But not before this example of where simply using the relative frequency of words to perform spelling correction breaks down.

"And every barcode is divided into two sections by three markers and those markers are always represented by the number six. Six, six, six

"And what they’re planning to do, in order to eradicate all credit card fraud and in order to precipitate a totally cashless society…and they’ve already tested it on the American troops: they’re going to subcutaneously laser-tattoo that mark onto your right hand or onto your forehead. They’re going to replace plastic with flesh!

"Fact!"

I'll spare you the whole tirade but it leads up to the point where Johnny and the Singularists come together as one:

"And no, we’re not going to sprout extra limbs and wings and things because evolution itself is evolving. When it comes, the apocalypse itself will a part of the process of that leap of evolution. By the very definition of apocalypse, mankind must cease to exist, at least in a material form. We’ll have evolved into something that transcends matter, into a species of pure thought. Are you with me?"

And so, there I was reading Kevin Kelly's exposition of the OneMachine made out of old PCs yoked together that thinks with hyperlinks, mentally adding an extra "Fact!" at the end of every paragraph to complete the effect:

"Each new link wires up a subroutine, creates a loop, and unleashes a cascade of impulses. As waves of links surge around the world, they resemble the thought patterns of a very large brain."

Fact!

"By 2040, the planetary computer will attain as much processing power as all 7 billion human brains on Earth."

Fact!

And what do these computers actually do when harnessed as one? Some of them do something useful such as perform quantum mechanical calculations to predict protein folding. Unfortunately, they are more likely to be sending out tons of spam. But no mind, "we are headed toward a singular destiny: one vast computer composed of billions of chips and billions of brains, enveloping the planet in a single sphere of intelligence".

Fact! The techalypse is coming.

But there was one thing niggling at me: where were the figures coming from to support the contention that the One Machine rivals even one brain today? And this is assuming you accept Giulio Tononi's assertion that intelligence comes as a function of complexity, that you can just slam a bunch of circuits together and automatically get something that thinks. Towards the bottom of the page are some figures in a diagram.

By far the oddest one is the choice of 70MHz for the brain's operating frequency: "grey matter is about as speedy as an original Pentium". That sounds pretty quick to me given that the calcium induced cascade that triggers a neural response takes on the order of 200µs. That gives you a maximum frequency — even working on the basis that neurons switch like electronic transistors, which they don't — of tens of kilohertz. By that token, the human brain can barely keep up with a Sinclair ZX80. The actual frequency is probably way lower than that as neural signalling seems to rely on pulse trains that take tens of milliseconds to transmit from one neuron to another. The brain makes up for that sluggishness by not trying to work like an electronic computer. The transistor, as it turns out, is a pretty rotten analogue for a neuron, although maybe not nearly as bad as equating a hyperlink with a synapse.

But I'm really curious about the 70MHz. Where does that figure come from? Surely it can't be derived from Bruce Tainio who claimed in the early 1990s to have found a relationship between frequency and disease. According to Tainio's measurements, the brain has a 'bio-frequency' of 72MHz to 90MHz — genius intelligence is at the upper end, apparently. Fans of the woo business will be delighted to know that you can buy 'essential oils' that resonate in the same range and so help you get a better brain. And not those nasty gigahertz frequencies, like 2.4GHz, that mess your brain up. I can't find any paper from Tainio that explains his conclusions, just references on essential-oil websites, found courtesy of the resident Overmind otherwise known as Google. However, if I suspect my neurons to be running at 70MHz, I'm going to be ringing the doctor pronto, assuming that I'm actually able to.

* Sorry Orb fans, this post has approximately zero to do with Minnie Ripperton done ambient stylee, but here's a link to the video if that's all you wanted. But thanks to the Orb for sampling so much of Naked on S.A.L.T. (Orblivion) to save the aggro of fast-forwarding through the film to find the monologues.

"Yet there is still a vast difference betwixt the slovenly butchering of a man, and the fineness of a stroke that separates the head from the body and leaves it standing in its place."

In ruthlessly taking Israel apart with the humour equivalent of a rusty meat cleaver, Feldman co-opted Israel into saving the finer cuts for social media in general.

"And now it’s done, my little experiment with Social Media. I beat you with your own tools, in the arena in which you bill yourself an expert. You are an amateur Shel, an amateur, always remember that."

With the puppet, Feldman did distinctly old-media things. For one thing, it's all fake. It's a puppet pretending to be some other guy. Out through the window goes the social media stricture of "authenticity". Although the puppet was a goof, it was a lovable goof – the kind of thing old TV loves. And the set-ups were straight from from pro-TV school. It's just as well. Israel's videos were self-satirising: the one of him waving a boom mic around like a balloon on a stick in front of a bleary-eyed Jeremiah Owyang while supping disinterestedly on a latté is unforgettable. And not in a good way.

