Monday, December 3. 2012
Further to our earlier post on the incipient unwinding of the UK consumer tech startup scene, it doesn't help that any that do survive will cost significantly more to run than the indstry heavyweights they compete with.
Google's tax rate in the UK is between 2.5% and 0.25% of revenues, depending on whether they make £4m or $4bn out of the UK - Pc Pro.
Google bills all online advertising via its European head office in Ireland, and at the hearing, Google's vice president of operations for Northern Europe, Matt Brittin, said his firm uses tax havens including Bermuda to increase shareholder value, but said the company obeyed the letter of the law. Last year, it posted £395m in revenue and paid £6m in UK taxes; however, a US SEC filing showed it made sales attributable to UK addresses of $4bn (£2.5bn).
Amazon is similar - As PC Pro previously revealed, Amazon.co.uk is considered a "fulfilment" company for the European branch of Amazon, which is based in Luxembourg, and paid £1.8m in tax last year. However, the evidence submitted to the PAC showed £3.35bn in sales were from the UK - 25% of Amazon's sales outside of the US. If all the tax was on UK only revenue that's a maximum of 0.05% (and more like 0.0013% if only 25% of tax paid is from thre UK)
You either have to believe these businesses perform far, far worse than their corporate average, or you have to believe that their tax revenues are underpaid.
Now, compare this with the tax that any UK technology company pays in the UK, which, for a small limited company is 20% on the first £300k and ratchets up to 23% at £ 1.5m. What this in essence means is that any UK tech startup starts the game with both hands tied behind its back vs the major players.
Now, let us make a heroic assumption that a viable startup's taxable income is similar - as a % of sales - to Amazon or Google (in fact it's probably worse). This implies that the UK startup is spending between 10x and 1000x more on it's tax bills per £ earned. This is an "order of maginitude" rather than an exact figure, but it makes the point - the risk of a startup is far higher than that of a major corporate, but the rewards are structurally far less.
This is also an a**e-to-face reward structure, and certainly not the way to give the UK's technology entrepreneurs a boost, especially if you are hoping they will lift the UK out of a depressing recession.....one could (and in my view should) make a case for near zero tax for startups until the position is equalised
A mere week after we noted the Silicon Valley sturm and drang about the decline of Consumer VC funding, following the popping of the Social Media bubble, there is now a sturm and drang around the impact of the cash drain on the booming "startup production industry" as we called it in 2008 (the seed funding competitions, newly minted angels, incubators, optimistic lecture circuitry etc etc), probably started by Y Combinator's discombobulation this weekend just past. Now there is much more handwringing in the blogosphere as it becomes clear the oxygen of cash is receding.
To say this is totally predictable is putting it mildly, heck, we predicted it months ago - but it seems that time after time greed trumps sense. Anyway, a good summary of the basic dynamics acting in the tech startup funding space is well put by Chris Dixon:
Startups sit in the middle of two markets: one between VCs and startups, and one between startups and customers. These markets are correlated but only partially. When the financing supply is low but customer demand is high, entrepreneurs that are able to finagle funding generally do well. When financing and startup supply is high, customers do well, some startups do well, and VCs generally don’t. And so on.
What this means is well satirized by The Kernel, as it allows a lot of vested interests to invest in it:
This creates a wall of hype that suck(er)s in aspirant startup CEOs....
Now consider that glut of start-ups in east London, aided and abetted by that noisy, hyperactive, undoubtedly well-meaning but ultimately insignificant Government department anxious to locate simple, measurable metrics of success – like the number of companies founded, or people employed.
Indeed, when newly minted Angels are stampeding over the Fools and Friends in a rush to the startup pot, you know its time to run far, far way. Sadly for all the startups out there, the "startup production industry" is a lagging indicator of a bubble deflating, i.e. by the time their clay feet are showing the cash tide has long gone out.
Wednesday, November 28. 2012
When Randy Adams, 60, was looking for a chief-executive officer job in Silicon Valley last year, he got turned down from position after position that he thought he was going to nail — only to see much younger, less-experienced men win out.
Forty is definitely not the new 30 in Tech, it would seem:
"I don't think in the outside world, outside tech, anyone in their 40s would think age discrimination was happening to them," says Cliff Palefsky, a San Francisco employment attorney who has fielded age-discrimination inquiries from people in their early 40s. But they feel it in the Bay Area, he said, and it's "100 percent due to the new, young, tech start-up mindset."
