victory early in the game. And amongst others, John Batelle got more than his share of predictions right. There is no reason to believe that 2017 will be any less volatile or unpredictable than 2016, but will our ability to deal with that volatility improve? One of the more cynical tricks of the prediction game is to make lots of predictions at many different occasions. People won’t remember all your bad calls, but you can pick out the ones you got right, at leisure! This is your chance, then, to make your predictions for 2017. Be bold, be counter-cyclical. And shout it out! Don’t be demure. The monkey is history, after all. This is the year of the rooster!

Revolution By A Thousand Digital Cuts

You can say that with every new wave of technology, the format, structure and even the content of media changes. Or you can simply say that the medium is the message. Either way, publishing just isn’t what it used to be. Here’s my wide angle view of some of the many changes bubbling through the publishing world. 

Self publishing in all it’s many forms continues to flourish and grow. Just when you thought that between WordPress and Blogspot, that was all there was to it, you now have a raft of new platforms, including Medium and Hi for example. I’m still working out the real value of these tools, apart from the fact that they are beautifully laid out and easy to set up for the infrequent writer. I don’t feel yet that the writing on these platforms are genetically better than those on any other blogging platform. But clearly there’s a big market for self expression and this is really a good thing. 

If Blogging is the selfie of publishing, the social media must be its new mirror. As much as social media is a means of connecting with others, in an increasingly perverse way, it seems to also represent how we see ourselves through their eyes. This kind of voyeuristic narcissism is reflected in many ways but none more so than this strange and increasing trend of self categorisation through arbitrary & meaningless ontologies, abbreviated for the purpose of this discussion as ‘scamo’. Facebook is full of scamos. What colour is your aura? Which Downton Abbey character are you? Which superhero are you? Which city are you? Where will it end? Which lego piece are you? (I got the flat green base), which paper size are you? (I got A3 – gutted!) Which bollywood item girl are you? (I got Yana Gupta but I can’t see the resemblance). And definitely, which type of common cold virus are you? (I got adenovirus, so distinguished!) See how easy it is? You can make your own lists up as you go. You can see where this will end, right? Which scamo are you? 

The disturbing trends don’t end there. I pray every morning that the phrase “what happens next will xxxx you” (insert appropriate transitive verb) could be banned from headlines. “This surgeon started to operate on his patient. What happened next will amaze you!” “This man tried to drink printing ink. What happened next will stun you”. “This man tried to click on this link in face book. What happened next will baffle you” But of course, in the click-economy, it’s all fair game. As long as it can make a few (million) people click on the link, it’s a successful headline. 

To be fair, the original story headlines were competing with other headlines in the same newspaper, because typically, you would already have bought or be reading that paper. Or at best your lead story would be competing with the main headlines of other papers. Today you’re competing with a stream of consciousness flow of headlines, curated, ad-inserted, thrust upon you by friends and family and wished upon yourself by those links you clicked unsuspectingly last week. Forget 15 seconds of fame, each headline gets about 1.5 seconds before it’s history in your eyes. 

Facebook and Twitter have definitely become strong sources of news curation for me, much more so than TV or any single media organisation. But in the lead are still aggregation apps such as Flipboard and Zite. I was quite gutted to learn that Zite had sold itself to Flipboard, as they represented 2 very distinct kinds of approaches, both valuable, and I’m fretting that the result will be a bit of both but neither to it’s optimum levels. Circa is quite interesting (thanks @maria_axente!) because it allows you to track one story as it evolves. 

But then you have tools like Paper.li and others which allow the aggregation itself to be automated in a democratised format. This is basically software eating media eating software. Pretty soon the only real value will lie in original content. This is why players like the Economist, New York Times or HBR are likely to have long lives because they are effectively becoming the HBO’s of the publishing space. Everybody else is aggregating, sorting, distributing, dicing and slicing. It’s worth pointing out that players like Business Insider, Outbrain and Bleacher Report,  are trying hard to build a business that truly exploits the new distribution in different ways. But while Business Insider, which was founded by Henry Blodget and counts Bezos as an investor, does focus on good and original content, the others seem to want to flood you with content with those titilating headlines, so they can financially surf the click economy. 
One of the outcomes of the smartphone enabled and Instagram and Facebook fuelled environment we live in, is that I’ve come to expect pictures where a picture is required. As a consequence, I struggle through long descriptive paragraphs in books. I appreciate that it would have been hard for Dickens to simply Instagram a picture of foggy London, and perhaps we’re the better off for it. But with the increasing democratisation of tools and knowledge of image and video creation I think a new wave of storytelling is just around the corner. A book created for electronic consumption should have pictures, videos, hyperlinks and more, all of which are creatively and effectively used to enhance the storytelling. This is not to denounce the metaphor as a bedrock of great content, but to provide an experience that truly exploits the medium. Just imagine Gibson’s Neuromancer told through this kind of multimedia! 

Certainly, there’s plenty of excitement and enough funding for new ventures in news and publishing, as this piece from the FT points out. There is ongoing innovation as start ups like Blendle demonstrate. I personally think that we are just at that point where we start to appreciate the value of news as distinct from entertainment, and stop clubbing the business models together. Certainly, when ‘rock star’ geeks such as Bezos and Nate Silver are getting into the game, there must be plenty left to play for! 

In the mean time, I’m off to post my selfie to Facebook and Twitter, so I can see what others say about it, so I can figure out which mythically egocentric character I resemble the most.