Entries by Alan Patrick

As readers of this blog may know, we started watching Robotics again in about 2008* when it became clear to us that the advance of Moore's Law meant that finally enough computer power and battery life made it possible to build robots with all their systems onboard, so they could become self-mobile and (to an extent) self directing. This change was labelled "3rd Generation" robotics (as always it was hyped long before it became reality, but over the last 5 years or so there has been a tipping point), and heralded a "Cambrian Explosion" in new robot design. This happens in every new technology, see here re: ships, steel and steam for example, and a plethora of ideas (and companies) start up up in the Darwinian ooze of the startup ecosystem, until eventually the category killers emerge.

Anyway, you know the robobuzz is well and truly ringing the bells of the early mass mind when someone like NESTA produces a 100+ page book on Robotics, it is called "Our Work Here is Done", and I read it over the weekend. It's a series of essays by various people on the topics of robot evolution, robot economics, robots and society, and of course What is To Become Of Humanity.

As to the individual papers - as you'd imagine, they're a bit curate's eggy, but there is a lot of good stuff, and some real nuggets in just about every paper. There are 4 main sections:

1. The Economics of a Robot Future (Has a lot of Social impact thrown in)

2. Technology Possibilities

3. Robots of the Past & Future

4. Robots and Justice (which has a whole 'nother slew of Socio-Economics)

Overall though it is a good introductory overview to all the emerging socio-economic issues. My two critiques overall are that:

- it is light on the actual technologies and how it all works, IMO its useful to have a grasp of the basic emergent technologies - stops the flights of the the fanciful.

- there is a bit of Panglossing over the downsides. Who owns these automated means of production for example? To whom will the newly liberated labour productivity wealth flow?. Promises of a leisure-filled and abundant future for a happy humanity should be put in the same bin that the self same predictions in the 1930's and 1970's were.

But with those caveats, its a cracking read.

I'm sorry I missed the launch, as one of Broadstuff Towers' all time heroes, Carlota Perez,, gave a keynote talk and it was excellent (see here). She would be the first to note there is usually quite a bit of Destruction before the happy Creation phase. I suspect that will also be the case for robot futures - take longer to happen, be nastier while happening, and take longer to get better. As one grounded participant (Ben Russell, Curator of Mechanical Engineering at the Science Museum) tweeted:

"The cry of forthcoming robot revolution won't be "I'll be back" or Exterminate, but 'Unexpected item in bagging area"

No one knows what to do with those who will be displaced by this industrial revolution, but at least this time round most of the writers note the displacement will happen...

(*Bit of background - my Honours dissertation & design project was on Robotics, years ago when they were very 1st generation - I reckoned robots were at least 30 years away from being more than auto-Waldos and went on to d other stuff, but now things are getting very interesting again).

People Invested $1 Million In An App That Just Says ‘Yo’

"It’s not just an app that says Yo,” says Mr Arbel. “It’s a whole new means of communication"

'nuff said... are we getting to an age when every startup gets $1m just for existing? Will tomorrow see $1m for an App that says Ni! ?

As was noted by James Surowiecki* in the New Yorker, the problem is increasingly not getting started and seeded these days, its finding a way out the Darwinian stew of all the other crap ideas encouraged to start up - and this ain't the way to fix that.

* Author of Wisdom of Crowds

When the Twitter IPO was mooted, we believed that although the company has potential, one of the major risks to its future valuation was its management - see here for example, where we wrote :

6. As always though, realizing potential comes down to execution.

- The FB team are very focussed, Twitter is harder to judge - lots of change at the top over the years, we wouldn't be at all surprised if they bring in an "Eric Schmidt" figure.

The fun and games this week was totally predictable (see above...), now we await part 2 of our prediction - an Eric Schmidt type character brought in to reassure investors.

Who's your money on?

From The Atlantic, it would seem that Google self drive cars rely hugely on the information about the road.:

Today, you could not take a Google car, set it down in Akron or Orlando or Oakland and expect it to perform as well as it does in Silicon Valley. Here's why: Google has created a virtual track out of Mountain View.
A Googler demonstrates what the self-driving car "sees." Note the background world on which the light traffic lights and their sightlines are displayed: that's the track.

