@T: ALWAYS THE TWAIN

Well I’ve spent the last few days wrapping up London to-do’s before I fly to the US. I met with Martin Bloom who’s involved with the Innovation Warehouse, completed some paperwork and bought items that I need for the US which aren’t available there.

I have to admit that I’m really looking forward to this next phase in my career. The mentors and investors I’ll have access to in the US are more suitable for the corporate objectives of my venture. It wasn’t a straightforward decision to  physically leave  the UK in search of mentors, investors and talent; I spent time investigating the startup ecosystem and gauging my chances of success if I stayed put.

However, maybe the mark of an entrepreneur is to go and seek out  smarter opportunities rather than accept any stagnant status quo.

US technology companies must surely be global leaders for good reasons and I’m lucky enough to be about to be educated by some of  the people who have created these companies.

Let me share this: when I’m in NYC and Boston I’m planning to go to Columbia and MIT campuses. The former, in particular, for a good reason…….

At the weekend I caught up with some reading and happened  upon this ’FT’ article in which Joseph Stiglitz, the 2001 Nobel Prize Winner for Economics, wrote about the need for a new economic paradigm:

* http://www.ft.com/cms/s/0/d5108f90-abc2-11df-9f02-00144feabdc0.html

The sentences which struck a chord were these:

Many (economists) used “representative agent models” – all individuals were assumed to be identical, and this meant there could be no meaningful financial markets (who would be lending money to whom?). Information asymmetries, the cornerstone of modern economics, also had no place: they could arise only if individuals suffered from acute schizophrenia, an assumption incompatible with another of the favoured assumptions, full rationality.

I’ve presented the case several times on this blog that we need a radical overhaul of the mathematics underpinning economic models and computational code for a myriad of reasons, including the fact that QUALITATIVE ELEMENTS are not carried into the calculations of demand, supply, interest rates, search context etc. Those are predominantly quantitative metrics (“full rationality”) which provide us with limited insights into the underlying motivations and intent of consumption as well as why we go in search of content (perceptions, emotions, values, mood modalities, intelligence orientation and more).

At the same time, it’s emergent in the tech sector that ASYMMETRIC revenue models — in which we allow the tailoring of products and services by the individual rather than to the homogeneity — works more effectively than symmetric models.

In the case of what I’m focussing on, well…….a picture says 1000 words, so……

I’ve also defined previously my concept of “autistic  algorithms” with its over-emphasis on logic and absence of emotion, ambiguity or cultural context capture, and this symmetry versus asymmetry approach in economic modeling also is a variation on this autism.

It’s important because, aware as I am about Ray Kurzweil’s proposals to re-engineer the human brain to create an AI version that somehow exponentially becomes self-aware and accelerates towards a Singularity……….Last week I wrote this:

Often I think that if Turing was alive today he’d have revised his criteria for machine intelligence in the light of these developments:

•            Neuroscience as a scientific discipline became established in the 1960s after his passing in 1954.

•            Following Alfred Binet’s tests for children’s intelligence in 1904 there have been a whole series of psychometric and IQ tests (including Myers-Briggs 1962, Bebin 1981, Baron-Cohen 1985 and more) that redefine what we consider to be “intelligence”.

The limitations of IQ tests have also been documented, including: cultural bias, left hemisphere weighting and sensory exclusion. Sensory exclusion meaning that most IQ tests are based on our ability to read and visualize the problem rather than to hear, touch, taste or smell it.

So, for example, is there intelligence in Nigella Lawson being able to smell variations in chocolate depths and notes or intelligence in Roger Federer being able to hear and “touch” the weight of a ball on his racket and determine how much topspin is needed?

Notably, neither of these skills is tested in IQ tests and yet both people are intelligent.

•            The invention of MRI scans in 1977 transformed how much we can see into the brain. Plus the advancement of nuclear medicine in the 1970s, which enabled most organs of the body to be visualized.

(NB: visualizing it is not directly equivalent to experiencing and walking in every step of its myriad of interactions.)