They go on to point out that there are some benefits of youth, but it is possibly being over-emphasized now:
My own experience and those of other "wrong-side-of-40's" in the industry I know (bearing in mind anecdote is not the plural of data of course) is that no, we are not as up on the intricacies of the latest cool language, but our experience also shows us that the big drivers of success are seldom to do with the tech itself, nor working long and hard instead of smart. It's about managing risk, enthusing people, controlling cash, ensuring delivery quality, attracting customers, managing expectations - and while experience doesn't guarantee success in this, it does increase it's probability, as it's a learning curve thing. Which is why, when the going gets tough, Boards start to want a "grown up in charge" (Google, Facebook...and now Groupon it would seem). Horses for courses, as they say....
And, if I was being exceedingly cynical, I would suspect that some of the preference for youthful startups is their naivete, allowing funders to strike deals that no-one who has been around the block would ever accept.
Wednesday, September 5. 2012
Interesting piece in the WSJ about an Urban Drfit for technology companies:
I recall at the height of the dotcom boom, you couldn't move in San Fran without tripping over a a Blazer'd and Chino'd dotcommer, but Silicon Alley was still mainly Chinatown - so is it just a new Bubbletime, or is it a real shift?
Across the Atlantic, London's once- derelict Shoreditch district—now known as Tech City or Silicon Roundabout—has been transformed into a thriving high-tech district housing 3,200 tech firms and 48,000 jobs, according to a recent report from the Centre for London.
Except that's not really true, the action is more spread out - Soho, London Bridge, and other areas all have their enclaves, but they are still mainly within the inner city Circle line, it is true. So asssuming it is a real trend, what is driving it? Part of it is avoiding the increasingly traffic-jammed commutes to beltway business parks, says Mark Suster (now in LA, but he was a London boy when I knew him), and part of it is other amenities:
I suspect there is also the shadow of underlying modern economics there, in that I am reliably informed that you can no longer afford a Mountain View house and car on startup money, so if it's to be a bijou pad and bus it may as well be somewhere with decent amenities outside.
But SV and New York and London have long had overpriced housing, so why did people go to out-of-town campuses in the first place?
The answer was cost - companies used cheaper land business park campuses to minimise their costs, while also externalising the inconvenience cost by forcing employees to bear the cost of commuting and car ownership. However, when the majority of employees own the companies (as is the case in a small startup) then that economics is turned on its head and it's far more rational to live as near the shop as you can (or even above it, or in it). Also, its an attractor. A company baesd in central London is easy to get to for a large number of people all around London. Put it out on the beltway, and its becomes inaccessible to 3 quadrants out of 4 without a bad commute. And if they have other options, you've just lost 75% of your potential staff recruiting base.
Also, it would seem the startup and market economics have changed:
I'd discount the London thing as an overall trend, London bats way above its weight in media (online and off, it always has, it houses the UK's Madison Avenue, Hollywood, News Media and the BBC plus its multiple spin outs/offs/ins/etc), just as SV does in new technology infrastructure, so I'd say that's a London cluster-specific issue. The rest of the economics of firm size, speed to market and close to consumer issues do ring true though.
The other thing about cities is that, well, they are just fun places for smart people to live in:
Cities are central to innovation and new technology. They act as giant petri dishes, where creative types and entrepreneurs rub up against each other, combining and recombining to spark new ideas, new inventions, new businesses and new industries.
Once you are tired of London (or New York, San Fran, Berlin, etc etc) you are tired of life.
(Incidentally the article is written by Richard Florida, whose major thesis is that liberal urban areas attract the most groovy, smart, creative and interesting people. As a Londoner, I have to agree . As an aside, my experience is that having a big University (or even better, a few) in the town is a huge boost to that vibe as well )
Saturday, September 1. 2012
Following on from Part (I), in my opinion this piece, "All Revenue is Not Created Equal: The Keys to the 10X Revenue Club" by Bill Gurley a few months ago sums up a lot of the main issues to think about around the business model, and some areas of customer attraction. I have abridged it below, but the full piece really is required reading.
1. Sustainable Competitive Advantage (Warren Buffet’s Moat)
2. The Presence of Network Effects
No discussion of competitive advantages and barriers to entry is complete without a nod to perhaps the strongest economic moat of all, network effects. In a system where the value to the incremental customer is a direct function of the customers already in the system, you have a powerful dynamic that tips towards winner take all. Perhaps the definitive piece on this type of advantage is Brian Arthur’s Increasing Returns and Two Worlds of Business published in HBR back in 1996 [Recommended reading, its an eye opener]. This “second world” that Brian refers to is one where the market leader has an unfair advantage that is reinforced by network effects.