The key to Google's success has been that these cars aren't forced to process an entire scene from scratch. Instead, their teams travel and map each road that the car will travel. And these are not any old maps. They are not even the rich, road-logic-filled maps of consumer-grade Google Maps.

They're probably best thought of as ultra-precise digitizations of the physical world, all the way down to tiny details like the position and height of every single curb. A normal digital map would show a road intersection; these maps would have a precision measured in inches.

In other words, the real work is not in the software for driving the car, but in mapping the road...

Google has created a virtual world out of the streets their engineers have driven. They pre-load the data for the route into the car's memory before it sets off, so that as it drives, the software knows what to expect.

"Rather than having to figure out what the world looks like and what it means from scratch every time we turn on the software, we tell it what the world is expected to look like when it is empty," Chatham continued. "And then the job of the software is to figure out how the world is different from that expectation. This makes the problem a lot simpler."

While it simplifies the driving algorithms, it relies on a hugely detailed - and up to date - map of the roads being used. In a way it makes me happier - they are not using new super-technology, nor have they thought of anything no one else has - they have just imagined using a far bigger hammer. As The Atlantic points out, the solution is very "Googley" - Mohammed won't go to Mountain? Simple - move Mountain...

The more you think about it, the more the goddamn Googleyness of the thing stands out: the ambition, the scale, and the type of solution they've come up with to this very hard problem. What was a nearly intractable "machine vision" problem, one that would require close to human-level comprehension of streets, has become a much, much easier machine vision problem thanks to a massive, unprecedented, unthinkable amount of data collection.

Not to mention massive use of huge data centres to do the Crunching...

Which is all very well, until you start to look at the costs of producing this sort of data on enough roads to make these sort of cars useable by private motorists. In fact the setup costs are so huge, and any payback very skewed (looking at where most road miles are travelled, it looks a lot like a logistics network) it's likely that these sorts of cars will initially be used as a new sort of taxi in or between major conurbations (ie cost to datamap road can only be offset by volume of paid journeys on very heavily trafficked routes). "Data Highways" first, then city roads, then suburban roads, then small towns, and as for the final 20% of rural roads - maybe never. And that is just the cost of initial digitisation - but you then have to keep those data maps to a useable level of accuracy, so frequent re-digitisation is required.

This also seems very similar to the classic Simulation Model error - the belief that if you can make a model that is accurate enough, you can simulate anything in software. The truth is you cannot simulate anything with 100% error free models, so you have to believe that 99.9999999% reliability x millions of road miles travelled x probability of serious accident will give a better outcome than is currently possible with a zero cost non digitised road, a sophisticated biocomputer driving the vehicle, and a fraction of this investment spent on a fraction of this technology to put intelligence onboard to make safer cars over the next few years.

The final issue is this - if Google spends the $ billions to collect the data, and if no one else can use these roads with their automated cars unless they buy that data (how else will the business case work - Ad boards on the cars? ) - then that is a classic infrastructure lock in, like any good road toll scheme. Of course, the local authorities could then add an extra tax on using these cars on their roads, so this could all get very interesting....

So - I made that Ad comment somewhat snarkily, only to find out that very evening that some people are planning to attach plastic laminates that can have have Ads printed on them on cars...and the laminates can have new images uploaded onto them from time to time.

Saw this project - Outrunner -on Kickstarter. It particularly caught my interest as it is using a simple but innovative approach to robot movement - two rotating 3-spoke "legs" to get in effect a 6 rotating leg device - to move extremely fast (c 20 mph) and uses a combination of weight shifting and speed adjustment to steer.

