Personal intelligent software agents to smarten your every day life

Billions of intelligent software agents working on behalf of their human 'client'/owner. Those agents augment what their 'clients'/owners can do, by f.i. A. monitoring news feeds and selecting the relevant items (Paper.li), B. track local-government decisions and report the relevant, impactful decisions C. keep an eye on their client's /Owners' health via digital sensors and signal when something is not normal What will be 'software-programmed' are software agents for a particular rare combination of circumstances that happens only once every 1,000 years but happens to you. The technology exists, but the 'personal intelligence software agents' eco-system is still in its infancy. Which companies will become the eco-system leaders of this emerging agent-based approach? Who will be the market leaders of the smart agent industry?

QR codes are brilliant, if used properly

Classic storytelling techniques and how it applies to content marketing

An insight into the subconscious

Brain-imaging techniques have given economists and marketeers a whole new set of tools to improve understanding of human decision-making processes. Result: an emerging interdisciplinary field of scientific research called Neuro-economics; a fusion of methodology and theory from neuroscience, economics, management and psychology. Our subconscious mind is a better predictor of our future behaviour than our conscious intentions would have us believe. In Neuro-economics, high-tech brain-imaging MRI-techniques are used to solve questions of an economic and marketing nature. Neuro-marketing, the discipline's sub-field and an area of most direct interest to business, narrows in on the consumer and his or her responses to marketing stimuli. It is the first time that biologists are collaborating with economists to shed light on economic and marketing theory. The brain is the machine behind the decisions that are being made in economics. This is an opportunity to get inside that machine and see precisely how it is working. No other methodes can bring you to access to this kind of data. A study examined the effect of celebrities in advertising. The study revealed that the presence of a celebrity enhanced memory retrieval and created positive associations. But only if the celebrity had some credibility in relation to the product. It also showed that the effect was rapid and did not require repeated exposure to achieve the desired effect. The techniques employed by neuroeconomists clearly have immense potential value, when turned to commercial ends. In the past companies have relied on consumer feedback through questionnaires and focus groups for direction on products and marketing. These methods take it as a given that people know their own minds enough to reliably indicate preferences. Which is not always so. The technology and our knowledge about the brain is developing at a rapid pace.

Why do we have brains?

