(Special thanks to my colleague Rocky Fong for the research and insight on home care)
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 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.
(1) Doing Agile at Scale
(2) Artificial Intelligence At Scale – for non-technology firms
(3) The Ring of Success:
What makes a new product successful? I met Jamie, the founder of Ring a couple of years ago in London and was struck by his directness and commitment. He even appears in his company’s ads. Ring.com was recently acquired by Amazon for $1bn. Here one of the backers of Ring talks about the factors which made Ring a success. In a nutshell, the list includes (1) the qualities of the founder, (2) execution focus and excellence, (3) continuous improvements, (4) having a single purpose, (5) pricing and customer value. (6) integration of hardware and software. (7) clarity about the role of the brand.
(4) Blockchain and ICO redux:
Do you know your Ethereum from your Eos or your MIATA from your Monero? This piece from the MIT Tech Review will sort you out. And for those of you who are still struggling to understand what exactly blockchain is, here’s a good primer. Of course, you could always go look at my earlier blog post on everything blockchain.
(5) X and Z – The Millennial Sandwich
X & Z: Or the millennial sandwich. All the talk in the digital revolves around millennial, but there is a generation on either side. The generation X – followed the baby boomers, and it turns out they have a better handle on traditional leadership values than millennial. This article talks about Generation X at work.
(6) Big tech validates Industry 4.0
This week, the large tech players disclosed significant earnings, beating expectations and seeing share prices surge. In a way it’s a validation of the industry 4.0 model – the abundance of capital, data, and infrastructure will enable businesses to create exponential value, despite the challenges of regulation, data stewardship issues and other problems. Amazon still has headroom because when push comes to shove, Amazon Prime, which includes all you can consume music and movies can probably increase prices still more.
(7) Defending Democracy
The US elections meets the technology arms race – this article presents experiences from a hacking bootcamp., run for the teams who manage elections. While the details are interesting, there is a larger story here – more than influencing the elections either way, the greater harm this kind of election hacking wreaks is in its ability to shake people’s faith in democracy. As always, there’s no other answer than being prepared, but that’s easier said than done!
(I had the privilege of speaking about IOT at the Oxford Technology and Media forum yesterday. What follows is the gist of my session and some thoughts from the panel discussion)
The tech industry is often guilty of pushing technology solutions to consumer without focusing on the benefits, the emotions and simplicity. Invariably, businesses that get it, do better at selling tech to consumers. Apple are clearly the masters at it, but UK customers will know that after many years of ‘interactive television’ discussions, what customers bought were ‘sky plus’ and ‘red button services’. (The technology didn’t actually deliver on the promise, but that’s a different story).
So we come to the Internet of Things and I believe, we’ve swung to a different end of the pendulum. We’ve created a pithy, catchy phrase, something that everybody can relate to and not be daunted by the jargon. I would personally have preferred the internet of stuff (stuff is cooler than things). But the internet of things means (pardon the expression) bugger-all when it comes to actually buying, implementing or solving something.
Maybe I’m being harsh. It’s a catch-all word conveying a general wave of technologies much like “digital convergence” in the broadcast and comms space. But it’s a very loaded phrase and masks many layers of complexity that haven’t yet been resolved to the point where they can be implemented. Or even understood by the consumer.
The IOT includes communication between machines, between people and machines, and also between people and people via machines. It includes wearables, and all manners of sensors, and an ever increasing ocean of data, an implicit assumption of an economically viable, reliable and available network. And so far, very few standards.
After all, we’re all spoilt by the Internet – in the world of standards driven browsers, we only had to worry about the browser environment. The most complex questions in the early days of the web included ‘web safe’ colours. And later, pushing the limits of HTML. You never had to think about the OS, the device (are you viewing the website on a Dell or IBM laptop?) You didn’t have to think about whether the user was sitting or standing or walking around. And all you had to know was a URL, and the internet would find the website from over 50 million computers in a fraction of a second. Even transactions and ecommerce are now taken for granted.
In the IOT world, all these are non-standard and have to be thought from scratch. What’s the user interface of a ‘thing’? If it’s a sensor on a coffee machine vs a door, how should we access the data, how can interact with the thing? The design challenge moves from an ‘interface’ design to an experience and even environment design. Who designs the experience of walking into a retail store which is armed with iBeacons or other sensors? Design challenge will range from fitting an antenna while managing heat dissipation, to figuring out how to retail product aesthetics while adding a bunch of tech.
Service design has been a term in vogue for a few months now, but is fundamental to the creation of IOT models. We must take a design centric view and build from there. That’s the only way we’ll get around to focusing on the right problems to solve, to ensure adoption.
As with all emerging technologies, we’re in the world of ‘compound change’ – where each layer builds on previous layers, and so it creates an exponential change curve, which is near impossible for us to predict, since we’re still very used to thinking in linear terms. What is intuitive to me, is that we’ll get entirely new companies dominating the IOT space, in the way that FB, LinkedIn and Twitter dominate the social sphere, and Google and Amazon dominate the web, Apple and Samsung dominate mobile devices and Microsoft and Intel dominated the Desktop world.
Because, this will take a whole new business model. It will shift value, destroy old models and create entirely new services. Most often, we think of new tech as better ways of doing what we do today. So the ‘better’ model leads us to thinking about how our fridge will tell us when it’s out of milk. Rather than ‘different’ models – perhaps our fridge telling us which of the foods we’re storing has the earliest use-by date, so we can modify our consumption appropriately. Or other more imaginative and useful behaviours.
Undoubtedly the way in which business models will evolve will involve adding layers of services to existing and new products. The value of the service will outstrip the value of the product. You may pay more for the service of tracking your weight and the feedback on your lifestyle and diet, than you do for the weighing scale itself. In fact asset ownership models may change, with companies willing to give you the asset for free in order to lock you into the service, or simply, follow an asset leasing model, which brings down your outlay but enables longer term revenue stream for the seller. Soon we should be able to view this information and services layer explicitly and this explicit-isation of the service and information layer may be one of the biggest sources of consumer value in the IOT. This would enable us to understand better the total cost of any product (say a sweater, or a vaccuum cleaner) and make different choices on that basis. It would also align value realisation with costs – imagine a washing machine which you lease and pay per use.
Although it’s tempting to consider just the things we acquire and own, there are all those things we use, which form the asset base for service delivery, from smart meters, to hotel rooms and railway stations to rented cars. These can all also follow the same principles of creating explicit service and information layers, so that maintenance, usage, and cost and value can all be tracked more easily. Then you have natural resource and public environments – weather, floods, pollution tracking, and more.
As has been noted, it is almost impossible to talk about IOT and emerging technology of any kind without talking about data, privacy and security. I used to think, like everybody else, about a data brokerage, or info-mediary. Now I think data-brokerage should be a feature built into every product. A data brokerage module will ensure that consumers data is stored, transacted and valued in a way that is fair to both sides, and in a transparent manner. Really, you can’t ask for more than that.
Undoubtedly the IOT is a big deal. We’re talking about billions of connected devices changing the way we live our everyday lives. The transformativer potential of this can barely be imagined. I just hope we use this to solve some of the bigger problems we face – the energy crisis, caring for an ageing population, getting supplies more efficiently to the needy, across the world. And not spending too much time debating whether our kettle should gossip with our washing machine.