Uber is now valued at $50 bn - WSJ
Uber Technologies Inc. has closed a new round of funding valuing the five-year-old ride-hailing company at close to $51 billion, according to people familiar with the matter, equaling Facebook Inc.’s record for a private venture-backed startup.
This is...extraordinary, for a business that essentially bases all its economic value on arbitraging a section of the labour market, essentially the newly emergent (and thus poorly regulated) zero-hours-contract, dead end contract job market, or whatever the equivalent is in whichever country you look at. History tells us this will inevitably be regulated at some point in OECD countries.
Plus, all public service markets (like taxis, hotels etc) were eventually regulated to protect providers (eg drivers) and customers (eg passengers) after the inevitable high profile abuses, this one will be too at some point. (The recent scalping of Uber customers in London during the Tube strikes didn't help their cause)
But also what also fascinates me is the view is that it is a sustainable high margin business among many people who really should know better, i.e. those handing over the money at these values, with all that implies. The dream is that efficient algorithms match supply to demand and the customer pays the value added surplus. That is fine in startup scale, when most customers are time starved salarimen with brass in pocket, buts its not a mass market proposition. The cost of running a taxi is little different no matter who is running it (unless you want people to skimp on all those regulated issues like maintained cars, drivers licences etc...), so when it tries to scale to this valuation it is going to have to offer rides to teh kless cash-flush hoi polloi. So unless Uber is being run as a not for profit (and the $50 bn valuation rather belies that) then the bulk of the money taken out of the business model will be from the drivers' wages. And when that is dis-allowed (see - skimping, abuses, etc above) , where are the margins and who takes the hit?.
I guess its more that the backers are betting on Uber being able to
lobby like hell
avoid regulation of their part of the taxi labour market until after they IPO* (Or get rid of the taxi drivers and replace with AI cars before the proverbial hits the fan? )
Do you believe this will lead to higher or lower standards in the industry? Do you believe that there will be public pressure to regulate this part of the taxi industry? Do you believe it will come sooner, or later?
Answers on a share application form for the impending IPO.....
BTW - there is an implication for all those building the "Uber for X", they maybe better think carefully about their business model (or their IPO date), as it will probably have the same (low) returns that the other regulated players they are trying to disrupt have, unless there is some other cost pool in that X value chain they can take surplus from other than arbitraging unregulated labour. (Hint - one doesn't get Unicorn values if one takes it from one's own cut...)
*Definition of IPO post Facebook - to sell unicorn-poo for a lot of dollars to those people who believe in unicorns
The IoT is 70% Hackable, says HP. Only 70%? It's hardly even growed up yet! PIcture Source
My colleague David Short has long been concerned about the hacking potential on "digital cars", as all intelligent devices in a car typically share the same databus, and as they become more wired to "the grid" the probability of hacking will grow, whereas so far the probability of manufacturers to take preventative measures is at best static. (And, as David often says, "preventative measures" will only deter the casual hackers, taking care of the real professionals requires considerable redesign of any such simple system)
What does this mean - well, anything from me being able to lock your car and demanding ransom money be paid to an anonymous bank account to deliberate sabotage.
But this is just the tip of the iceberg, now that the IoT is officially on top of the Hype Curve
, it means that any hacker worth their salt will be sharpening their code, and the truth is - (having been doing IoT stuff for nigh on 30 years, since long before IoT was called IoT), there has been absolutely minimal interest from the promoters in either mentioning or preventing the possibility of hacking, mainly as (i) it tarnishes the hype, (ii) it makes the seamless simplicity of those IoT solutions a lot less so and (iii) it costs money - theirs to shore it up or yours if they don't.
And we are not talking about good old datahacking and datascraping, the thing about the IoT is it controls devices, so hacking them not only gets the data, it lets the hacker control those devices. At its simplest it is swiping cycles like a botnet does, at its most malign its causing dangerous malfunctions, at its mainstream use cases its probably going to be used to facilitate crimes we already know and love - theft, extortion, etc. And not all teh bad guys will be bad guys - ther are quite a few corporates and quasi governmental agencies who see a benficial paycheck from controlling more of what YOU! used to do for free.
Now I watch the Economist with interest, as its my "mainstreaming" litmus test - as in when something is mentioned in The Economist, it means its about to get mainstream publicity. And today they let the cat out the bag
....Dr Graham Steele of Cryptosense, quoted below, sounds just like David:
...many of the firms making these newly connected widgets have little experience with the arcane world of computer security. He describes talking to a big European maker of car components last year. “These guys are mechanical engineers by training,” he says. “They were saying, ‘suddenly we have to become security developers, cryptography experts and so on, and we have no experience of how to do all that’.
As The Economist notes, this is the InnocentNet of the 90's, replayed:
the biggest difficulty is that, for now, companies have few incentives to take security seriously. As was the case with the internet in the 1990s, most of these threats are still on the horizon. This means getting security wrong has—for the moment—no impact on a firm’s reputation or its profits. That too will change, says Dr Anderson, at least in those industries where the consequences of a breach are serious.