All of these advances have changed and are changing how much we know about the human brain and about the nature of intelligence — knowhow not available to Turing in his time.

If he was alive I don’t doubt he’d propose that instead of Babbage’s difference engine (which itself forms the basis of the Enigma machine), we should be examining ways to develop coherent differentiation systems in the first instance and use these as a basis of then building out context and eventually artificial consciousness — again the distinction should be kept between organic human consciousness and silicon machine consciousness.

Just because we attribute (rather than impart) “human characteristics and personalities to complex but inanimate objects like our cars and computers” does not mean they are alive. They’re not oxygen, water and sunlight dependent for their existence and growth so even by this most basic of definitions of Life………….they cannot be alive.

These inanimate objects are a reflection of our intelligence rather than intelligent in their own right; the machines depend on us humans to reproduce and to adapt their shape, materials, personalities — “A customer can paint a car in any color he wants it as long as it’s black” as Henry Ford said and we’re all aware that human marketing is responsible for giving objects like the iPad identities and characteristics rather than the object being able to self-generate these.

Consider also the issue of injuries and viruses. Organic matter which is alive strives to stay alive and regenerates tissues and chemicals that can help that organic matter to ward off or deal with that injury or virus. An inanimate object that gets broken or catches a virus stays in that state and is dependent on human intervention, repair and troubleshooting. That’s another obvious distinction between what constitutes something being alive and something being an attribution by something that’s alive.

Now it would take too long to dissect Turing’s Test in detail and there are people more intelligent who can share their attempts to pass the Turing test with their machines:

* http://blogs.discovermagazine.com/sciencenotfiction/2010/06/28/watson-fails-the-turing-test-but-just-might-pass-the-jeopardy-test/

•            http://www.computerweekly.com/Articles/2008/10/15/232669/Meet-Elbot-Loebner-Prize-Turing-Test-contest-winner-transcript-and.htm

•            http://www.a-i.com/show_tree.asp?id=67&level=3&root=1

What is important, though, is to be reminded of the specific premise and parameters of Turing’s paper on ‘Can Machines Think?’

At its core it’s about a machine MIMICKING a human purely according to text-based inputs.

It isn’t about a machine being able to interact as a human at all.

For example, the Turing test doesn’t require a machine to do face recognition to determine whether we’re smiling or showing any other emotion and the extent of authenticity of that emotion from our body language and pupil dilation. It isn’t about the machine being able to smell our hormones to determine other emotions (fear, desire, anger etc.) either. Nor is it about a machine that can hear the emotion in the timbre of our voices or that can reach out and touch our smile / tears out of sympathy or empathy.

Importantly, it isn’t a test for Consciousness as such. It’s a test to see if a machine can copy our pattern of text-based conversations (understanding and extracting the context, humor, emotion etc. from the text).

There’s simply so much more complexity needed for a true test for Consciousness and we haven’t even definitively answered what that is for the human brain yet…………….

So…………… to the books, the drawing boards, the brain imaging scanners, the Web and the code kitchens for all of us!

And  this:

There’s an obvious variation between my approach and what Kurzweil propounds about the Singularity. I start from the basis that humans are more intelligent and complex than machines; also that the heritages of our DNA as well as our moral conditioning affects our socio-economic-philosophical psychology and human contracts.

Meanwhile, Kurzweil seems to want us to revert our brains to mere matter (information) that can be transmitted digitally in the same way that information was via the Reading Machine he invented.

Kurzweil believes the code answers to the artificial brain lie in genome. Interestingly, Craig Venter the man who successfully sequenced the human genome and is involved in all types of experiments involving it ranging from biofuels to software gave this interview to Der Spiegel in July 2010:

* http://www.spiegel.de/international/world/0,1518,709174,00.html

And this:

If readers will (and I have no intention to start a “battle of the sexes” scenario), we could potentially reverse engineer the left “male” hemisphere of the human brain. The right hemisphere which is concerned with language, intuition, free association, consequentiality and more may prove to be more of a challenge.