3. Visibility/Predictability Are Highly Valued
4. Customer Lock-in / High Switching Costs
5. Gross Margin Levels
This may seem super-basic or even tautological but there is a huge difference between companies with high gross margins and those with lower gross margins. Using the DCF framework, you cannot generate much cash from a revenue stream that is saddled with large, variable costs. As a result, lower gross margin companies will trade a highly discounted price/revenue multiples. Amazon (20% gross margin), which is certainly among the very best retailers when it comes to execution, trades at a low 1.5x 2012 revenue estimates. Wal-Mart (25% gross margin) trades at 0.41x 2012 revenues. Best Buy (24% gross margin) trades at only 0.22x forward revenues. All things being equal, gross margin percentage should have a direct impact on price/revenue multiple, as there will obviously be more gross margin dollars to contribute to free cash flow. Journalists who quickly apply 10x multiples to all private companies should at the very least consider gross margin levels in their analysis.
6. Marginal Profitability (ie scaling)
7. Customer Concentration
In their S-1, companies are required to highlight all customers that represent over 10% of their overall revenue? Why do investors care about this? Once again, all things being equal, you would rather have a highly fragmented customer base versus a highly concentrated one. Customers that represent a large percentage of your revenue have “market power” that is likely to result in pricing, feature, or service demands over time. And because of your dependence on said customer, you are likely to be responsive to those requests, which in the long run will negatively impact discounted cash flows. You also have an obvious issue if your top 2-5 customers can organize against you. This will severely limit pricing power. The ideal situation is tons of very small customers who are essentially “price takers” in the market. Google’s AdWords program is a great example.
8. Major Partner Dependencies
Investors will discount the price/revenue valuation of any company that is heavily dependent on another partner is some way or form [Which is why we are sceptical of biusinesses based on Twitter or Facebook platforms]. A high profile example of this is Demand Media’s reliance on Google’s SEO traffic. Google isn’t the customer per se, but they can heavily impact the outcomes for Demand. And even if they don’t impact them (the recent quarter was in line with expectations), the mere awareness that they could, can have drastic impact on long-term valuation, and therefore price/revenue multiple. These dependencies are also [usually] disclosed in the S-1 under “Risk Factors.”
9. Organic Demand vs. Heavy Marketing Spend
All things being equal, a heavy reliance on marketing spend will hurt your valuation multiple. Think about this simplistic example. There are two stores in the middle of town. One has a product/service that customers love, and as a result, customers flock to the store day in and day out all on their own. These customers then tell other potential customers, and through this “word of mouth” process, the customer base grows even larger. The second storeowner advertises frequently, and all new customers are a result of this advertisement and promotion (which obviously costs $$). Which business would you prefer to own? Which one would likely have higher cash flows? If you have to “buy” or “rent” your customers, you have a non-optimal business model – plain and simple.
We saved the best for last. Nothing contributes to a higher valuation multiple like good ole’ growth. Obviously, the faster you are growing, the larger, and larger future revenues and cash flows will be, which has direct implications for a DCF. High growth also implies that a company has tapped into a powerful new market opportunity, where customer demand is seemingly insatiable. As a result, there is typically a very strong correlation between growth and valuation multiples, including the price/revenue multiple.
A really good piece, I think its realy worth reading the whole piece and pasting it on the front of any startup's business plan design file.
Friday, August 31. 2012
I was on holiday at the time so I'm a bit late onto it, but this piece in The Economist chimes a lot with my experience:
Firstly, "market research" for new technology startups is nothing like what usually works for more tradtional start up businesses:
Anyone who has tried a hand at starting a high-tech business—seeking to turn a clever research idea into something customers will pay good money for—quickly learns that everything taught in business school is next to useless. The mistake is to think of start-ups as just smaller versions of established businesses. They are nothing of the sort.
Our experience is its far more about modelling scenarios, what-ifs, probabilities etc and laying down "marker stones" to know where you are, so you can tell which scenarios are probably playing out. For this reason I was very interested that Silicon Valley Entrepreneur Steve Blank has come to similar conclusions, but with a lot more data and experience, and has set up his own accelerator - i-Corps - to do this (I know, I know re Accelerators* - but read on, there is some interesting stuff here):
What distinguishes an I-Corps start-up from a typical university spin-out is the way it forces researchers to stop fixating on the technology they have developed. New ventures, they are taught, are all about finding customers, what distribution channels to adopt, how to price the product, who to partner with, and more. From day one, the mantra is “get out of the lab”. Participating academics have to make countless cold calls to potential customers—something few research scientists and engineers have ever done in their professional lives and most initially find awkward.
