Frontiers
with Peter Evans

"If I can take living tissue and make them part of a system that involves living tissue which is hard to control and electronic circuits which we have a hundred years experience in controlling,then all of a sudden I have a hybrid object that has the same flexibility and adaptability as a biological system,but then the controllability of an electronic circuit."

"Putting a neurone with silicon and having these things work symbiotically so to speak,we hope that this will become a complete package where we have neurones and silicon working together.Not silicon driving neurones,or silicon asking neurones 'How are you functioning?',but actually working together for a common task."

"We're trying to create computer chips,that learn,that get better with age,and that can solve complex problems not through brute force,but through adaptability."

Peter Evans : I think I know what you're thinking,trying to create a symbiant of living nerve cells and inanimate electronic circuitry doesn't sound much like respectable science,more like a latter day version of the demonic deeds of that colourful experimental neurobiologist,Dr Frankenstein.

"There's nothing to fear,look,no blood no decay,just a few stitches,and look, here's the final touch,the brain you stole Fritz.Think of it, the brain of a dead man,waiting to live again in a body I made in my own hands. (Lightning bolt) It's alive! It's alive! It's alive! It's alive! It's alive! It's alive! (Lightning bolt) "

Peter Evans : The dramatically eerie smoky lab of Frankenstein with atmospheric noises off isn't one bit like the working environment of professor William Ditto [I bet he gets teased -LB] a physicist at the Georgia Institute of Technology in Atlanta,Georgia Tech His domain is a sparkling new stainless steel and glass confection,housing multi disciplinary laboratories,pursuing an ambitious [Jeff Beck would be proud -LB]and admittedly whack sounding project - a new breed of thinking computers,that combine the hard dry stuff of silicon with the wet pliable material of biological tissue,namely brain cells.
[To me this is the only way to make a thinking machine -LB]
Forget to the manic cackle and flowing cloak of Mary Shelley's anti hero,Bill Ditto is a friendly casually dressed family man,who happens to have a passion of biocomputing,an area that's still at the fringes of modern research.A bit of a maverick perhaps,but one who commands both the respect and support of the scientific establishment.

Bill Ditto : As we work down here we get wetter and more bio-.

Peter Evans :  When did you as a physicist stroke engineer I guess,when did you get interested in the idea of biocomputing?

Bill Ditto :  Well you know I was actually inspired by a couple of things. I read a couple of articles about how conventional computing was going to hit the wall of physics in about 5 or 10 more years [see members.nbci.com/Templarser/chess.html {The King makes his move....}].
Maybe even 20 more years if we're lucky,okay you can only shrink transistors so much,down to a single atom and I was reading that and I was actually also reading an interesting story,it was actually I think it was an INTEL engineer,who was talking about that one of the biggest problems isn't going to be shrinking everything so much,okay,we're going to hit that wall,but we're going to hit the power law sooner
[By a strange coincidence or Radio 4 planning In Our Time covers the subject this week,see iotm.html at the nbci URL -LB]

and the power law is that,it just that every time you shrink everything and put more and more transistors on a smaller and smaller substrate,it utilises more power,and anybody who has actually touched one of these INTEL Pentium chips realises they are lot hotter today than they were ten years ago [And that's why they have fans on the top -LB].

Peter Evans : And excessive heat is damaging?

Bill Ditto : Oh absolutely,I mean you can fry an egg on these things,and so imagine at a certain point you can't do it,you can't vent enough heat,so that's also one of the considerations,it's very poorly known by the general public,but the engineers are sweating over it right now.So there's no doubt about it,the basic physics tells us whether it's being 10 years,20 years from now,is that this technology ultimately is going...is not going...you know Moore's law where the speed of every computer chip doubles every 18 months is going to come to an abrupt halt.
 And so the other articles I had been reading had been on quantum computing [see qcomp1 and qcomp2.html @nbci],the idea that you can use quantum systems in order to solve problems and the other one was DNA computing [See algo.html and fittest.html @nbci] which was also fascinating,where DNA computers could solve...I think there's a woman at Princeton who is solving chess problems with DNA [See http://www.newscientist.com/news/news.jsp?id=ns222722  and  http://www.newscientist.com/archive/archive.jsp?id=20384100]

and so we're were thinking about the thing okay if you use quantum computers you're slave to quantum systems,you use DNA computers you're a slave to DNA,if you use dynamics you're a slave to anything which has dynamics,and that's just about everything around you.
So I mean theoretically I could couple you know a variety of clocks together and actually get them to do computation.I could use circuits,I can use tissue,I can use anything....I can use...and a very interesting application is high speed lasers,which behave chaotically [see beffect.html@nbci] and have very complex dynamics.
Now there's a situation where I'm going to take an optical system that's behaving very quickly and potentially be able to make a computer out of it.
We're actually going a little different way,we're looking...we want computers that potentially we can actually cultivate or grow,that will solve problems in a fundamentally different manner than our conventional PCs.