Now………Even if we did manage to reverse engineer both sides of the brain this still doesn’t necessarily mean the machine would be as intelligent or capable of sense-making as us. This is before we’ve even factored in the fact that intelligence varies in the human population and so this variance would be replicated in whichever reverse engineered artificial brain we built. It would have the intelligence of its human creators and that intelligence would be limited by their intelligence (reference points, linguistic abilities, perceptions and modalities of thinking etc.)

Moreover, we would still encounter the crux of consciousness that separates Man from machine: the biochemistry of emotions that informs our values, our beliefs, our morals, our humanity, our empathy and consideration for others and for Society.

Ergo the core issues in economic models and also Web code are the same: it’s not only the quant logic functions that count (the binary 1′s and 0′s and probability %), it’s the qualitative asymmetric dynamics that also contribute to VALUE and will enable us to map the context, consequentiality and coherency of more of our models (be they resource allocation, conscious consumption or risk management) .

Anyway, maybe I’ll manage to visit Professor Stiglitz at Columbia…….

Oh and, at the w/e, I found out that a PARC team (Palo Alto Research Center which is where Alan Kay worked for 10 years) has started to follow me on a social media site. This is interesting since I used a pseudonym and alternate email which is not associated with any of my public profiles and I didn’t post any materials about Semantic tech there.

Yet this PARC team decided to follow me. Maybe it’s the Yin Yang  logo that caught their eyes, :*).

Mamma Mia and I decided to hang out in the Saatchi gallery on Saturday and these are some of the works we admired:

The painting that looks like aluminum foil scrunched up is a very clever way of showing what perspective, contours and line illuminations can do and it stands out from the usual “let’s paint some glasses and their reflections” so I think this is one of  my favorite contemporary paintings. The Cher-Che Guevara screenprint by Scott King has notes of Andy Warhol so, whilst it’s striking, is not an entirely innovative form of art and therefore not as good as William Daniel’s tin foil alludes.

After the Saatchi gallery I made my way to a friend’s 30th birthday party where we “signed in” by creating a portrait of  ourselves with colored paper, pens, gluestick, glitter symbols and other paraphernalia we loved @school:

Naturally, I took my inspiration from Sigrid Holmwood’s fluorescent egg tempera pieces that were exhibiting at the Saatchi gallery. No prizes for guessing which portrait was mine!

Yups, the one with rose-tinted eyes (ok there was no blush only hot fluorescent pink paper), the blue mouth (an ironic statement because I rarely swear and write with asterisks when dealing with expletives like s***) and the bouncy curls (actually my hair is Oriental black and…..straight).

Ah and I’d like to make an observation about my generation and manners. On my way to the party I dropped by  Chinatown to pick up some food for the party (delicious heavy noodles, chili sauce, Tom Yum peanuts, a bottle  of Sake and more). I was also laden down with my bag of birthday presents and other  items so ……,on the bus, I was more than happy to find an empty seat.

Now there were several people the same age as me who were not over-flowing with bags (in fact they had none) and they were sitting close to the doors (the seats typically allocated to those less able to stand). A super-glamorous elderly lady of about 60 boarded the bus. Not a single one of those people the same age as me stood up to offer her a seat (!) — despite it being obvious by the way she grasped the railings that she was unsteady on her feet in a moving vehicle.

Of course I stood up and let her have my seat. Then I lugged my bags over to a corner and did the best I could with balancing those and standing upright in a moving vehicle — LOL.

This was A-OK. Afterwards, as she got off the bus, she made a special effort to come over to thank me which was really cool and I hope I’m that glamorous and soignée in decades to come…….

So it was a GR8 Saturday!

This September I’m going to the US to progress my startup. Originally I had hoped to stay in the UK, collaborate with others interested and involved with the semantic and context space and to attract UK investors but when I did a deeper SWOT analysis (strength, weaknesses, opportunities and threats) of the UK ecosystem — from business support to audience adoption potential to investor financing — I finally accepted that the chances of TWAIN IT being nurtured and becoming a success in the US are higher.