Why do we and other animals have brains? Why we evolved one? Not to think, feel or to perceive the world or to think, but to control movement. We have a brain for one reason: to produce adaptable and complex movements. Sensory, memory and cognitive processes are all important, but they're only important to either drive or suppress future movements. Movement - contractions of muscles - is the only way you have of affecting the world around you. So think about communication – speech, gestures, writing, sign language – they're all mediated through contractions of your muscles. There can be no evolutionary advantage to laying down memories of childhoodor perceiving the color of a rose if it doesn't affect the way you're going to move later in life. Now for those who don't believe this argument, we have trees and grass on our planet without the brain, but the clinching evidence is this animal here – the humble sea squirt. Rudimentary animal, has a nervous system, swims around in the ocean in its juvenile life. And at some point of its life, it implants on a rock. And the first thing it does in implanting on that rock, which it never leaves, is to digest its own brain and nervous system for food.So once you don't need to move, you don't need the luxury of that brain. And this animal is often taken as an analogy to what happens at universities when professors get tenure, but that's a different subject. So I am a movement chauvinist. I believe movement is the most important function of the brain – don't let anyone tell you that it's not true. Now if movement is so important, how well are we doing understanding how the brain controls movement? And the answer is we're doing extremely poorly; it's a very hard problem. But we can look at how well we're doing by thinking about how well we're doing building machines which can do what humans can do. Think about the game of chess. How well are we doing determining what piece to move where? If you pit Gary Kasparov here against IBM's Deep Blue, well the answer is IBM's Deep Blue will occasionally win. And I think if IBM's Deep Blue played anyone in this room, it would win every time. That problem is solved. What about the problem of picking up a chess piece, dexterously manipulating it and putting it back down on the board? If you put a five year-old child's dexterity against the best robots of today, the answer is simple: the child wins easily. There's no competition at all. Now why is that top problem so easy and the bottom problem so hard? One reason is a very smart five year-old could tell you the algorithm for that top problem – look at all possible moves to the end of the game and choose the one that makes you win. So it's a very simple algorithm. Now of course there are other moves, but with vast computers we approximate and come close to the optimal solution. When it comes to being dexterous, it's not even clear what the algorithm is you have to solve to be dexterous. And we'll see you have to both perceive and act on the world,which has a lot of problems. But let me show you cutting-edge robotics. Now a lot of robotics is very impressive, but manipulation robotics is really just in the dark ages. So this is the end of a Ph.D. Project from one of the best robotics institutes. And the student has trained this robot to pour this water into a glass. It's a hard problem because the water sloshes about, but it can do it. But it doesn't do it with anything like the agility of a human. Now if you want this robot to do a different task, that's another three-year Ph.D. Program. There is no generalization at all from one task to another in robotics. Now we can compare this to cutting-edge human performance. So in my group, what we try to do is reverse engineer how humans control movement. And it sounds like an easy problem. You send a command down, it causes muscles to contract.Your arm or body moves and you get sensory feedback from vision, from skin, from muscles and so on The trouble is these signals are not the beautiful signals you want them to be. So one thing that makes controlling movement difficult is, for example, sensory feedback is extremely noisy. Now by noise, I do not mean sound. We use it in the engineering and neuroscience sense meaning a random noise corrupting a signal. So the old days before digital radio when you were tuning in your radio and you heard "crrcckkk" on the station you wanted to hear, that was the noise. But more generally, this noise is something that corrupts the signal. So for example, if you put your hand under a tableand try to localize it with your other hand, you can be off by several centimeters due to the noise in sensory feedback. Similarly, when you put motor output on movement output, it's extremely noisy. Forget about trying to hit the bull's eye in darts, just aim for the same spot over and over again. You have a huge spread due to movement variability. And more than that, the outside world, or task, is both ambiguous and variable. The teapot could be full, it could be empty. It changes over time. So we work in a whole sensory movement task soup of noise. Now this noise is so great that society places a huge premium on those of us who can reduce the consequences of noise. So if you're lucky enough to be able to knock a small white ball into a hole several hundred yards away using a long metal stick, our society will be willing to reward you with hundreds of millions of dollars. Now what I want to convince you of is the brain also goes through a lot of effort to reduce the negative consequences of this sort of noise and variability. And to do that, I'm going to tell you about a framework which is very popular in statistics and machine learning of the last 50 years called Bayesian decision theory. And it's more recently a unifying way to think about how the brain deals with uncertainty. And the fundamental idea is you want to make inferences and then take actions. So let's think about the inference. You want to generate beliefs about the world. So what are beliefs? Beliefs could be: where are my arms in space? Am I looking at a cat or a fox? But we're going to represent beliefs with probabilities. So we're going to represent a belief with a number between zero and one – zero meaning I don't believe it at all, one means I'm absolutely certain.And numbers in between give you the gray levels of uncertainty. And the key idea to Bayesian inference is you have two sources of information from which to make your inference. You have data, and data in neuroscience is sensory input. So I have sensory input, which I can take in to make beliefs. But there's another source of information, and that's effectively prior knowledge. You accumulate knowledge throughout your life in memories. And the point about Bayesian decision theory is it gives you the mathematics of the optimal way to combine your prior knowledge with your sensory evidence to generate new beliefs. And I've put the formula up there. I'm not going to explain what that formula is, but it's very beautiful. And it has real beauty and real explanatory power. And what it really says, and what you want to estimate, is the probability of different beliefs given your sensory input. So let me give you an intuitive example. Imagine you're learning to play tennis and you want to decide where the ball is going to bounce as it comes over the net towards you.There are two sources of information Bayes' rule tells you. There's sensory evidence – you can use visual information auditory information, and that might tell you to allow that red spot. But you know that your senses are not perfect, and therefore there's some variability of where it's going to landshown by that cloud of red, representing numbers between 0.5 and maybe 0.1. That information is available in the current shot, but there's another source of information not available on the current shot, but only available by repeated experience in the game of tennis, and that's that the ball doesn't bounce with equal probability over the court during the match. If you're playing against a very good opponent, they may distribute it in that green area, which is the prior distribution, making it hard for you to return. Now both these sources of information carry important information. And what Bayes' rule says is that I should multiply the numbers on the red by the numbers on the greento get the numbers of the yellow, which have the ellipses, and that's my belief. So it's the optimal way of combining information. Now I wouldn't tell you all this if it wasn't that a few years ago, we showed this is exactly what people do when they learn new movement skills. And what it means is we really are Bayesian inference machines. As we go around, we learn about statistics of the world and lay that down, but we also learn about how noisy our own sensory apparatus is, and then combine those in a real Bayesian way. Now a key part to the Bayesian is this part of the formula. And what this part really says is I have to predict the probability of different sensory feedbacks given my beliefs. So that really means I have to make predictions of the future. And I want to convince you the brain does make predictions of the sensory feedback it's going to get. And moreover, it profoundly changes your perceptionsby what you do. And to do that, I'll tell you about how the brain deals with sensory input. So you send a command out, you get sensory feedback back, and that transformation is governed by the physics of your body and your sensory apparatus. But you can imagine looking inside the brain. And here's inside the brain. You might have a little predictor, a neural simulator, of the physics of your body and your senses. So as you send a movement command down, you tap a copy of that off and run it into your neural simulator to