He draws an analogy with the early days of railways, pointing out that it took decades of boiler explosions and crashes before railway magnates began taking safety seriously. The same thing happened in the car industry, which began focusing on security and safety only in the 1970s
One difference is the 'Net has generated a huge community of hackers, they were a rare breed 20 years ago, now not at all, and the IoT is the biggest unlocked toybox you an imagine. Now you can be sure thet critical devices worth a lot of money will have some attention thrown at them, but for the rest...
For those markets where bugs and hacks are more annoying than fatal, though, things may take longer to improve. “I might be happy to pay a bit extra to make sure my car is safe,” says Dr Steel. “But would I pay more to make sure my fridge isn’t doing things that annoy other people, rather than me?”
So what to do - well, I don't mean to be a killjoy - there is a typical trend for new technologies liek this - first comes the hype, then the arbitrage, then the cowboys, then regulation to clean up Dodge City, then it settles down. our advice. For practical purposes for now, we are not even in Cowboy phase so best is to be a "laggard early adopter"and let others experience the delights of being first into the Internet of Hacked Things for a good few years, but if you must adopt these New New Things:
(i) Don't sign up to any current metering or "smart" devices - none of them have any anti-hacking capability yet. If the control button is not yours and yours only, caveat emptor!
(ii) Ideally, keep your datacoms separate from the car (or any potentially risky) infobus. Avoid any car that wants to "phone home" using wireless for a few years. This also means eschewing all those helpful apps on your phone that want to connect to those other databusses you own and "phone home"
(iii) Don't let any device talk to anything that may be able to find your financial details. Separate Wifi nets. Seperate routers even (yes, do this....). Get a Faraday cage for your Contactless credit card - you better believe it!
(In fact, never mind "intelligent wearables" - the other hype curve No 1 contender, I reckon the high value market is in cybercloaking wearables)
Last Thursday I was lucky enough to visit IBM’s Big Data Crunching Operation behind (and underneath) the annual Wimbledon Tennis tournament, courtesy of fellow Tuttler Andrew Grill
of IBM (who says nepotism never pays) and also courtesy of the knowledgeable and enthusiastic (despite me being the Nth tour guest of the week) Sam Seddon
who escorted me through the databunkers.
Now I am far from the first Old Tuttler blogger that Andrew has invited, my colleague David Terrar went last year and Neville Hobson
went on the Tuesday last week (here is his post
). Thus the “what happens behind the Datascenes at Wimbledon” is already more than well covered, just look at David’s blog post from last year
- to quote:
Sam [Seddon] has a team of around 200 supporting Wimbledon using an impressive array of terminals and technology on site, supplemented by an enormous amount of Cloud compute power from data centres in Amsterdam and the USA. They are providing a service to the All England Lawn Tennis Club to help make Wimbledon the premier sporting event, but in doing so they are serving the audience at the ground, fans around the World, the radio and TV broadcasters of the event, the event sponsors, the Club itself, and even the players directly
David did a good analysis of the overall IBM operations last year, and had some cracking photos - so what can I add to this? Probably the best is to talk about it from the point of view of things I know about in some detail – in this case, high end datacentre infrastructure, real time big data & analytics, and system automation (in this case, Watson
High End Datacentre Infrastructure
Firstly, from the point of view of datacentre infrastructure, this is a high pressure operation – real time, high visibility, peaky data flow. High embarrassment if things go wrong. Also, the web based systems get quite a few attacks 24/7. And as well as running all the tennis data feeds discussed below, IBM also run the ticket checking and security operations of the whole site.
Secondly, from an Operations & Logistics point of view this is further complicated as the whole setup is also completely transient – for 2 weeks a year the Tournament Tennis circus descends on Wimbledon. The entire IBM system rolls in, the porta-datacentre and its operatives are wheeled into the empty bunkers from locations elsewhere in the world (along with all the TV broadcast trucks, meedja personalities, commentators in their glass boxes, tennis line callers, buckets of strawberries and flagons of Pimms etc etc) - and then two weeks later the whole panjandrum disappears and the whole site is emptied and mothballed again for another year.
This is non trivial stuff, kudos to IBM for making it so seamless!
Big Data & Real Time Analytics
From a “big data fan” viewpoint there are 3 main data handling operations (see flowchart above, and weep) - in summary::
Every shot played by every player is captured, not just physically but with rich metadata – tennis experts analyse every shot and record what it was, why it was played, did it work/fail. Interestingly IBM captures data from every major tournament so you can pick up a rich data picture of every player and the permutations of their matched with others.
Added Tennis Metadata
Not only player match stats, but their historical metadata and also Wimblestats are collected – for example, veteran Leighton Hewitt hit his 1500th ace the day I was there, and they can play comparison games with stats back to the 1870's. Much of this is to add rich data to the various media outfeeds - website, TV, Radio, Social Media.