Without going into too much detail about the trials, tribulations and challenges facing UK startups, the contrast between US and UK’s approaches to cutting edge technology and entrepreneurs may be best illustrated by these articles:

• http://www.mobileindustryreview.com/2010/03/the_us_startup_visa_a_boon_for_dismayed_frustrated_british_entrepreneurs.html

• http://www.freddestin.com/blog/2010/03/a-cry-for-europe.html

• http://news.cnet.com/8301-30685_3-20010832-264.html

• http://www.bbc.co.uk/news/10152929

• http://www.bbc.co.uk/blogs/thereporters/rorycellanjones/2010/07/uk_tech_is_anyone_listening.html

• http://paidcontent.co.uk/article/419-atlas-venture-reorg-moves-european-investing-to-boston/

• http://blogs.ft.com/techblog/2010/01/atlas-ventures-pulls-back-from-london/

When one of the larger VCs like Atlas Ventures decides to move its European operations to………BOSTON — as a reflection of how tough it is for  European VCs to raise money from Institutional Limited Partners to back them — then it’s obvious that the UK ecosystem for financing isn’t making the progress out of infancy to adulthood in quite the same way as the US did.

Unfortunately, the situation is what it is. As entrepreneurs we can choose to  go with this flow or we can go find another flow more conducive to getting us where we need to be.

At some point I owned a Microsoft Natural Ergonomic Keyboard which — whilst curvy and with a large “fringe” on which to rest my wrists and prevent RSI — also took up about 30cm by 50cm of my desk space.

Now I  use this:

Yes, if 4 of my business cards are laid vertically they cover the entire machine!

It’s  just as well I have slender finger tips because if they were bulbous I’d be constantly mistyping!

At some point in the future we may not even need  physical input devices. Our very thoughts will be somehow  captured and transmitted over the airways and appear as text, graphics, videos etc on a surface somewhere.

So the universal truth about startup life is that it’s often chaotic and if the founder(s) aren’t dynamic, adaptable and super-skilled (or at least have access to talented people who can compensate for their skills gaps) then the chaos consumes the startup and sinks it……….:*(.

Vision, passion and chutzpah are advantages but even more of a plus is when the founder(s) have strong execution skills to back up those qualities in a coherent way.

In today’s post, I’d like to share how resource and talent constraints need not necessarily result in disasters. Quite often what happens when entrepreneurs get a semi-good idea is that they throw cash at designers and developers to design them a snazzy website and, in the process, they unfortunately forget that this should be tethered with business model and revenue objectives as well as a UI that’s comprehensible and easy to use.

It would actually be better for those founders not to waste capital in this way but to focus on the product, its user base and its business model.

One Semantic play in particular (alas for them no more because they burned through US$20+ million of cash but didn’t understand their core user proposition and couldn’t deliver on system’s improvements) was a cursory lesson in……….

SMART = SIMPLE SOLUTIONS NOT SPIN.

Superficially, their UI was “rich” with lots of content and a multitude of features. However since their semantic algorithms were unable to provide CONTEXT that content was actually static and compounded the non-performance of the platform. Compare this with Google with its single search bar or the way iPad works and it becomes obvious that navigating the clever complex algorithms don’t need to be on the consumer’s consciousness.

One Touch. One Click. One Icon / Info Bar is about what most people can handle and it’s how they prefer to handle info and technology.

Unfortunately, another universal truth is that once a platform has been coded it’s more expensive to go back and start again and it would seriously disrupt the service for users.

This incoherent approach to strategic implementation also arises because technical founders are rarely versed in business knowhow whilst business founders rarely have the tech knowhow and when they do partner up, they invariably find themselves communicating at cross purposes. At later stages of the startup this is what causes “management and strategic differences” that can contribute to the company being less successful than if the principals involved are on similar and complementary planes of perspectives.