Stopping Technology Fixation is IMO one of the absolutely critical issues for Technology startups, the problem is its virtually impossible for techies who are in love with their technology to do - so the second bit, on treating the startup dispassionately as a live project, seems like a very clever way of forcing that dissociation. Anyone who has studied innovation and startups will know that which technology/company/method succeeds is highly unpredictable in the initial stages, and all sorts of factors come into play - exactly because all sorts of factors are untested.
But I was also impressed with the following, because in my experience turning around tech companies, these are usually the most critical issues - making sales and making profits:
There are other methodologies than those suggested here of course, but in my experience the "80/20" impact is the act of focussing on the business model (how you will make money) and the customer model (who will buy). Its damned hard to do, especially for the techies who are struggling with making the new wotsits work, but absolutely critical. You don't have to have the "right" business model initially (just look at Google) but you have to know what a "wrong" one looks like, and what the envelope of success looks like.
Also, they emphasise that there will be significant twists and turns in the business (or "pivots", as the fashion is to call it these days), its a given not a failure
The I-Corps curriculum emphasises that failures which force participants to pivot and change their assumptions are an integral part of the learning process. That can mean rethinking the market, changing the price, even altering the product itself. During the eight-week programme, I-Corps teams repaint their business-model canvases literally dozens of times. The average team confronts 100 or more potential customers while honing its business plan and tweaking its product.
Re: pivoting, I increasingly think of a startup as a bit like a new genetic algorithm, so it has to go through a number of self winnowing cycles before it can navigate the ecosystem its launched into. Another analogy may be a new species that has emerged blinking onto the landscape and has to adapt to its niche.
Its too early to say whether this particular program will work, after all execution is 9/10 ths of the lore, but I think the proposed areas of focus are in the right direction. The one thing this piece does not say, of course, is that for any startup taking money from an accellerator, incubator, seed investors etc - Cave Contract! Get a lawyer to look it over.
*Yes, in the Bubbletime we are also sceptical of any New New Accelerator story, but this piece has some interesting points.
Wednesday, August 8. 2012
Comparing outcomes so far of Y Combinators v "The Rest" - c 119 US Accelerators that came after (Source Konczal et al)
In Dotcom 1.0 there were Incubators. These businesses typically rented space, facilities, admin and backoffice support to startups for some cash and a share in the success (or failure) of the business, typically back to backing it against investment from others who hoped to get into startup portfolio investment. Cometh the Dot Bomb, goeth the Incubators, and they got a bit of a bad name, a recent study by Jared Konczal of the Kaufmann Foundation, showing what everyone suspected empirically - Forbes:
The findings reveal that the effects of incubation are potentially deleterious to the long-term survival and performance of new ventures. Incubated firms outperform their peers in terms of employment and sales growth but fail sooner. These are important findings for policymakers who support incubation as a strategy to increase employment locally and for entrepreneurs who risk their livelihoods in order to earn a decent living.
Cometh Bubble 2.0, cometh Incubator 2.0 - only they have been rebranded, "Combinator" was tried but never took off, the New New Word is an Accelerator. The business models has also changed a bit- Forbes again:
In other words they are Incubators with a more direct funding link (and often without the benefit of any facilities to help startup companies with). But are they any more effective?
Claims are made by their proponents that they are more effective (eg Grasshopper, here). As Konczal notes, the major criticism of such assertions is there is no "blind test" vs other startups that did not use Accelerators. In essence though, from the data, the main issue that emerges is that you have a huge differences in impact between the Very Early In to any trend (like Y Combinator) that work out very well, and the following horde of me-toos that don't (as was true for Incubators, and the VC game in general). One piece of research is noted by Konczal. Based on the c 120 Acceleraror programs in the seed-db.com database, it shows that by 2012 Accelerators are a massive wealth reduction agents to the end-of-the-line funders. As the chart at the top shows, splitting Y combinator out from The Rest, Y Combinator is profitable whereas The Rest, on aggregate, are massively loss making - $300,000 lost for every startup job created is all you need to know. (The author points out his data is not accurate, but has some sound reasons to suppose it is indicative - ie the non reported costs are probably larger owing to many types of investments being below the radar).