anticipate the sensory consequences of your actions. So as I shake this ketchup bottle, I get some true sensory feedback as the function of time in the bottom row.And if I've got a good predictor, it predicts the same thing. Well why would I bother doing that? I'm going to get the same feedback anyway. Well there's good reasons. Imagine, as I shake the ketchup bottle,someone very kindly comes up to me and taps it on the back for me. Now I get an extra source of sensory information due to that external act. So I get two sources. I get you tapping on it, and I get me shaking it, but from my senses' point of view, that is combined together into one source of information. Now there's good reason to believe that you would want to be able to distinguish external events from internal events. Because external events are actually much more behaviorally relevant than feeling everything that's going on inside my body.So one way to reconstruct that is to compare the prediction – which is only based on your movement commands – with the reality. Any discrepancy should hopefully be external. So as I go around the world, I'm making predictions of what I should get, subtracting them off. Everything left over is external to me. What evidence is there for this? Well there's one very clear example where a sensation generated by myself feels very different then if generated by another person. And so we decided the most obvious place to start was with tickling. It's been known for a long time, you can't tickle yourself as well as other people can. But it hasn't really been shown, it's because you have a neural simulator,simulating your own body and subtracting off that sense. So we can bring the experiments of the 21st century by applying robotic technologies to this problem. And in effect, what we have is some sort of stick in one hand attached to a robot, and they're going to move that back and forward. And then we're going to track that with a computer and use it to control another robot, which is going to tickle their palm with another stick. And then we're going to ask them to rate a bunch of thingsincluding ticklishness. I'll show you just one part of our study. And here I've taken away the robots, but basically people move with their right arm sinusoidally back and forward. And we replay that to the other hand with a time delay. Either no time delay, in which case light would just tickle your palm, or with a time delay of two-tenths of three-tenths of a second. So the important point here is the right hand always does the same things -- sinusoidal movement. The left hand always is the same and puts sinusoidal tickle. All we're playing with is a tempo causality.And as we go from naught to 0.1 second, it becomes more ticklish. As you go from 0.1 to 0.2, it becomes more ticklish at the end. And by 0.2 of a second, it's equivalently ticklish to the robot that just tickled you without you doing anything. So whatever is responsible for this cancellation is extremely tightly coupled with tempo causality. And based on this illustration, we really convinced ourselves in the field that the brain's making precise predictions and subtracting them off from the sensations. Now I have to admit, these are the worst studies my lab has ever run. Because the tickle sensation on the palm comes and goes, you need large numbers of subjects with these stars making them significant. So we were looking for a much more objective way to assess this phenomena. And in the intervening years I had two daughters. And one thing you notice about children in backseats of cars on long journeys, they get into fights – which started with one of them doing something to the other, the other retaliating. It quickly escalates. And children tend to get into fights which escalate in terms of force. Now when I screamed at my children to stop, sometimes they would both say to me the other person hit them harder. Now I happen to know my children don't lie, so I thought, as a neuroscientist, it was important how I could explain how they were telling inconsistent truths. And we hypothesize based on the tickling study that when one child hits another, they generate the movement command. They predict the sensory consequences and subtract it off. So they actually think they've hit the person less hard than they have -- rather like the tickling. Whereas the passive recipient doesn't make the prediction, feels the full blow. So if they retaliate with the same force, the first person will think it's been escalated. So we decided to test this in the lab. We bring in two adults. We tell them they're going to play a game.And so here's player one and player two sitting opposite to each other. And the game is very simple. We started with a motor with a little lever, a little force transfuser. And we use this motor to apply force down to player one's fingers for three seconds and then it stops. And that player's been told, remember the experience of that force and use your other finger to apply the same force down to the other subject's finger through a force transfuser – and they do that. And player two's been told, remember the experience of that force.Use your other hand to apply the force back down.And so they take it in turns to apply the force they've just experienced back and forward. But critically, they're briefed about the rules of the game in separate rooms. So they don't know the rules the other person's playing by. And what we've measured is the force as a function of terms. And if we look at what we start with, a quarter of a Newton there, a number of turns, perfect would be that red line. And what we see in all pairs of subjects is this – a 70 percent escalation in forc on each go So it really suggests, when you're doing this – based on this study and others we've done – that the brain is canceling the sensory consequences and underestimating the force it's producing. So it re-shows the brain makes predictions and fundamentally changes the precepts. So we've made inferences, we've done predictions, now we have to generate actions. And what Bayes' rule says is, given my beliefs, the action should in some sense be optimal. But we've got a problem. Tasks are symbolic -- I want to drink, I want to dance – but the movement system has to contract 600 muscles in a particular sequence. And there's a big gap between the task and the movement system. So it could be bridged in infinitely many different ways. So think about just a point to point movement. I could choose these two paths out of an infinite number of paths. Having chosen a particular path,I can hold my hand on that path as infinitely many different joint configurations. And I can hold my arm in a particular joint configuration either very stiff or very relaxed. So I have a huge amount of choice to make. Now it turns out, we are extremely stereotypical. We all move the same way pretty much. And so it turns out we're so stereotypical, our brains have got dedicated neural circuitry to decode this stereotyping. So if I take some dots and set them in motion with biological motion, your brain's circuitry would understand instantly what's going on. Now this is a bunch of dots moving. You will know what this person is doing, whether happy, sad, old, young -- a huge amount of information. If these dots were cars going on a racing circuit, you would have absolutely no idea what's going on. So why is it that we move the particular ways we do? Well let's think about what really happens. Maybe we don't all quite move the same way. Maybe there's variation in the population. And maybe those who move better than others have got more chance of getting their children into the next generation. So in evolutionary scales, movements get better. And perhaps in life, movements get better through learning. So what is it about a movement which is good or bad? Imagine I want to intercept this ball. Here are two possible paths to that ball. Well if I choose the left-hand path, I can work out the forces required in one of my muscles as a function of time. But there's noise added to this. So what I actually get, based on this lovely, smooth, desired force, is a very noisy version. So if I pick the same command through many times, I will get a different noisy version each time, because noise changes each time. So what I can show you here is how the variability of the movement will evolve if I choose that way. If I choose a different way of moving – on the right for example – then I'll have a different command, different noise, playing through a noisy system, very complicated. All we can be sure of is the variability will be different. If I move in this particular way, I end up with a smaller variability across many movements. So if I have to choose between those two, I would choose the right one because it's less variable. And the fundamental idea is you want to plan your movements so as to minimize the negative consequence of the noise. And one intuition to get is actually the amount of noise or variability I show here gets bigger as the force gets bigger. So you want to avoid big forces as one principle. So we've shown that using this, we can explain a huge amount of data – that exactly people are going about their lives planning movements so as to minimize negative consequences of noise. So I hope I've convinced you the brain is there and evolved to control movement. And it's an intellectual challenge to understand how we do that. But it's also relevant for disease and rehabilitation. There are many diseases which effect movement. And hopefully if we understand how we control movement, we can apply that to robotic technology. And finally, I want to remind you, when you see animals do what look like very simple tasks, the actual complexity of what is going on inside their brain is really quite dramatic.