It's interesting as the search for optimal robot movement systems is in its early days, and the level of experimentation is huge. This approach maps to the cycle of human running movement, but abstracts it to another architecture (rotating spokes) to deliver a similar result - in my view this observation of tested bio-mechanism and abstraction to mechatronic ones is probably going to be the endgame for optimal "mechanical life" configurations - but this field is a proper "artificial Darwinian stew" as robospecies evolve, and who knows what the endgame will be. (There is a 2 x 2 4 legged version as well, interesting as both sides have 4 spokes but 2 are shorter an don't reach the ground - the spoke on the other side does- I assume that is to balance the secondary moments - one wonders therefore why a 2 x 4 arrangement is not better than a 2 x 3)

But the bigger picture is this - this project (and the many like it) are being funded by end customers rather than angels or banks, so control of the money and ownership of the business is far more in the hands of the founders. Compare this to what these people would heve had to do to get the product out even a few years ago. Whether this one wins or loses is irrlevant, many are being tried out, innovation is moving at rapid speed

One of the real lesson we have learned in our research on new technologies that take off, is that the technological innovation is not enough to drive success and that often innovation in the business model is also required. The "Equity Gap" in technology startup funding has been well documented (by us as and by many others), and it seems that these crowdfunding schemes are part of the solution to that gap*. I see it as a part of the emerging collaborative economy, and it is massively disruptive as it:

- cuts out all direct middlemen, and replaces funding with a market platform at far lower rental cost
- gives the entrepreneur very direct customer feedback very early on (no likee, no fundee)
- keeps ownership with the innovator longer

In fact one could argue there is now a Darwinian competition between business models as well as mecatronic perambulation systems.

Of course, this is not to say this sort of funding won't have the same problems every other new player going to market has - getting attention. Apps were cool when there were a few, its far harder to make a splash when there are millions to sort through. No doubt at some point rising marketing spend and "trusted third parties" will interpose themselves between funder and crowdfundee (though they may be bots as much as humans) - but for now, it good to see innovative technology being driven by this new innovative business model.

* As of course is the "Freeconomic" benefit of massive research by semi publically funded bodies that these technologies often spin out from....

Apple will spend $silly on Beat, and confirm that their creative mojo is wilting. The story runs like this:

The potential $3.2 billion deal would mark Apple’s largest acquisition of another company ever, and would be a stark contrast from Apple’s former reluctance to making large acquisitions. Apple CEO Tim Cook recently said that Apple is on the “prowl” for more deals, and this Beats acquisition would certainly prove that…

Beat has c200,000 users so that is Apple saying its worth c $16,000 per user....riiiight*. But Big Tech Co's buying in the IP at ludicrous values as they cannot do it themselves anymore - T'was always the case, we've catalogued this from Google to Facebook over the years...

But to me a more interesting story is that the FT, which broke the story, has a paywall so unless you go through the faff of signing up, you don't see their story - which of course most people can't be arsed to do - which means it's been stolen by every other media unit going (and here we go too....) - 9to5Mac is running as the story leader on Techmeme for example.

An interesting downside of paywalls, when the story goes viral, the paywall says No....maybe they need to put Ads on the paywall signup

*Update - Ciaran Norris pointed out to me that Beat was valued at c $1bn a few months ago on a refinancing deal, so a 3.2x valuation uptick in a few months is not quite $silly - though still.....interesting

Some time ago we showed a man carrying dronecopter, and then the idea of Amazon delivering packages via drones - put that together, add a few more horsepower, and why not a truck-copter? Now you can - from the Torygraph, news of a truck capable of flying with an octocopter arrangement of rotors:

In this first test, the vehicle hovered 10 feet off the ground for a couple of minutes, but it is capable of flying at much higher altitudes while carrying payloads of more than 4000 pounds.

After landing, the UAV folds up its propellers and transforms into a supply truck, capable of navigating over rough terrain.

There's more....why stop with trucks:

The transformer's drive train will also be detachable, allowing it to be replaced by an amphibious boat hull, making it suitable for missions on land – and at sea.