Feldman called the puppet "more real": a classic bit of legerdemain. Israel was very real during the whole spat. He was angry. He was upset. He wanted to get even. Faced with what Feldman was doing to him, what would you want to do? Social media's advice: be real, be honest.

But nobody believed the advice. The sensible advice to Israel was to bottle it up, act nice. And that probably would have worked. Had Israel gritted his teeth and pretended that he really loved the puppet, he would probably have come out of the whole episode more famous and better off. In other words, ignore Naked Conversations: Be inauthentic. You can't blog or tweet your way out of a crisis any more than you can knit your way out of a burning building.

And don't forget Feldman's position of being a pro versus Israel's amateur in what was meant to be an amateur's game.

And that is the Feldman's gift to social media in a situation where most in the club seem to have ignored the puppet sites's tag line: "A parody of Social Media’s impact on business & culture".

But what about the position of Michael Arrington and Jason Calcanis in this? Israel seems to believe that Arrington's hand was behind the puppet all of the time. Feldman's response:

"You chose to blame Mike Arrington, Jason Calacanis, and myself when you should have been blaming yourself. Mike is busy taking on AP and the NY Times. Jason is taking on Google. I’m taking on TV, do you think anyone of us have the time or even give a shit enough about you to plot a conspiracy?"

Or, to paraphrase with a slant on social media: these people are building media empires, do you imagine they give a shit about some social-media revolution? It's been good to them, it's been a laugh, but there's a lot more money in replacing the 'old-media' companies.

Now it seems to be Dave Winer's turn. The joke's just not so funny second time around but the ability of some of social media's voices to self-satirise, who knows what's possible.

Did Peter Norvig, Google's research director, really say: "All models are wrong, and increasingly you can succeed without them"? Because, if so, he seems to have misinterpreted what his own company has been doing. Yes, search and its related technologies do not rely on language models. But the core of all that Google does right now is based on a statistical approach that makes some basic assumptions about how language works. You might call it a model.

Anderson postulates a world based on machine learning, where the computer crunches through the data to come up with predictions.

"This is a world where massive amounts of data and applied mathematics replace every other tool that might be brought to bear...With enough data, the numbers speak for themselves."

Yet, machine-learning algorithms depend on the construction of some kind of model. It is not necessarily a deterministic model in the way that classical mechanics is, but just because it invokes statistics does not make it any less a model-based technique. What are models for? They allow you to make predictions about what will happen given some inputs.

They are using machine-learning and data-mining techniques to uncover patterns in the data. They are dredging through the seemingly countless genome and other 'ome databases to find data that they can plug into — yes, you guessed it — models.

Professor Jaroslav Stark of Imperial College sees modelling as a key to understanding what goes on inside living systems precisely because models are often inaccurate. For him, the fact that a model diverges from reality provides important clues to interactions that need to be taken into account. And they can provide a way to probe interactions where it is simply not possible to use traditional methods such as turning genes off selectively because that introduces other interactions.

The problem with Anderson's argument on this point is that, because what gets taught at school on biology has turned out to be inaccurate, we are getting further away from understanding through models. But that is what science is like: it finds new information, assimilates it and moves on. The biologists aren't finished yet, and aren't likely to be for another 30 years or so, even if they're lucky.

Anderson cites the work by J Craig Venter to sequence bacterial life in the oceans. A yacht is sailing around the world with a bucket to collect samples that get progressively filtered down until all you have left is bacterial DNA. This then gets dumped into an massive array of gene sequencers that randomly chop up the DNA with enzymes to produce fragments that can be separated to indicate the nucleic acids they contain. Computers then attempt to crunch through that data to reassemble the sequences into individual genomes. In practice, it's not possible to do that final step. At least, not right now. But, it is possible to see how much genes diverge among similar bacteria.

Venter has not really discovered unknown species of bacteria as Anderson writes because genetic sequence alone does not identify a species. Some of the putative genomes are very different to others, but Venter himself says that there is no percentage difference between genomes that will indicate a new species.

Basically, to identify a species, you have to go and look at how it lives and what it looks like. Maybe there is a shortcut to that process that involves the genome but until biologists fully understand the interplay between genes and the other bits of the genome, that is not going to be possible. It's probably easier with bacteria as they have comparatively little junk DNA, but it could still take some time. And the only way to build that model — even if it's a statistical one — is to assemble the genomes individually and examine the organisms. Not simply take a best guess as to how millions of fragments might match up in a genome.

What did Venter's team find? Based on predictions of the proteins that the assembled genomes produce, it seems that bacteria can have tuned versions of the light-sensitive protein proteorhodopsin. A single amino acid change in that sequence can alter the wavelength of light that the proteins absorbs and helps convert to energy. But that did not come just from blind number-crunching of the kind that Anderson suggests is the future. It was based on having a model of how rhodopsin works and then matching the gene data to it. Statistics helps, but there's still a model in there.