Interestingly, Konczal notes a NESTA (UK) study from last year that I read just after we were developng the Bubble-O-Meter, the NESTA research noted the rapid growth (see graph below), said that early evidence was that they were a positive influence, but noted 4 main risks:
NESTA Graph of Accelerator Growth in USA. Perish the thought its a Bubble....
We've been following the Accelerator trend since 2007, here was what the state of our research c 2008 was:
By 2011, when NESTA was writing their report, we had seen the latest bubble in Accelerators and listed it as No 4 in our Bubble-O-Meter trends.
Looking at the huge growth in Accelerators since c 2006 again now, and juxtaposing the Kauffman data, we'd propose that bubble-like behaviour has indeed emerged here, and the me-too startup count is rising (empirical observation sure, but a lot of them do look similar). If the dotcom era is anything to go by, this implies that anything founded since the "bubbly bit" began in the graph - about 2007/8 looking at the graph, soon after Y Combinator according to the chart - is probably not going to make any money for its funders.
Sunday, August 5. 2012
Yesterday I was one of the "response" speakers to Jimmy Wales' talk at the London Mayor's "Technology: Disruption and Convergence" debate. Facilitator Nico Macdonald had asked me to focus on what London had to do to foster Innovation in new technology (and, by extension, startups in London). According to the hype, we have the skills, we have the people, we have the creativity, we have the Accelerators, we even have Tech City.
Hype notwithstanding, we are probably all also familiar with the major barriers the UK has for startups getting big, ie:
However, when you look at Wikipedia. it wasn't relying on VCs, its product inspired people worldwide to contribute en masse, wasn't up against subsidised industries, wasn't shooting for "success" and it was hardly a company structure being Not For Profit - so, none of these UK disadvantages mattered.
So, why did JImmy Wales, an ex Chicago currency trader, set this up in the US rather than some UK person set it up here (Heck, we have enough ex-currency traders of our own)?
I suggested 3 hypotheses, assuming our Entrepreneurs were no less creative than anyone else's:
- Numbers - there were just more entrepreneurs in the US, so it was more likely there.
Wales's view was interesting (bear in mind he is now living in London so has some familiiarity with the scene). He said he wasn't in Silicon Valley, and set up Wikipedia far from the "SV bubble", and that he would have set it up wherever he was. He agreed that the "large number of small frictions" is a factor in the UK, but said one of the biggest risks was.....
.....UK Libel Laws
Wales said Wikipedia still does not put any of its servers in the UK owing to the risks posed by UK libel laws. Its not just that they overprotect and can deliver large damages, but they are also unclear and unpredictable which adds cost, time and hassle and would make it very dfficult to operate Wikipedia effectively.
So, there you have it.
Wales feels the UK/EU laws around content, and its freedom. are major barriers to content based startup success. Which points to an issue for the UK, and London in particular. As another spot speaker, Dean Bubbley, pointed out, there is not much "Silicon" in Silicon Roundabout (or in the UK overall really), and creative content (media, software etc) is where the UK punches way above its weight in (the traditional British succesful startup is a world class rock band, not a world beating Tech company).
And yet, and yet..I am still sitting here wondering why someone - anyone - in the UK didn't do something like this, even if it became an heroic failure...... so, do we need to look at our much vaunted innovative creativity again, or maybe Jimmy's 3 previous failures were what winnowed Wikipedia?
Update - interesting response from El Reg -on British Wikipedias.....
....and on their scaling:
We can see that Britain does have wiki-style distributed user-contributed projects. However, what it doesn't have is a "Wikipedia Cult": our collaborative projects don't have utopian aspirations, and don't claim to save the world. Ours aren't given utopian status by slack-jawed journalists, pundits, management consultants and gabfest organisers. Ours don't have a Messianic leader; Wales styles himself as Wikipedia's "spiritual leader". You could make the case that the British projects are Wikipedia done properly – without The Bullshit.
I think he may have something there, we tend not to boost technology in the UK. I was reflecting on this last night, when on BBC's premier Newsnight analysis priogram neither the Mars landing nor Bernard Lovell's death were covered, whereas the death of an Arts TV prersenter was
(Twitterstream of the event is over here)
Friday, June 8. 2012
Given the current vogue for "lean startups" I thought it may be useful to point towards a fact based alternative way of looking at the problem. Harvard Business School's Noam Wasserman on what drives success and failure of a startup. He has surveyed nearly 10,000 founders from 3,500 ventures, compiling his results in a huge database that he has mined for patterns, and he has now published a book on it “The Founder’s Dilemmas: Anticipating and Avoiding the Pitfalls That Can Sink a Startup”.