Peter Evans :  And the fundamentally different manner that Bill Ditto refers to is based on an important property that biological brains possess and silicon chips do not.
The silicon-based computer is a glorified adding machine,at great speed it carries out computations logically and systematically,the process is essentially linear from A to B.
 The brain is on the other hand what the engineer would call a complex non-linear dynamical system,
[See  seedark.html,beffect.html,randreal.html and forecast.html @nbci]

It processes information according to the principles of chaos,from A to B sometimes,but just as likely from A to C or A to Z.
Why though do Bill Ditto and colleagues feel that they need to pursue Chaotic Nonlinear computing? After all number crunching brute force of supercomputers,PCs laptops and now hand held computers is serving us extraordinarily well.

Bill Ditto :  If you ask the question what don't computers do right now,they don't drive in traffic [Traffic is subject to chaos too,not the observed kind,but the Theory kind -LB],you know they're not capable of  doing that,and I'll be honest with you,I don't use a personal digital assistant in the handwriting mode,because it doesn't recognise my handwriting,you know,my 5 year old who is just learning to read,can recognise my letters,but this thing can't. Well we've been hearing every couple of years that if we just had a little faster computer that problem would be solved.
[Bill's right,the AI types are going about it all wrong -LB]
So we say "Oh we'll just wait a couple more years,then wait a couple more",problem is we're just applying the wrong tool.So what is the right tool? Well biological systems,we already know,they do motor control,pattern recognition things amazingly well. So we're going to look at problems like shining patterns on things like photo sensitive neurones to see if we can actually do pattern recognition better. There are a variety of problems associated with motor control,could you put these things in robotic vehicles and send them out into space.
You remember,when we write a conventional program,we try to anticipate every situation,and I got to tell you,just anticipating every situation of what's going to happen after I leave this building and try to drive around town is absolutely impossible,

[Prediction and prophecy is impossible -LB]

I couldn't write that program,I couldn't run that program.

Peter Evans :   And yet you have a brain which is wonderfully adaptable to be able to cope with that situation.

Bill Ditto :  Absolutely,and that's what we're trying to so,

[A brain predicts from experience and pattern recognition,it does not know the future but hones in on a near guess.Future-telling is impossible in principle -LB]

we're trying to create computer chips that get better with age and that can solve complex problems not through brute force,but through adaptability.

Peter Evans :  And what makes the human brain so adaptable,so able to learn from experience,is that it's essentially a chaotic system. Michael Firman who works alongside Bill Ditto in Georgia Tech's bioengineering labs.

Michael Firman : There was a science fiction story,years ago,written about a guy that went back in time,and the only thing he did was,he accidentally killed a butterfly [see beffect.html@nbci], and when he came back everything had changed.

[ I don't buy the premise of this story,when he got back the history would have been that with the squished butterfly.It's like the story of Lucy Lightfoot. If one uses David Deutsch's view of time the guy moves off a time line rather like "Back to the Future" this avoids "The grandfather paradox" -LB]

Now if you think of that point in time as you know,this path could have gone this way or it could have gone that way,in Chaos it says it goes in an ordered path,there is order to it.
Chaos does not mean random [see random.html and mathex4.html {Pattern ,order and Chaos} @nbci].It means there is order,any more than that history all of a sudden went to randomness,because of the butterfly dying,but it took a different path,a different ordered path in a sense,and that different ordered path is one of the things is seems that neurones seem to like to communicate with.

[This is a slightly different view of "collapsing the wave function" from QP.The boundary between Chaos and QP is explored in 2-worlds.html@nbci -LB]

Peter Evans :  Just going back to the neuro physiology,so if the brain....when the brain carries out tasks,does it take different ordered paths to arrive at the same end points,so I give you a task and you carry it out,do you always take the same trajectory or do you take different trajectories on a sort of totally random basis,one after the other?