Big computers can certainly help with the creation and execution of models. But it seems unlikely that unleashing petaflops and petaflops on a problem blind is going to do much for machine learning.

Update: Now Kevin Kelly has chipped in, citing Google's translation system as evidence for the "stick it all in the Overmind/OneMachine" approach. Statistical language models have been kicking the structural models around the park for close to 40 years, and the techniques that work for search have some features in common with those that work in translation. What's happened with the web is that researchers have access to a huge corpus of text on which to train the systems. People are still working on the algorithms and they have to carefully pick the training corpus so as not to pollute the learning algorithm: the computers are just doing the boring legwork.

Kelly discounts idea of the approach killing scientific method. But dreams up a new term for it: "correlative analytics". This is hardly new. And questionably useful. As Robin comments below on the original version of this post, the finance community has been there, done that. Momentum trading is one 'algorithm' at the simple end of the spectrum. But it's basically taking outputs from a system and trying to use them as inputs. Not surprisingly, the results aren't all that spectacular.

However, if people want to believe that they can teach their computer biology by stuffing it full of all the genomics, proteomics, and other 'omics databases they can lay their hands on, I see no harm in letting them do it. However, the people doing real work on this stuff will be asking themselves: how was the data collected; what were the conditions? In short, while they may not read the data, they will attempt to understand how it came into being and then try to fit it into a model. It will get easier to automate some of those steps as labs adopt more standardised ways of generating the data, but we're still a long way from just stuffing bytes into a machine and let it figure it out for itself.

"So I gave up and sent mail to Amir saying - where is this Moviemaker download? Does it exist?

So they told me that using the download page to download something was not something they anticipated."

It did not get better for Billg and his download past that point. However, Todd Bishop's post has a sting in the tail. He asked Gates on his departure about the email, sent almost five-and-a-half years ago:

As for the message, Gates smiled and said, "There's not a day that I don't send a piece of e-mail ... like that piece of e-mail. That's my job."

When people ask what Microsoft will be like now that Gates has left the building, this memo and the idea that Gates sent lots of them should be the clue. Nothing. Because if any of these memos had any effect, Windows would be a rather different piece of software. The structures that Microsoft built over the last 30 years effectively nullified any direct control that Gates had over software development. I'm sure people who weren't directly responsible for the problems Gates had with the download nodded and agreed with what he had to say, and they all listened intently to his speeches. But they then went on their way to product-planning meetings that not only created these hindrances but ossified them into place.

Yet, despite having had ten years to build an unbeatable handset operating system, Symbian almost stumbled at the last hurdle. Nokia's majority ownership of the software maker has been a stumbling block with manufacturers, some of whom chose to build other user interfaces on top of the operating system to prevent Nokia from maintaining a stranglehold with the Series 60 environment. That is where environments such as UIQ and MOAP – used largely in Japan – have come in.

The situation has irritated operators such as Vodafone who find themselves having to deal with three different flavours of mobile phone built on ostensibly the same base when they have tried to tie back the number of platforms they support. Several years ago, Vodafone decided to try to restrict the amount of time it spent on software by picking three platforms: Limo; Microsoft; and Symbian. The idea of being able to bring Symbian back to one piece of software is far more attractive than the current situation.

This is where the picture of what actually happens with the Symbian Foundation gets hazy. Nokia is already some way down the road of deciding what software will be open-sourced, a process that could take two years to complete. The other players have agreed to sign up but it's unclear how much of UIQ and MOAPS will be in the final environment. Lee Williams, senior vice president for S60 software at Nokia said he reckoned the core environment will be based largely on S60 with components coming from the other guys. UIQ, for example, has a lot of touchscreen support that S60 does not.

Although the UIQ shareholders have agreed to back the Symbian Foundation by offering the environment up royalty free, some things have still to be decided, said Alain Mutricy, senior vice president of Motorola. "We are discussing right now with the UIQ management team how to restructure UIQ within the new ecosystem that is created by this move." He added later: "If we talk about two years down the road, we have to discuss with the shareholders and management team how their business model will adapt to the new ecosystem. But we will contribute the UIQ technology as and when the foundation is established."

For Vodafone, Symbian is still not the only game in town. Guido Arnone, director of Vodafone, said the company is continuing to work on the Linux-based Limo. "There is some competition but I believe it can be very complementary. Limo is relevant to higher end mobile touchscreen devices. Symbian is more lower tier. There is an air of competition for sure but there are areas where they are complementary to each other."

Tommi Uhari, executive vice president of STMicroelectronics, said he thought the removal of the royalty would help lower the point at which handset makers use Symbian. Although it was originally devised to drive the smartphone business, it now seems to be heading towards the featurephone. There is still the Linux option for handset makers and operators looking at the business Symbian might once have expected to command: the higher-end smartphones and mobile internet devices.