What's interesting to me, putting my Engineering hat on, is why this is only possible now - the theory has been around for decades, so why now? Turns out that its the controllers that allow multiple rotors to be co-ordinated to keep the machine stable, these simple rotors don't tilt or change pich so can only move the 'copter by different motors speeding up or down. Which is the other thin we can do better today - electronic controllers and motors now are better at speeding up and slowing down. Even so, these vehicles will always be less efficient than helicopters. and as vehicle mass increase this will increasingly be a problem so there is probably a limit to growth here - but the (computer aided) simplicity of these new rotor designs are very tempting for smaller man-carrying craft.

I spoke last night at the Cybersalon event on "Reclaiming our Big Data", must say I enjoyed all the contribution from the other panellists who I felt were very well qualified to talk about this area:

Kenneth Cukier - Data Editor for The Economist, from 2002-2004 he was a research fellow at Harvard's Kennedy School of Government. He is the co- author of "Big Data: A Revolution that Will Transform How We Work, Live and Think" (2013).

Smári McCarthy- Privacy, Security and Mailpile - Smári is the director of the International Modern Media Institute, a skilled programmer and a prominent member of the Icelandic Pirate Party. He has developed Mailpile- an encrypted web mail client.

Daniel A. Smith - Daniel is a Research Fellow with the SOCIAM Project at the University of Southampton. Daniel holds a PhD and a Master of Engineering in Computer Science from the University of Southampton, where he researched large scale exploration of heterogeneous data. He works on INDX, an open-source personal data store designed for long-term secure personal data storage and sharing.

Also very well facilitated by Wendy Grossman, and an interesting introduction from Eva Pascoe*

There was a rather good mindmap of the event (see picture above - and it's worth a thousand words, so I don't have to write any ). As you can imagine there were opinions from all over the spectrum, but I did think there was a coalescence around one major issue over the evening from all - that the social understanding, regulations and various laws about privacy, damage restitution and rights to people's own data are not in any way ready for the impact of Big Data.



To my mind the major issue then, over the next few years will be the "Wild West" that will occur until regulation, law and social understanding catch up. That there will be a Wild West cum Gold Rush is not disputable (though no doubt it will be), as there is just too much value in this arena (and too much naivete among the consumer/citizen base) for it not to. The question we need to address going forward is how wild we want it to be, and for how long. And the only way to minimise both in my view is to raise the understanding among those people whose data is being put into play - i.e. YOU!. The recent care.data shenanigans are merely the start of this game, and set the tone of the way it will be played in this coming Wild West - that one was headed off at the nick of time for now, but not before the NHS sold off a lot of the data for a pittance on the quiet (See Ben Goldacre's summary of this over here).

(More detail on my previous notes over here)

*Oh yes - one more thing - Eva Pascoe, the event organiser, made a fascinating observation - that In the history of technology, the more cuddly the logo, the more sinister the company. You have been warned

So, Twitter posts perfectly good results that make perfectly good sense for it's business progression, yet the stock falls sharply (down 10% at one point in aftre hours trading).

Why?

Well, unfortunately for Twitter, the Bubbletime Punditocracy wants to believe its a $50 stock, despite its fundamentals (which are very well known) implyingits more a $26 stock (it's IPO price). Twitter is what it is, and hasn't changed its model dramatically since its IPO, and its track hasn't shid=fted much from then - so its hard to imagine why its value should be be double its IPO valuation - Irrational Exuberance and Irrational Analysis at the same time.

To quote that great tech stock analyst, Mr D Bowie:

"And I want to believe in the madness that calls now
And I want to believe there's a light shining through somehow
And I want to believe, and you want to believe
And we want to believe"

(Cygnet Committee)

Facebook had the same problem, the Punditocracy was desperate to believe it was something it wasn't, it took them a good year or so to get their business to a point where it started to resemble their wishes, and its stock price driftef ever lower from its peak of irrational exuberance until that happened. Twitter is best advised to ignore the Pundits as well and just get on getting on with it.

Interesting 2 paragraphs from Fred Wilson's blog, talking about "what's next":

But the roadmap has been clear for the past seven years (maybe longer). The next thing was mobile. Mobile is now the last thing. And all of these big tech companies are looking for the next thing to make sure they don’t miss it.. And they will pay real money (to you and me) for a call option on the next thing.