Add excessive “spin” to the mix and the primary objectives (SOLVE USERS’ NEEDS, MAKE A PRODUCT THAT’S STRAIGHTFORWARD AND COMPANY-USER SYMBIOSIS IN MONETIZATION) get lost in the wash which means no one wins and leaps of tech advancement are not realized.

So amidst the chaos of startup life, what’s a sensible approach?

Well………….wherever possible………….SCHEMATIZE THE USER FLOWS BEFORE THE SYSTEM IS CODED.

For exampple, here’s what happens when we cross Michael Porter’s 4P principles of business modeling with the tech knowhow of wireframing a simple, clean UI:

This focuses management to remember the audience they’re servicing as well as what value utility those users are receiving from the platform (that some of them may be prepared to pay for).

Eagle-eyed readers will instantaneously recognize that this 8-pod molecule is the same structure I deploy on  @T’s homepage :

It is also the basis of my data consciousness model:

What does this show? Well, in problem-solving when we can visualize a structure and its components that can help us unlock the problem we have to apply some creative adaptability. The components can seem unrelated, random and even confusing. Yet by anchoring it around a central core and then attaching each of the 8 pods into a sequence (a DNA) it becomes part of a coherent whole. The same is as true in business models as in UI design.

In this way, instead of “wrestling the octopus” we have a clear understanding of what our central goal is: (data) consciousness whilst keeping in sight its constituents.

An experienced developer I recently met made the observation that I’m able to “see the Big Picture and also loop the details back in an agile way, which is rare. It’s a good quality to have in product development.” By comparison to him and many others, I’m a novice so I take his comments as a compliment.

Well my UK iPhone contract ends in September and, coincidentally, I’m going to the States so I was pondering whether I should get a Pay+Go or new US mobile contract — that is until I found a number of options to make calls on my iPad instead.

The sound quality is just as good; the iPad mic does a reasonable job of picking up what we say. Obviously it looks silly to have an iPad next to your ears, so the way to do it is talk via a bluetooth headset.

It’s going to be strange to know that as of September this will be the first time I haven’t got a mobile phone in…….over a dozen years — WOW. Still at least I won’t be paying twice to get online (iPhone and iPad).

I’ve also discovered another handful of business applications which are “must-installs”, mostly related to translations and I’ve also downloaded a couple of iBooks on Objective-C which is the programming language/compiling methodology that most iPad applications are built with.

What makes these iBooks different is that…….they’re written in………French. For some strange reason, there are no English iBooks on Objective-C so maybe we can assume that within the next few years French-speaker technologists will monopolize the iPad applications market because they have the natural first mover advantage of the iBooks on Obj-C being written in their language!

It’s just as well I have a DFAII (apparently the highest level of business proficiency in French possible outside of France and Quebec) and can navigate technical French terms like this:

Smalltalk-80 est un des tout premiers langages réellement objet, qui a donc fortement influencé les développements ultérieurs de ce concept. Le C++ et l’Objective-C sont deux branches différentes visant à créer un langage objet basé sur le C. Tandis que C++ se tourne vers une forme de programmation très statistique minimisant le <> du modèle objet pour les performances d’exécution, Objective-C choisit la voie du dynamisme de Smalltalk, dont il emprunte aussi une partie de la syntax.

[Actually, there are excellent series on Obj-C++ from some of the top US universities and the Chinese have created an Institute of Internet Things so there are several resources available.]

I want also to comment on Smalltalk. For several years now I’ve had an instinct (a Twain intuition?) that I somehow need to strand semantic algorithms with Smalltalk and my own originations of code approach and maybe some Quantum Mechanics notation and we will arrive at……………….

A CONSCIOUS WEB. You all read it here first, :*).

As readers are aware, I’m building a DIFFERENTIATION / CONTEXT ENGINE. Now whenever anyone originates anything it’s always advisable to check what competitors (or those providing broadly similar services) are doing. Then we can populate interesting competitive landscapes like this one I did on Chinese banks back in 2005:

Naturally, I’ve already put together a nice Porter-esque quadrant of the key players in the “smart ratings and recommendations” space and this appears in my business plan (which is available only under NDA).