One litre of fuel would serve the UK for a year and oil reserves would last the expected lifetime of the solar system - if efficiency in the car industry had improved at the same rate as in the computer world - a leading computer scientist will tell an audience in Manchester, UK, on Friday 20 June 2008.

I bet he won't be telling them about the motorways clogged with automobiles stranded at odd angles as their drivers phone into call centres to be told: "Just try taking the battery out, then put it back in and start the car up. We can see if it happens again."*

Sorry, it's an old joke, but someone's got to do it.

* I once hired a Smart ForFour with an ECU that crashed so badly - in the middle of Wimbledon in rush hour - the only option was to reboot the car. When I next hired a car from them, I noticed that the ForFour was no longer on the list of vehicles.

The current design is temporary, which is why it's on a standard Movable Type template but that will change.

Not just that. The public needs to be involved and may even be in the position to stop certain kinds of research: "It is vital to recognise the importance of maintaining public legitimacy and support. In order to achieve this, scientific research must not get too far ahead of public attitudes and potential applications should demonstrate clear social benefits."

This is from a different section but covers similar ground: "Partnership with civil society groups, social scientists and ethicists should be pursued as a highly effective way of understanding critical issues, engaging with publics and winning support for emerging scientific fields. However, at the same time it must be recognised that this is a two-way process and that some ethically problematic scientific projects and potentially controversial technologies may have to be abandoned in order to maintain trust."

This all sounds good in principle. But it is a process that could lead to some seriously strange decisions being made as to which branches of biological research are pursued and which are terminated. For a good many of the ethical issues that surround synthetic biology do not lie in the research but in the application. And in many cases, the economics of the application.

According to the story, the report draws a distinction between the first generation of biofuels - basically those in production today - and the second generation which will expand the amount of plant material that can be used to produce ethanol and other fuels. My piece in the technology section looks at the role that synthetic biology is likely to play in the development of those fuels as well as the following generations, which will attempt to substitute hydrogen for carbon-based fuels.

In principle, feedstock plants for the second-generation fuels will not displace food crops. In some cases, they could be one and the same. The stover from maize could go into fuel production with the main crop being used for animal feed, if not corn-on-the-cob. As some crops, such as the one planned by Agrivida, will modify the genes of a maize plant, the latter is less likely - most of today's genetically modified maize goes either into fuel or animal feed - but there are companies working on bugs that can digest leaves and stalks without needing an altered plant. Which direction the industry takes will depend on how efficient the processes are and it is way too early to decide on that one.

However, that "in principle" is a big assumption. There is no guarantee that a technique based on synthetic biology can guarantee that economic conditions will lead to an undesired effect. One, as yet unanswered question in the use of 'waste' biomass for producing fuel is how much of the plant do you need to lead behind in the ground. If you removed everything during the harvesting process, you would be creating the conditions for a dustbowl. How much biomass need to remain behind is currently an open question. In the case of corn stover, it is far from being all of it. But there is an upper limit. It's a similar situation for rice, rape, sugar and the forests that could potentially produce bug-ready biomass.

There is no-one involved in biofuel-technology research who wants to create a dustbowl. Or, if there is, I haven't found them yet. However, it is economic incentives and regulations such as those imposed by the EU on the current generation of biofuels that can distort a market effectively enough for the conditions to be right to wreak havoc on the agricultural system. It is practically impossible for any researcher to design out that possibility from what are going to be pretty fundamental technologies. And the more you look into an area such as synthetic biology, you realise how many different research themes are intertwined. Even if you thought banning one of them would prevent the dustbowl scenario, which one would you ban?

It is worth bearing in mind that previous interventions using food crops in the widest sense have caused more localised disruption. The World Bank and others spent years telling some countries they should plant more coffee, only for those robusta producers to find they were feeding their produce into a massive world glut, and not from potentially more lucrative cash food crops. It's hardly a surprise that similar things should have happened with the biofuels business.

Over-promise is a problem with any technology. LS9's contention that it could serve the US demand for petrol with a biorefinery the size of Chicago seems not unreasonable, especially when you divide that down into smaller producers, although perhaps not as many as Rob Carlson envisages - he is looking forward to the day when every home has its own refinery. However, what is not clear is just how much sugar or biomass has to go in through the gate to produce 140 million barrels a week. The US Department of Agriculture was a lot more circumspect about using biomass for fuel in its 2004 report: a third of the US fuel demand looked ambitious then and it still is, although it is not impossible as long as some technologies come good.

It's hard to argue against having a more open dialogue in and around science. But pushing the ethical debate too far upstream is not going to achieve the effect that anyone wants. Except for the fundamental ethical issues - things such as cloning - it can work. But, very often, the potential ethical nightmares do not reveal themselves until much later. Blaming basic science for them is not going to achieve better results.