The emerging data science agency

Neuroscience applications for more effective marketing

Because traditional market studies do not guarantee the success of a product, marketers now turn to neurosciences; to more effectively decode the subconscious part of our brain to know our desires better.

Magnetic Resonance Imaging (MRI-scanning) improves the identification of advertisements and products which seduce and displease us. If badly used, some of the neurosciences applications could deal a new blow to personal freedoms. From France to the U.S.A., via Italy and the United Kingdom, this documentary examines this new avatar of consumer society.

Neuroscience: mapping the human connectome

Sebastian Seung is mapping a massively ambitious new model of the brain that focuses on the connections between each neuron. He calls it our "connectome," and it's as individual as our genome; and understanding it could open a new way to understand our brains and our minds.

The Price of altruism

Oren Harman reveals the discoveries of George Price - who strove to understand evolution's greatest riddle: altruism.

Singularity Summit 2011

Web 2.0 Summit 2011

Update of Mary Meekers mobile trend slides (october 2011)

Mary Meeker presented yesterday (october 18, 2011) a fact-based update of her mobile trend slides at Web 2.0 Summit 2011.




The biggest digital trends, according to Mary Meeker:
1. We are living through a once-every-10/20-years technology evolution: the mobile computing cycle
2. Global mobile internet growth 35% Year-on-Year; smartphones surpassed feature phone shipments and mobile usage still has huge upside
3. Digital user interface moving to touch, sound & motion sensing (Siri, Kinect)
4. Next level commerce = fun / convenient / fast / price-transparent
5. Accelerating growth of eCommerce; continues to gain share from offline
6. mCommerce has lifted off
7. Local commerce is rejuvenated by mobile
8. Magazine concept is rejuvenated by mobile
9. Magazine concept transforms into an inspiration experience, combined with next level commerce (fast/convenient/fun/price-transparent)
10. Magazine concept transforms into a see-enjoy-yell-(or wave)-and-buy-(on a mobile device)-concept
11. In a mobile-ized, transparent world pricing matters a lot (in addition to branded differentiation)
12. Empowerment of people via connected mobile devices
13. Apple, Google, Amazon & Facebook remain mega-leaders; Chinese and Russion companies continue to step up
14. In last three years China added more internet users than exist in USA.
15. Content creation changed forever; How does one create differentiated content in an economically viable manner, when few want to pay for it? Joanne Bradford, chief revenue officer at web media giant Demand Media, gives the - oversimplified - answer:

Symbiothic Artificial General Intelligence

David Orban gave a talk at AGI-10 "Symbiotic Artificial General Intelligence (AGI) and Emergent Intelligence: Is a Planet Enough?"

AGI is also referred to as Strong AI: Artificial Intelligence that matches or exceeds human intelligence — the intelligence of a machine that can successfully perform any intellectual task that a human being can.

There is wide agreement among artificial intelligence researchers that intelligence is required to do the following:
reason, use strategy, solve puzzles, and make judgments under uncertainty;
represent knowledge, including commonsense knowledge;
plan;
learn;
communicate in natural language;
and integrate all these skills towards common goals.

Gary Hamel: Reinventing management

Watch Gary Hamel, make the case for rethinking how we mobilize people and organize resources to productive ends. "Modern” management was developed more than a century ago to maximize standardization, specialization, hierarchy, control, and shareholder interests.

While that model delivered an immense contribution to global prosperity, the values driving our most powerful institutions are fundamentally at odds with those of this age—zero-sum thinking, profit-obsession, power, conformance, control, hierarchy, and obedience don’t stand a chance against community, interdependence, freedom, flexibility, transparency, meritocracy, and self-determination.

It’s time for reinventing management.

Where are smartphones being used?

Source: Tatango SMS Marketing

Context & Core

Brandwashed

View a brain-scan made as part of a 'De Telefoongids & Gouden Gids'-funded program to analyze and gain insights in brand appeal.

The brain-scan was made at the University of Amsterdam in cooperation with Neurensics and Department of Psychology.

Chaos happens, let's make better use of it: value of unintended consequence

Every new invention changes the world...in ways both intentional and unexpected. Historian Edward Tenner illustrates the gap between our ability to innovate and our ability to foresee the consequences.

Key message of Tenner: Chaos happens, let's make better use of it.

Smart companies not only compete on decreasing the cap, but also on managing the unintended consequences.

Brand Asset Valuator 2011

Brand Battle 2011 - De sterkste merken van Nederland

presentationsjeffreykruk

How to compete (and win) by challenging assumptions

New disciplines have always faced the usual initial resistance of any disruptive innovation.....not only in the past.

Due to false (outdated) assumptions, neuroscience, QR codes and mobile payments (still in its infancy) face scepticism (coupled with a degree of uncertainty), as to whether it could deliver on its promises.

What would be the most appropriate strategy?
Start programmes of frequent, inexpensive experimentation that allow for cheap failures. The holy grail of the emerging Marketing Eco System lies in how you get yourself and others to try new things.

Just do it. Start in beta. Learn and improve. Challenge the (outdated) assumptions of the mainstream. And win.

Challenge your colleagues to recognise how much of their world and their expectations of the future are based on a sea of assumptions, rather than observations. First thing to do: show them this video.

A 'chromosome-based-Linkedin'-app to check your family tree

The concept of a 'chromosome-based-Linkedin' already exists for customers of 23andMe, Family Tree DNA, and others who've had their DNA sequenced.

They can connect with people who have genetic matches with them through the companies' websites, as well as through the forums, email lists, and projects blossoming all over that have been created by citizen scientists, do-it-yourselfers, students, etc., where they share, compare, and analyze their DNA sequences in many ways.

Watch this TEDtalk and imagine tomorrow

Emerging attractive blue ocean markets as a consequence of combining the progress made in robotics, neuroscience and Artificial Intelligence

Are your expectations of the future based on a sea of assumptions, or fact-based observations?
Observations of what is already happening right now....

Now that you have seen the video. Did you know this? How are you acting upon it? What can machine learning do for your organisation? How can your organisation benefit from this emerging opportunity?

Think of what Artificial Intelligence software can do for the control and perception mechanisms in your organisation.

Media consumption and habits across generations

Created by: MBA Online

Mobile phone replacing your wallet. Mobile payments redefining commerce.

Your mobile phone probably hasn’t replaced your wallet yet, but it could in the next few years. One of the defining features of the next generation of smartphones will be a technology called Near Field Communication (NFC).

Instead of whipping out your wallet at a store, via NFC you'll simply tap or wave your phone to make a payment.



As NFC phones get into the hands of consumers, mass adoption of in-store mobile payment systems seems inevitable.....as long as NFC proves to be secure. Both consumers and retailers will benefit from the simplicity and convenience of these tap-and-go systems.

The challenges of openness & collective intelligence

Think Mobile Event 2011 in London

It’s not a debate anymore about mobile website or apps, you need to have both.

To help customers book easier, ebookers launched in January 2011 the first fully transactional multi-product mobile site of any online travel agency in Europe. “What we wanted was really to have 100% the same product that we have on desktop,” said Rob Define, ebookers' Director of Product Strategy. This meant the mobile site offered a lower cost, faster development time and more straightforward support than an app. ebookers also knew that a mobile website would bring more bookings than an app.

While in the early days of smartphones customers could visit the ebookers desktop site via their mobiles, since launching their mobile site ebookers experienced a 90% jump in visitors and bookings via mobile during the first five months after launch.