Social Media Analysis
The 3rd operation is the monitoring of Twitter feeds off the Gnip firehose. To my readers much of this is familiar ground – find, scrape, focus, process, analyse, use output to inform and focus further coverage etc. (David covered it last year if you’d like more detail) However, there were a few counter-intuitive things I learned:
- Court Prowess and Twitter are loosely linked – Rafa Nadal was the most talked about all player week, despite being an early exit
- Tennis stars endorsing brands is pretty pointless, on Twitter anyway – the online conversation and attention follows the person, not the brand, no matter how many hashtags the PR people throw into the Wimbledome.
- Well heeled Wimbledon fans are by and large not Twitterers, those who can pay to watch live tennis are by and large not (yet) the Generation Who Tweet – but it grows every year
- Increasingly, fairly respected online retailers are clocking onto on the Twitter trending #tags and ad-spamming them (Wimbledon is clearly a better class of hashtag)
I was a bit taken aback by the last one, but I guess when you think about it, in media there is a general trend that where porn blazes a trail, advertising soon follows
To a data modelling/simulation wonk like me this was all fascinating, and I hit Sam with all sorts of “what ifs” but he reminded me that It's all about understanding the business of tennis - that you have to look at who the customers are, and what they want. I may want to run the Moneyball
Crunch of all crunches on the tennis world and create virtual avatars so I can play Bjorn Borg against Rafa Nadal, but realistically the data is required by:
- Media organisations looking to enrich (and pad out….) their commentary teams’ output, especially as the days progress and the early round flood of games subsides
- A “value add” that Wimbledon.com alone can provide the legions of the tennis–nuts from its website, they aim to be the best tournament in the world.
- Coaches/players who want to look at their performance to improve (apparently not all do this, so data-led training has not got to the level many of the big team games – odd in my view given the spoils to the victors involved, but hey….)
'You know my methods, Watson.'
….said Sherlock Holmes in The Crooked Man
(he never said “Elementary, my Dear Watson by the way ), and to me this is what is starting to set apart what IBM is doing vs other big iron data operations.
For those who don’t know about Watson, it is a very powerful Machine-Learning system initially focused on natural language processing. It’s key role is Question Answering, so underlying the language processing is are powerful deduction chain algorithms. In short, if you can feed it information and deduction methods, it can form its own hypotheses and reasoning chains This makes it useful for quiz shows (it won at Jeopardy in 2011), medical diagnoses, and – well, tennis among other things.
Right now it is being taught the basics of Tennis geekdom (What is love? – answer – a score of zero), being force fed Wimbledon tennis history (to draw parallels etc) and is starting to look at the social media chatterflow. But if you look at the data processing going on at Wimbledon, there are a LOT of workflows, methods and deduction chains that are ideal for a natural learning machine learning system.
So when afterwards the IBM people asked me what my main thoughts were from the tour, I told them that in my view, many of their 200 or so operatives here will disappear in the next 5 - 10 years as Watson and other AIs start to take over the rote data processing going on there, and then the less rote, and then the really high value add..
And yes, it felt traitorous to say that, sipping Pimms and watching the bright young meedja things gambolling on the grass, but at the end of the day the automation of dataflow & analytics is just the next step in an ongoing process of transformation.
Wimbledon is just part of a trend I see everywhere right now, wherever previously unstructured data is being digitised. First comes the rudimentary digitisation of hitherto unstructured data (often from manual or semi manual processes ), then comes the early analytics which creates huge value from the low hanging datafruit, and increasingly we now are starting to see the application of automation, both in data capture (IoT) and analytic reasoning (MI/AI). The future will come one automated data feed and workflow method at a time.
Automating the Tennis Tournament Production Factory?
Wimbledon makes 70% + of it’s money from selling Media rights
for the two weeks of the tournament (and as more and more courts get their own datafeeds this revenue will only increase).
And as all those assets, that span acres of prime London real estate – the main courts, the techie bunkers and media circus rings, the player palaces, the buildings for the huge catering and logistics operations – all largely lie fallow for 50 weeks of the year, Wimbledon will always need to maximise income and minimise costs from those 2 weeks a year.
Thus they will inevitably be pushed into the economics of ongoing automation of Tennis Tournament production. The need to both reduce operating costs and produce ever more value-add from the datafeeds is probably inevitable. The competition for media $ will only intensify, other tournament operations will up their value add year by year. So that means more and more AI for the data handling and analytics tasks, to produce more value add for Wimbledon and its customers.
Unless, unless…..the unquantifiable human input can be shown to make the difference between an experience that will delight, versus one that is artificially inserted.
Maybe automation will have it’s limitations, we may not like a smart Watson, but instead prefer a nice-but-slightly-dim Watson to our Holmes - quoth Mr Holmes:
A confederate who foresees your conclusions and course of action is always dangerous, but one to whom each development comes as a perpetual surprise, and to whom the future is always a closed book, is indeed an ideal helpmate.
We shall see. I’d place my money on Smart Watson though....