Anyway, it may be interesting to gain some insights specifically into Hunch, whose Chief Product Officer happens to be Caterina Fake of flickr fame and which was publicly launched in June 2009 after a private preview period that started in Dec 2008, reached 1.2 million users by Feb 2010  and raised US$12 million in Series B financing in March 2010. At the time of writing there seem to be 12 people on the team. Notably, most of the engineers are MIT graduates and its board members include Gideon Yu (former CFO of Facebook) and Jimmy Wales (founder of Wikipedia).

Ok so this is the team I’ll be competing against when my wee tools finally launch — what  odds, LOL!

Now here’s what happened when I road-tested Hunch today — initially optimistic that MIT engineering graduates would have all the answers to everything, that the UI would be slick and AJAX-y (which it is, btw) and that it would be able to “capture my taste graph” and “personalize the Internet” experience for me.

There’s even a phrase on the site which claims :

(This all sounds like the type of phrase tarot card readers and astrology gurus deploy all the time, btw. Plus Hunch obviously needs an editor / copywriter to spellcheck their copy because it should be “astouNding”.)

The first question I didn’t screen-capture but it was simply about whether I lived in the suburbs / city / countryside and I’ve seen multiple choice questions like these before from Chris Hughes (former co-founder of Facebook, organizing guru at mybarackobama.com and now of Jumo).

Here are 5 of Hunch’s 20 questions along with my highlighted answers to give readers a flavor of the types of questions Hunch uses to train its prediction engine and generate its taste graph:

See the “61% of respondents chose the same answer”? That corresponds to the question about whether I can do 10 pull-ups and the 61% gives a good indication that around 2/3rds of Hunch users answering the 20 questions are probably male — since we women don’t do pull-ups because we don’t want to bulk up our shoulders, upper arms or rear backs. We do crunches, aerobics and yoga to strengthen our abdomen and increase our flexibility.

The result of 33% being spooned is interesting because it seems to confirm that 1/3 of Hunch’s respondents to this 20-q survey are women (which is consistent with the question on pull-ups).

After the 20 questions, Hunch produced this screen:

‘Great,’ I thought, ‘So now Hunch must know what psychometric profile I am — maybe like in an MBTI / Belbin / Baron-Cohen way!”

Alas, it was not to be because this is the page which popped up after I’d clicked on ’10 Predictions Hunch makes about you……’

A-ha……….so Hunch isn’t that intelligent and reverts to binomial Yes / No (+1/-1) in its decision-making architecture.

It’s also offered a nonsensical question about the bathroom signs at the Science Fiction Museum which, in fact, we can’t answer “Yes” or “No” to because what the Hunch system should offer are three buttons to specify gender “Male”, “Androgyne / Android” and “Female”.

Well, for the sake of completing the road-test and humoring the process I went through to either confirm or deny (yes / no) each of the ten statements. For some statements where I contradicted Hunch’s predictions, this then produced another link ‘Answer this question’ which led to another page of a multiple choice question.

(In seriousness, what happened to one-click intelligence? How many people would lose interest in training the engine after the first 10 clicks — never mind another 5+ pages to correct the engine’s prediction mistakes?)

Interestingly, wrt the question of “Do you fold your underwear”, Hunch made the prediction of “No”. Given the choice between the “yes / no” buttons I clicked on “no” to negate their “No” prediction. The mathematicians amongst readers will know that -1 – (-1) = 0 and the English grammar aficionados know that a double negative creates a……neutral statement.

So it’s curious that Hunch interpreted my click as me agreeing with their “No” prediction. In fact, I do fold my underwear because it looks neater in the drawers.

Anyway, the end result of my click contributions to training Hunch’s engine so that it would product my personalized taste graph……….This is what Hunch’s engine, built by super-smart MIT graduates, elicited:

Hmmmn and LOL. Readers will remember what happened when I road-tested one simple question on Elbot:

The engineers work hard and take years to perfect their intelligent systems, run them through extensive beta testing etc. Then I appear with a few simple clicks and they…………..CRASH.