Put this on

Rather than concentrating on total audience, media companies should concentrate on the net future value of each individual (reader). There are more ways to recognize value than in the traditional way of selling audiences to advertisers. The core value in media is not in the content and not in the size of the audience, the core value of media companies is in the trusted relationships with individuals; in the depth of data of individuals and in the generated level of relevance for each individual. Key question is: how to add and extract that value? People used to say that information is power, but that's no longer the case. It's analysis and use of the data that is the power.


Media companies must challenge every assumption about the role of content. Content is not a product to sell, but a device to generate and gain more signals & information about each individual content-user. Smart media companies are able to use that data to target (branded) content, services, m-Commerce, t-Commerce, e-Commerce, marketing partnerships, commercial conversations and advertising.

Media companies must also challenge their current, outdated, irrelevant, KPI's.
The challenge with KPI's is selecting the right ones. The key requirement for leading indicators is that we track them because there is a demonstrable link with key future outcome indicators.

In his book 'How brands grow' Byron Sharp proves that 'retention-percentage' and 'defection-percentage' are currently often used, but misleading outcome indicators. Key Outcome Indicators (KOI) are 'penetration-percentage' and 'purchase'/'sales'.

Neuroscience has proven that former leading indicators as 'awareness' and 'consideration' are misleading. 90% of our purchases are processed by the brain's subconscious. What should be Key Leading Indicators (KLI)? Our project 'Van hersen-scan tot kassa-scan' will learn us what kind of brain activation patterns will be Key Leading Indicators.

Everything is a Remix

The century of the self

How sensors shape our Algorithm Eco System

The art of quantitative prediction is reshaping business. Technology evolves -> Sensors increase and improve -> Big data grows exponentially -> Development of mathematical models -> Resource allocation based on algorithms.
Being ten microseconds ahead is the distinctive competitive advantage in the unfolding, real-time, algorithm eco system.

In an interesting TEDtalk, Kevin Slavin explains how algorithms affect our everyday lives. Algorithms can make our lives better by recommending the right movies, but can also cause financial ruin.



Our financial system has become increasingly dependent on quants - math wizzards and computer programmers in the engine room of our financial system - trying to quantify human (economic) behaviour with mathematical models.

Building brands & driving sales by activating mirror neurons

Mirror neurons - the neurons that trigger the same responses in our brain whether we do something ourselves or whether we observe someone else doing the same task - form the foundation of influencing decisions about what products and brands we purchase. Indeed, Future actions (i.e. purchase decisions) can be predicted from registered brain activity patterns .

Magazine advertising is fairly effective at triggering mirror neurons by visualizing other people enjoying, for example, Häagen-Dazs ice-cream.

Observing someone else enjoying delicious Häagen-Daz ice-cream will trigger the same reaction in our brain as if you had one in your own hand. This neurological response generates a desire for ice-cream that can only be satisfied by buying a real one.

Recent research shows that well executed magazine ads can be impactful enough to create a false memory of having tried a product that doesn’t even exist.

Researchers Rajagopal and Montgomery showed subjects either high imagery or low imagery versions of magazine ads for a fictitious popcorn product, Orville Redenbacher Gourmet Fresh. Other subjects were allowed to consume “samples” of the invented product which were actually a different Redenbacher popcorn.

A week later, all of the participants were surveyed to determine their attitudes toward the product and how confident they were about their opinions. Members of the group that viewed the more vivid ad were as likely to report that they had tried the product as the group that actually consumed the samples. The group that saw the low imagery ads were less likely to report they had tried the product, and had weaker, less favorable opinions about it.

Changing the brand to an unknown name, the fictitious “Pop Joy Gourmet Fresh,” reduced the false memory effect. I presume that the more ubiquitous the product and brand, the more likely these false recollections are to occur.

This study shows the power of magazine ads that incorporate vivid imagery – clearly, paper has once again shown itself to be an effective medium. These magazine ads can apparently create the impression of experiencing the product in consumer brains, and can increase positive feelings about the product.

Clearly, it’s worth taking the time to create superb images – mouth-watering, well styled closeups for food products, for example. For other products, images that emphasize the products sensual aspects – textures, scents, etc. – would likely work best, even though the sensory experience will be in the mind of the viewer.

(Sources: tdgNeuroBrand & R. Dooley)

Relationship between brain activation pattern & intangible value of a brand

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Neuroscience: data mining & visualization

How to apply the generated brain-activation data to improve marketing ROI?

Data-driven neuroscience will need machine learning because of the curse of dimensionality.

Neuro secrets of superbrands

The BBC program, Secrets of the Superbrands, looks at why technology megabrands such as Apple, Facebook and Twitter have become so popular and such a big part of many people’s lives.

UK neuroscientists suggest that the brains of Apple devotees are stimulated by Apple imagery in the same way that the brains of religious people are stimulated by religious imagery.

DigitalNow 2011

Author Tomi Ahonen delivers the opening keynote presentation at digitalNow 2011 at Disney's Grand Floridian Resort & Spa

An effective economy-of-everyday-life-innovation

How to intervene meaningfull with commuters at critical inflection points?



What is the secret behind it's success? The concept has taken into account the critical success factors for economy-of-everyday-life-innovations:

1. Find a practice that is common and trivial enough
2. Remember that self-evident issues are in many cases the platform for new innovation
3. Become embedded in current practices of everyday life
4. Build new services on the basis of existing ways of doing
5. Help your potential customers to learn new forms of practices

The Transmedia Business Model Canvas

Technological development: robotica and gaming

Nieuwe technieken op het gebied van robotica en gaming zorgen voor een revolutie in de zorg. De computertechniek brengt tevens grote veranderingen in oorlogsvoering.

How to design effective business models

A moral operating system should be developed at a European level, not at a national level

There are a million thing you can do with cookie data. But we should not have a dialogue about what we CAN do with cookie data, but about what we SHOULD do with data. It's about making ethical decisions.