I haven't started it yet, just a quick flick through - but there is this video and an article in the NYT summarising his research where he mentions 3 main somewhat counter-intuitive learnings:
In other words, it is about The Team - but not the people, more the structure.
Some years ago I wrote about the original "Founders Discount" where it is highly likely that they will operate at a financial dioscount to their potential. That there is another dilemma - losing your job - is another issue not often well understood. There are two main drivers:
Often you begin with a technical founder, a scientific founder, someone with deep knowledge who is the best person to lead the charge during the early development of the product. But as soon as they succeed at hitting that milestone, they have to go and build a company. Often they have the exact wrong set of skills for the next stage of development. And one of the big problems is that their success heightens their belief that they’re the right person to keep running the show.
The anguish is therefore whether to jump out the seat before being pushed, in the hope that you get a smaller share of a greater pie:
The quantitative data shows that, for founders who keep control of their boards and hang onto the C.E.O. position, their own personal equity stake is worth half as much as if they give up control to a brand-new C.E.O. with resources to grow the value of the venture. That’s the “rich-versus-king” tradeoff.
The trick, as anyone who has been here will testify, is not to get shafted once you have relinquished your powers. On this, Mr Wasserman is sadly silent in the article, but does deal with it in the book. Suffice to say Mr Zuckerman was an able student
Incidentally, I read a fascinating lecture by Michael Lewis on a related topic to Princeton undergraduates, pointing out that his career was largely based on luck - and that that luck would not have occurred if he hadn't been to Princeton:
Friday, May 25. 2012
Last Friday I gave a talk at SxSC, a day held at Southampton University to showcase new Web/'Net based technologies. My talk was on the role of hype and bubbles in the creation/destruction nature of technolgy innovation (slides are here), but to me the most interesting thing was watching all the embryo technologies on display and listening to the other talks, as - as is the wont of Universities - they tend to be doing the really new, "isn't this interesting - hmmm, what if I do that next" sort of groundbreaking stuff, which allows you to take a view of where things may go.
In a nutshell, the things demonstrated were:
Distributed Music - Enrique Tomas and Alain Renaud gave talks on using music distributed all over the Web Enrique's application mashed GPS position and movement, so he can spread music across a landscape, mapped to a (potentially shifting) territory. Alain was using high speed internet to drive real time interactive performances in a multiplicity of spaces. (Bah - its easier to watch than explain - think about a variable soundstage that follows you around - I am also certain at one stage Enrique transformed hsi internet signal into a soundscape so that the 'Net was played as an instrument. If I were Dolby et al, I'd be watching with interest.
3D Manipulation and Printing - Paul Walland demonstrated digitised 3D masks from museums collections. These 3D mapping and visualisation techniques will clearly influence where 3D printing will come in. James Miles showed how to use Reflectance Transformation Imaging on existing three dimensional datasets in a virtual environment, which allowd them to show hard-to-discern archaeological features in a landscape.
Use of Social Media: Adam Procter showed research on how we interact with social networks via “streams”, and his thoughts about the emerging "conversation economy", and a joint Tsinghua-Southampton University project that analysed how the young in the 2 countries perceived the world, using their online output and extracting and visualising it.
There was also Peter Bennett's Chronotape (see here) which is a 3D timeline, used in the example shown for family history research - but it is a 3D interface to display and control multiple-thread time sequencing very simply.
In fact I wish I had videos of all the talks because the thing I've found hard here is to describe what was actually going on - and that is probably also a sign of these times and projects - you have to see this stuff to "get" it.
Also fascinating conversations about what you can now do with holography, using 3D imaging and archaeological research to recreate 8th century Caliphate Baghdad, using agent based simulation to deduce social network interactions among others. And 3D printing - there was so much talk about what might be done with 3D printing. Not just the common or garden squirty plastic sort, but imagine much bigger ones working on composiies, sintered metals, resins etc etc...
All in all a very interesting day, its taken me a week to let everything percolate through, and I can see 3 megatrends here:
Oh, and one last thing. Open Source. makes all this possible at fractional costs vs individual "re-inventing wheels" research. Of course, you know that, but here it was tangible
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