Smart algorithms obviously don’t like me testing them out — LOL.

Administration is a key skill I’ve been thinking about in recent days because a contact sent me their business plan to sanity check prior to their fundraising exercise. Their documents just reminded me how much paperwork goes into creating a startup — behind the scenes, the elevator pitches and the slick UIs. There’s the written business case, the tech documentation for the build, all the financials, all the legal filings for trademarks and patents (as applicable), all the contracts of employment plus service licensing agreements plus shareholder agreements and user agreements, all the marketing and press literature and another stack of paper dedicated to everyday operational communiques.

It’s not quite as extensive as one of the “deal bibles” that used to be delivered to my office  — one M&A took up 15 boxes of literature and one colleague went into an entire vault of information during the firesale of Enron’s assets and we were deciding which assets were worth buying on the cheap — but even a startup has a lot of admin to contend with.

Now I always love to check out other people’s business plans for 3 reasons:

(1.) I can often help them re-engineer it to increase the likelihood of attracting appropriate investors;

(2.) It’s always informative to experience how others approach their business models; and

(3.) Taking yourself out of your own area of focus and expertise is always healthy for intellectual development; it provides reference points for me to access later in any multi-disiplinary cross-pollinations I may do in problem-solving.

Anyway, the administration aspect also makes me think about………ACCOUNTING and how inappropriate assumptions during the modeling process can put the strategy off course whilst on-the-spot assumptions can shortcut a startup towards success. The best thing a startup can do is to proxy model themselves against either a direct competitor or a company providing broadly similar services — rather than carve out a cashflow model and balance sheet from scratch.

Recently I heard several UK startups claim that, “The numbers don’t matter, we can just make them up. That’s what everyone else does. The investors don’t care, they’re just taking a punt on the team.”

Hmmn………and this may be one of the reasons the startup sector in the UK is less developed than in the US where they do, at least, try to crunch some numbers about potential market size from credible industry sources (IDC, McKinsey, Gartner, Datamonitor et al).

Just as another observation: the startups which have typically failed have been the ones which “made up the numbers” (whether that’s in # of users, how long they engage with the site per visit, how sticky they are after X months etc.) to try and persuade investors to keep pumping money into them.

Sooner rather than later it becomes obvious that these “made up numbers” are unsustainable and actually ERODE the value of the investment.

Anyway, in the interests of avoiding such pitfalls I’m using a number of financial modeling tools to sanity-check my own projections (the example below is a dummy version — the real version is available only under NDA):

It’s also not the case that someone with an MBA, ACCA or chartered status always produces a spot-on financial model. Again this may arise from lack of access to assumptions data and this deficiency then feeds into the model as a whole. It’s something to be aware of — if not avoided as much as possible.

As for the imagination, innovation, ingenuity, leadership and execution traits needed in a startup founder, those are probably more of a natural state than administration skills.

Yet it’s probably the attention to detail during admin (e.g. checking through invoices and ensuring its compliance with the original financial plan) which makes the startup a success and how much of a success, long-term.

This post is for the super-smart AI specialists I’ve recently befriended, prompted by Barry Robson (CEO of Dirac Foundation; Strategic Advisor at IBM TJ Watson Research Center; and more) sending us all the link to the ‘Principles Versus Patterns’ paper by Carlo Pescio which highlights how the Feigenbaum Bottleneck affects our ability to collectively find solutions. This blog post is also related to Rob’s pointers on cross products and he’ll probably LOL when he sees what’s been distilling and mapping in my mind, byte size by byte size over 5+ years. Hopefully, Paul will also LOL when I offer my answer to the “Nature or Nurture?” question and special thanks to Pedro for reminding us of the power of language as re-imagined across cultures. Some of the best brains in the world and they’re generous in allowing me to add to the mix with my relative inexperience and ignorance.

It’s only in 2010 that I’ve allocated any time to the maths and technicalities behind my thinking; before I liked it being in conceptual free form that (like a magpie) I’d collect the super-shiny scintillating strands and commit to twaining together when the timing was better and when I met fellow protagonists who could and would enlighten me.