It makes no sense to have a dialogue at a national level on this topic. The online world is a world without nation states; a world without national borders. To be effective, a moral operating system has to be formed on - at least - a European level.

Imagine exponential-growth-impact of techological innovations (faster, smaller, cheaper, better)

When trying to understand the impact of exponentially growing techological innovations (faster, smaller, cheaper, better) on our Marketing Eco System, we often - unconsciously - assume a linear growth. But if you think about it, if you have a lily pad and it just divided every single day....two, four, eight, 16....in 15 days you have 32,000. What do you think you have in a month? We're at a billion.

Try to start to think exponentially to imagine how leveraging cross-disciplinary, exponentially growing technologies is affecting our Marketing Eco System.

In case of understanding consumer behavior: from cheaper, but higher-resolution MRI-scans to improving mobility of neuro imaging and next level real-time data-gathering & -visualization tools.

In case of healthcare: from low-cost gene analysis to the ability to do powerful bio-informatics to the connection of the Internet and social networking.

The current technology is able to make the next better by itself. That is new.

Augmented reality is not changing what you see, but how you see it; new ways to see, not new things to look at. Reality is not augmented by adding a layer, but by adding augmented sensors. Connectivity of people with data should not happen solely via the eye, but also via other senses.



The morality of objects from anonymous to highly disruptive to your personal space. Demolishing the public space.



Every generation threatens the generation before. The current technology is able to make the next better by itself. That is new. The people who are in charge now hardly know how things work in the new marketing eco system, the grown ups are the next ones down the list. The grown ups could not be disruptive anymore....the grown ups have work to do. Proving that networks are stronger than hierarchies.

Financial warning sense by tactile feedback

We have trouble controlling our consumer impulses, and there's a gap between our decision and the consequences. This is magnified by the digitization of money. When we pull a product off the shelf, do we know what our bank account balance is, or whether we're over budget for the month? Our existing senses are inadequate to warn us.

The Proverbial Wallet gives a financial warning sense at the point of purchase by un-abstracting virtual assets. Tactile feedback reflecting our personal balances and transactions helps us develop a subconscious financial sense that guides responsible decisions. In addition to providing a visceral connection to our virtual money, tactile output keeps personal information private and ambient.

The Proverbial Wallets are working prototypes, tough enough to sit on. They communicate with a cellphone through Bluetooth, using its data connection to get financial information from the user's bank accounts.

Source: http://eco.media.mit.edu/static/proverbialwallets/index.html

The Arab Spring, a rebirth far beyond a social media revolution

While some call it the Facebook-revolution, the Arab Spring (which began in Tunis) is far beyond a social media revolution...most Egyptians have no internet access at all. The Arab Spring is a rebirth of Islamic modernism.

Many Islamic movements in the Middle East tend to be authoritarian. But an authoritarian political culture, as Islamic modernists argue, should not be confused with the very origin of Islam. Realize that the main cause of the Arab Spring lies in the autohoritarian political culture of the whole region, not just Islam. Citizens in the Middle East have a problem with the authoritarian political culture and are motivated to change that political culture.

In the 19th century, when Islamic modernists were looking at Europe as an example (realizing that Europe has many things to admire: like science and technology, but also democracy, parliament, the idea of representation and the idea of equal citizenship), the Islamic modernists were independent and self-confident.

With the fall of the Ottoman Empire, in the early 20th century, the Middle East was colonized. This caused not only a very sharp decline in liberal ideas in the Muslim world, and a defensive, rigid, reactionary Arab mindset, the colonization of the Middle East also caused an anti-colonization culture. Europe became an enemy to fight and to resist.

When the colonial period ended, what you had in place of that was: dictators, suppressing democracy; suppressing its own people including the Muslims, and they reacted in reactionary ways.

With the Arab Spring, Islamic modernism is having a rebirth. Arab masses revolting against their dictators, are asking for democracy and freedom. And they do not turn out to be the Islamist fundamentalists that the dictators were always using to justify their regime. Democracy is a process, not an overnight achievement, but this is a promising era in the Middle East.

The language of a fluid, non-linear world of mutuality

How to survive disruptive innovations

How to achieve results beyond your imagination

Sanoma is a collective mind of over 20.000 individual employees. Until recently, the combined intelligence of a group has been inversely proportional to group size. Why? Because it was just to inefficient to share knowledge, to access what other colleagues were doing, thinking or sensing. Until recently, it has been hard to think and act as one ‘Sanoma-organism’. Caused by disconnection in space and time.

Today, open source, webbased wiki-technology beats these (former) limitations and empowers Sanoma colleagues to form dynamic networks, generating ’smart’ results to compete more effectively and to adapt faster to a changing world.

The Sanoma Wiki facilitates 20.000 individuals to generate valuable group output as a byproduct, without regard of institutional models. Wiki-technology enables the company to coordinate all activities of individual Sanoma employees. Colleagues have - by working together - made the first steps in achieving a positive relationship between group size and the combined intelligence & productivity of the group. Our game-changing objective: Turn a former weakness - Sanoma's group size - into a strength.

The 'only' limitation left in this disruptive process innovation is a widespread, fundamental mindset change....Changing from a 'span of control' to a 'span of support'-mindset....Change an institutional way of organizing into a business culture of working together in true collaboration to achieve common outstanding results....beyond what we have done before.

There are three basic 'working together cultures'. Only one of which is a truly collaborative 'working together culture'.*

The first 'working together culture' is labelled a 'Compliance Culture'. This is when each team member independently responds to the challenge by taking action in her own area. In other words, everyone on the team complies with the need to do something, but avoids working together. For example, A divisional leadership team that was required to reduce overall headcount by 10% to meet the corporation's goals. With very little discussion, each person agreed to cut 10% of the people from their own function and report the numbers back to the divisional controller. While this "spread the pain evenly" approach indeed met the corporate requirement, there was probably a better way.