It isn’t clear if the next thing is virtual reality, the internet of things, drones, machine learning, or something else. Larry doesn’t know. Zuck doesn’t know. I don’t know. But the race is on to figure it out. Trillions of dollars of collective market capitalizations are on the line. So a couple billion here or there is chump change. Except for the people who collect that chump change for selling them an option on the next thing. It’s real money to us.

I'm intrigued by the idea of a call option, I think it could be executed better than via VC funding though, Fred - now that would be disruptive

But I think Fred's largely right that Mobile was the last Next Thing - though strictly speaking its not "Mobile" now per se, but PC level processing power meeting Moore's Law and shrinking in size and price so it can be easily portable, with a damn good UI (think iPaq then iPhone). These "Smart" phones and "tablets" killed good old Planet Mobile dead in about 3 years (Motorola, Nokia, Blackberry - where are they now? They were earth shaking giants a few short years ago!)

Anyway, where is the Next Big Thing to be found is the question Fred asks. The future is of course here, just unevenly spread, so the trick is to see what bits of the future are here, now - and actually are going somewhere. Ten things that have changed exponentially in the "networked technology" areas we follow, in the time we've been writing Broadstuff (est 2006) are:

- Robotics (including the flying type)
- Data generation, usage and cost of processing it (aka "Big Data" - but I think the mpact will be felt indirectly - see this video by Phili Evans of BCG
- Penetration and usage of very cheap personal comms....
- .....especially those that are "Things"...
- ....and used to scrape data about "marketing value units" (aka people)
- WiFi Connectivity is increasingly ubiquitous, and whenever a powerful new comms system does that, big changes follow
- Smaller and smaller machine tools (including the over-hyped "3D Printer" but also a whole host of CNC tools)
- Games have moved from PCs to every device, and some games aren't really games any more as the principles move into other areas
- All manners of virtual/augmented reality devices (if Google Glasses don't make them irredeemably uncool)
- "Open" (ie other people's involuntarily exposed) Data - but sadly this will, in my opinion, probably be massively abused and then clamped down again, but its a short term shooting star.

As you can see, these are hardly New New Things, just things that were already here in 2006 and even then clearly had high potential. What's interesting is that they were all already on very predictable development vectors in 2006, but no one looked at them as killer technologies in those days. That was because at that time, their rate of development was still mainly all theoretical, and not provably valuable. To compare, here are 10 other things that were also floating around in 2006/7 that I thought also could happen sooner and haven't yet, but still may as they are all Big Next Next Things potentially.

- Widespread revolt against privacy-invasive free business models (it's starting now though)
- Modular hardware (Fred may recall Bug Labs from 2007)
- Open & portable social networks.
- "New" Search technologies (of which many have been tried over the last few years, a New New search hope appears every 2 years or so)
- Low cost and easy organisation of unstructured data
- Self learning software sorting out my media consumption, inbox and schedule (preferably materialising as a cross-media avatar with Marlene Dietrich's voice)
- VRM (Consumer to Business commercial tools)
- Effective voice recognition (the acid test - can it understand the Scottish accent...)
- And on that note, a near-real time "Babelfish" online service (to translate Scottish to English....)
- Various self-learning Algorithms that could predict things like the stock market, drive cars, etc etc

These are all here today, unevenly distributed, and still chugging along - but at slower rates than the various laws of networking, learning, Moores et al would predict. Typically there is a something in them that is missing, obstinately sticking at current capability or economically unavailable, awaiting the "key" to their leap over the Chasm. But all it takes is a small shift (think iPaq vs iPhone again) and over they go.

All you have to do to build your own mind-boggling portfolio of New Next Things To Watch is read the various Gartner Hype Curves for the last 10 years, and you will see a slew of things on the hot S curve one year and disappearing 2-3 years later. They don't go away though, and are still evolving in the Darwinian mud of technology species, it's just that something hasn't yet quite worked out for them yet. And somewhere in that stew already, are the next 10 New New Things.