Now the Feigenbaum Bottleneck states: as domain complexity grows, it becomes more difficult for human experts to formulate their knowledge as practical strategies (as human “say-how”). It is easier to demonstrate by doing (“show-how”) and most people can also make good choices between alternatives (“say-what”).

Admittedly, this is the first time I’ve happened upon the Feigenbaum Bottleneck; this is what happens when a person doesn’t do a PhD in maths / computing and doesn’t have the opportunity of exposure to it during the course of their career………….until now that they happen upon exceptional thinkers.

Well, naturally,  all this “show-explain” categorization referenced by Feigenbaum made me immediately think of first principles in film-making — whether we’re the scriptwriter, the producer, the director, the SFX supervisor, the makeup, the actor etc……………”SHOW + TELL”.

At this point, it may be worthwhile to provide context for Barry and other new friends. There is a running joke amongst friends of mine who’ve known me for a few years longer. There’s something called “SHOW + TWAIN“. This is my habit and practice of trying to make sense of multiple elements into some sort of coherent whole and putting that into pictographic form that’s actionable.

The pictographic habits are probably explained by my Chinese heritage and the fact that in the segments of visual spatial reasoning for IQ tests I do unusually well — for a female and we’re not supposed to be good map readers either :*).

Anyway, I do “show + twain” almost all the time. I can write reams of text and prose but I much prefer pictographic representations.

As a reference example, one of my closest friends met me randomly and serendipitously on a flight almost a decade ago. He’s a well-established figure in the hedge fund industry and he assumed that I was a Bohemian art student for the simple reason that I was doodling in my notebook — albeit it was like a project management version of all the Severinis, Dalis, Max Ernsts, modernism etc. that I’d just seen inside the Guggenheim Venezia, Accademia and Biennale.

So across 2 pages I’d creatively mapped out artworks into a differentiated perspective that made sense to me.

Partially, this habit arose because when I was 5 my father taught us how to play chess and years before my mother taught us how to play card games as a way to encourage us to count and do mental arithmetic. Therefore, as a kid I had to make sense of complex scenarios: board, pieces / 52 cards, rules of game, patterns, risks, strategies, trade-offs, seemingly random moves by the other competitor, reading human emotion (not necessarily via face), sportsmanship etc.

I developed these skills not via “say-how” text form (no chess books for child Twain) but by a cross-pollination of pictorial memory capture with context tagging and random referencing to other sports (basketball, hockey, netball) and other topics (e.g., watch a crowd crossing at a crossroads when the lights are still green, the cars are still go and……… navigation strategies and purpose emerge). The most efficient, safe route to the other side of the street is an analogy for pawn to Queen conversion, by the way.

“Say-how” to me is what happens before we set-up a chemistry or physics experiment: we list the apparatus and the instructions we’re going to follow but we have no idea of whether the results will concord with our planning because there are risks of random impurities affecting our experiment. In some cases, like in crystallization, these “random impurities” are actively encouraged / seeded. In other cases, we remove all possibilities of random impurities because we’re after specific results — so by extension, we’re already precluding the experiment to fit in with our “say-how” rather than allow it to be stochastic.

As an adult these childhood habits translated into a part of my career being dedicated to…….synergizing corporate strategy and transaction negotiations — of the type where I now classify the way Facebook is differentiated from what I’m doing like so:

Rest assured the way I classify and contextualize data for purpose is not to be found in most database sources or risk management solutions (from Bloomberg to VentureOne to CapitalIQ).

Anyway, I don’t always produce structured MBA-level strategy slides because sometimes breaking the professional norms / standards / conventions allows a person to be free, to be brave, to explore, to reflect, to appreciate the conflagration of other influences, to contextualize, and essentially  to……………innovate.

So here’s some of that free form thinking and “show + twain”:

So within my lifetime I hope to help realize…….The Conscious Web of We (CWOW).