The second 'working together culture' is labelled a 'Cooperation Culture'. Here again each person develops and implements his own plans, but in this case shares what he is doing with the group. While there is some amount of joint discussion, the focus is still on individual actions rather than a collective strategy. For example, when one technology company needed to increase its sales performance, the districts were all given significantly higher targets. The district managers then went about achieving these targets in different ways. Some increased individual sales quotas across the board; others reallocated resources to higher-potential customers; and still others focused on closing the gap with services contracts. The managers shared these approaches on their weekly calls, and gave each other feedback. But they never created a joint strategy to leverage their combined resources, ideas, and talents. In the end, while some districts hit their targets, the overall numbers were disappointing.

The third 'working together culture' is labelled a 'True Collaboration Culture'. In both of the cases described above, a 'True Collaboration Culture' might have led to a more robust and effective outcome. In the headcount example, the leadership team might have identified specific areas where headcount could be reduced by more than 10%, considered ways of consolidating similar activities into shared service centers, or any number of other possibilities. In the sales example, the district managers might have reallocated resources across districts, created joint campaigns for particular products, or brainstormed many other ideas that could have been quickly tested and possibly scaled.

What's interesting is that neither team consciously decided not to collaborate. Instead they did what came naturally, which is to work either completely or partially on their own.

The reality is that reaching a 'working together culture' of true collaboration is difficult. It requires subordinating individual goals to collective achievement; it means engaging in tough, emotional give-and-take discussions with colleagues about strategies and ideas; and it often leads to working in new ways that may not be comfortable or easy. So given these difficulties, most teams find it easier to talk about collaboration rather than do it.

It doesn't have to be this way. Teams can address their challenges through true collaboration, and by doing so can achieve outstanding results. The starting point however is to make a conscious — and collective — decision to go beyond compliance and cooperation.

Within Sanoma we have succeeded to overcome the - understandable - resistance to this disruptive way of true collaborative dynamic-network-organizing and reached the tipping point. I am confident that the network effect will continue, building valuable group output and achieving results that were once only available in our imagination.

* Source: Harvard Business Review, Teams That Only Think They Collaborate, by Ron Ashkenas, 2011

How to prevent info filters leading to a society of info junk food

How to get profound insights within one minute by brilliant data-visualization

Disruptive innovations in science: daring to transcend outdated conventions to productively lose control

The BBC4 documentary 'Dangerous knowledge' looks at four brilliant mathematicians - Georg Cantor, Ludwig Boltzmann, Kurt Gödel and Alan Turing - who dared to transcend outdated assumptions and conventions, but which tragically drove them insane and eventually led to them all committing suicide.

The documentary begins with Georg Cantor, the great mathematician whose work proved to be the foundation for much of the 20th-century mathematics. He was eventually driven insane trying to prove his theories of infinity.




Learn more of Ludwig Bolzman's entropy theory by this TED talk. And an introduction of Richard Feynman.


Learn more of Richard Feynman by this TED talk. Key message: go for less baloney and for more ham.

Intersection Day One: business models agnostic to unfolding solutions for complex systems

When disruptive innovations occur, people keep behaving in the same way.....still driven by outdated assumptions. When society adopts new tools, it takes a while before 'the mainstream' adopts mindset, culture and new behaviours to align themselves with what is possible. (f.i. Monks continued to handdraw illustrations on books printed by Guttenberg's press; behaviours driven by outdated assumptions). Nowadays, together (in collaborative networks of individuals) everything is possible, but 'the mainstream' still has to align themselves mentally and culturally.

We know how to change with the new tools, products, processes or services, we just don't do it, because we still don't think in a way that is aligned with these new possibilities.
Invention is creating stuff, innovation is creating value.
Innovation = Idea (product/service/proces/new way of thinking/new way of doing) + Impact
Innovation = Impactfull leverage of ideas. Creating impact. Imagination made count.
Incremental innovation
Three layers to find the breakthrough of disruptive innovation: The space (the meanings of the space, the culture) , the system (how the systems works within that space, the subjects (the indidual value proposition, the individual players).
Disruptive innovation example: Netbook took in 1 year 10% of the global market. Before no one thought about it.

Hierarchies maintain the status quo. Hierarchies fix our mental models. Hierarchies ensure people think the same.
Hierarchies are being dissolved in a networked globalised participatory society.
Innnovation in hierarchies (Apple company): One size fits all, determined by the authority (Steve Jobbs)
Innovation in networks (Google): Groups form around interest and solve problems themselves.
The law of unexpected win, win, wins

The challenging journey of holistic, networked, disruptive innovation.
Re-designing the future of business. How to (business re-)design for openness?
Belief 1 - Valueing diversity: value being created at the intersection of disciplines
Belief 2 - Look to extremes: will give you a glimpse of the future
Belief 3 - A 'designing systems approach': Unit of analysis can sometimes be meta-level, sometimes be a business model. Scalable approaches. solutions for complex systems can be combinations of a product, process, brand or service. Business models agnostic to unfolding solutions for complex systems..

Learnings with open models:
A. Conscious contributions (Wikipedia) versus unconscious contributions (Google, Last fm)
B. Yesterday: scale is good, because it makes it cheaper. Tomorrow: scale is good because it makes the whole Marketing Eco System better. B1: Makes the product/service/brand better). B2: Improves the personal relevance. B3. Makes the concept smarter. .

Data is the new oil & soil. Discover hidden patterns in data by visualization.
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Intersections Day Two: Josephine Green from Dott Cornwall on Vimeo.

Synthetic biology: creating artificial genomes to efficiently produce biofuels

Being able to design and - artificially - create entire genomes, instead of just short lengths of DNA, will dramatically speed up the process of engineering microbes that can carry out tasks such as efficiently producing biofuels or vaccines.

Until last year, biologists hadn't been able to make large enough pieces of DNA to create an entire genome. Though living cells routinely make long stretches of DNA, a DNA synthesis machine can't do the same.

In May 2010, ­researchers at the J. Craig Venter Institute announced their solution to this problem:

• Step 1. Using yeast cells to stitch together thousands of fragments of DNA made by a machine;


• Step 2: pooling the longer pieces;


• Step 3: repeating the process until the genome was complete;


• Step 4: inserting the genome into bacterial cells that are about to divide and grow the bacteria in a medium hostile to all cells except the ones harboring the synthetic genome.

The researchers tried their solution. And it worked! We are now able to create bacteria which are the first living creatures with a completely artificial genome. The microbes' entire collection of genes was edited on a computer and assembled by machines that create genetic fragments from chemicals and by helper cells that pieced those fragments together.

The same researchers have also developed a faster, yeast-free way to assemble large pieces of DNA in a bottle. They are using these methods to rapidly synthesize the viral DNA needed to speed up the production of influenza vaccines.

The creation of the synthetic cell is part of an effort to design a "minimal cell" containing only the most basic genome required for life. Synthetic biologists could use this minimal cell as the basis for cells that efficiently produce biofuels, drugs, and other industrial products.

Right now, the technique for incorporating his synthetic genome into living cells works only with mycoplasmas, which are useful for experimentation but not for industrial purposes. By adapting this system to work with a broader group of bacteria, it could be used to speed up the process of engineering microbes that make a wide variety of products.

At least two challenges remain:

1. Developing appropriate recipient cells for genome transplants, and

2. Finding ways of working with even larger pieces of DNA.

(Source: Technology review, MIT)

How to uncover opportunities to connect with young consumers

In order to uncover influential opportunities for your brand to connect with young consumers, it is not enough to base your allocation decisions on 'time spent on a media channel'.

In order to uncover opportunities for your brand to connect with young consumers, you need to truly understand their core motivations for using each specific channel. Without digging deeper into motivations (researching the greater picture of how and why young consumers are using f.i. social channels), much of the opportunity will remain unearthed.

Simon Sinek: What, How, Why & Trust

Planet of the apps - Android strikes back

Update of Sanoma's app development proces by Herman Kienhuis at Amsterdam Mobile Convention, April 20, 2011, Amsterdam

Neuroscience: what’s it good for?

It’s only a matter of time before neuroscience methods become a standard part of what researchers do. As we at Sanoma Media Netherlands learn more about the way people interact with brands and marketing, and about how people make decisions, we realise more that we need to be going beyond the conventional research-tools.

Neuroscience-based research gives us additional insights about how consumers make decisions and therefore will lead us to improve the communications- and business-solutions we offer to our business partners.

Are neuroscience research methods able to predict 'commercial conversation' success with more accuracy than conventional research methods?
A study* considered 24 ads and a measure of increase in sales due to ad-viewing and found that, when amygdala, hippocampus and parietal activation were combined and correlated with sales increase, a correlation value of 0,93 was observed.

Sanoma's advertisers have been receptive to our neuroscience-based research because they see that they’re getting insights that they wouldn’t have got beforehand from a regular survey.

When are which neuroscience research methods helpful?
There are lots of different ways of doing neuroscience-based research, some of which are more suited to some things than others.

A. Eyetracking - allows the computation of:
1. How quickly attention is directed to the brand on a package, or an ad (Attention)
2. How long viewers look to the brand on a package, or an ad. The number of fixations of a specific ad element is correlated with later recall of that specific object (Memory)
3. For static and dynamic stimuli, different analytics techniques need to be used.

B. fMRI - enables us to look at activation in specific brain areas. Studies have indicated that specific areas of the brain are activated during specific types of cognitive and emotional processing. Questions such as 'which one of two ads is more emotionally engaging/memorable/attention grabbing', are best addressed through fMRI. fMRI provides answers to the following questions:

1. Does a specific ad evoke an emotional reaction
2. Are elements from the ad stored in long-term memory?
3. Is an ad processed attentionally?

Emotional processing is indicated by neural activity in a network of areas in the amygdala
Memory processing is indicated by neural activity in a network of areas in the hippocampus
Attentional processing is indicated by neural activity in a network of areas in the occipital, parietal and the frontal cortex

C. EEG - Questions that can be addressed by EEG
1. Which parts of an ad are more alerting
2. Does a particular feature of an ad evoke a more positive, or a more negative reaction to the viewer
3. How does the exact time course of processing differ across different ads?

Conclusion: Investing in neuroscience research in advance of an advertising campaign is usefull to test the likely effectiveness of the material. Insight into neuroscience techniques is necessary to make good research investment choices and to be able to properly understand the outcome of the investment.

* Kennedy, R., Northhover, H. Leighton, J. Bird, G., & Lion, S. (2010). Pre-test advertising - proposing a new validity project. Copenhagen: EMAC Conference Proceedings

(Source1: Silvia Dalvit and Jane Leighton, Admap, februari 2011, pp. 12-14)
(Source2: Robert Bain, "A change of mind", www.research-live.com, april 2011)

Next level of human evolution

Meet the scientific prophets who claim we are on the verge of a next level of human evolution.

It's predicted that by 2029 computer intelligence will equal the power of the human brain. Some believe this will revolutionise humanity - we will be able to download our minds to computers extending our lives indefinitely. Others fear this will lead to oblivion by giving rise to destructive ultra intelligent machines.

One thing they all agree on is that the coming of this moment - and whatever it brings - is inevitable.

Can neuroscience offer more certainty that your advertising pushes the right buttons?

The ability to predict consumer behaviour using neuroscience techniques is much greater than that shown by self-report methods. Neuro research may be useful to test the likely effectiveness of a campaign. But there are caveats.

Neuroscience offers very powerful methodologies, but it cannot answer all advertisers’ questions with any single method. Insight into neuroscience techniques is necessary to make good research investment choices and to be able to properly understand the outcome of the investment. It is worth the effort as neuroscience technologies offer marketers tools for designing effective campaigns and predicting success.

(source: Silvia Dalvit and Jane Leighton, Admap, February 2011, pp. 12-14)

Since October 2010, Sanoma Media Netherlands is using neuroscience techniques to gather - next level - consumer insights (media consumption, effectivity of campaigns, consumer oriëntation- and purchase-proces). More of our 'Mediabrain' project in this video (in Dutch):

"The conscious mind seeks answers to why, the unconscious mind knows why."