[This maybe an example of what Mark Bucannon talks of in In Our Time of where a statistical overview is necessary -LB]

Michael Firman :  Well it basically says that if I'm sitting right here,and then I scoot over a quarter of an inch [Oh imperial this time,I wish they'd make up their minds,I guess it is the USA -LB],and sit a quarter of an inch to the right,and you give me the same task in each situation,I would actually take somewhat of a different path,even though to you,it looks like I might have done the same thing,they would be two different paths.Because I started from a different condition.

[This is a parameter that makes prediction impossible,sensitivity to initial conditions (see beffect.html) -LB]

It could mean that as I get up I might have to move this chair a different direction than if I got up and went that way,and yet I'm going off to do the same task.

Peter Evans :   That gives us the ability to cope with novelty doesn't it? Because virtually every task,we never do any task with exactly the same starting conditions as we did it before?

Michael Firman : Right.

Bill Ditto :  So what we're seeing is,is that we can design with instabilities,we can design with irregular behaviour,with this randomness and this chaotic behaviour then we can actually get away with a lot more flexibility.We can design circuits that don't just do one thing,but do a thousand things.If  you are only ever going to do one thing,you can always optimise,almost always optimise it and make one thing that just does that perfectly,but if you did that,you'd be...you'd die in an instant,you'd just...if you could only do one thing - walk,you'd walk right into the wall,because you couldn't avoid anything,right off a cliff.
So we're trying to create circuits that aren't going to be just you know single minded,that can actually change their behaviour,given varying conditions,can change their function,and that's why we're looking at things like non-linear dynamical systems,because they..we can actually morph them from say memory element to a computational element to a connectivity element,we don't have to change the hardware,we can just their operating point,and that's what we're really working towards.

Peter Evans :   The first step in the creation of a neuro silicon computer is to try to connect up the animate with the inanimate.
Paul Garcia is just running an experiment using small clusters of rat brain cells [See singer.html@nbci],to which he's trying to attach a vanishingly fine micro electrode,that will in turn connect up with a computer chip.He observes his progress under a high power microscope or on a VDU monitor.

Bill Ditto :   So how's it going Paul? Is this a ....you're trying to...

Paul Garcia : I'm first going to just get my electrode into the chamber here,and then we'll see if we can't stick a cell.

Peter Evans :  And Paul you just want one cell at a time, yes?

Paul Garcia : Yes,in fact I'll show you them on the monitor here in just a second,let me show you on the  low power,this is the structure....

Peter Evans :  So we have the microscope on it and now we seeing a feed from the VDU there.

Paul Garcia : This in on low power image,and all of these little bumps down here...

Peter Evans :  Right.

Paul Garcia : ..are cells.

Peter Evans :  Brain cells.

Paul Garcia :  And there from a tissue...er structure called the Hippocampus.

Peter Evans :  Right.

Paul Garcia :  From the rat brain.

Peter Evans :  This is very hands on and very fiddly isn't it? Really,it's quite....

Paul Garcia :  Oh absolutely.

Peter Evans :  ...delicate.I mean it goes wrong,I mean just simply goes wrong because of, basically because of the delicacy of the whole set up?

Paul Garcia :  Oh absolutely.You have no idea how frustrating this can be at times.

Bill Ditto :  There's one reason why we're trying to move over into the technology where we grow them on silicon chips,a little more reproducibly in patterns,because right now where this is very much a cottage industry that requires a fair amount of talent of which Paul has a lot more than I do,in doing this,in order to get everything to work.

Peter Evans :   Alright well Paul's got something else up on the screen,so what is this then Paul?

Paul Garcia :  So this is a higher power of the exact same area that we were looking at.

Peter Evans :  Right.

Paul Garcia :  This is the CA1 region of the Hippocampus,all these are cells..

Peter Evans :  Right. Individual cells.

Paul Garcia :  They're called parametal (?) cells,yes.

Peter Evans :  So what are you looking for,are you looking for sort of a couple of good candidates to hook up basically?

Paul Garcia :   Yes,that's true.Actually what I'm going to do now is I've got to find my electrode tip,the thing that I'm going to touch the cells onto,I need to get that in the plane of focus,I need to get that in the objective.

Peter Evans :  And you're doing this manually is it?

Paul Garcia :  Yeah,and that's actually no small task.

Bill Ditto : Right now what we're trying to understand is that if we take one cell,and one chaotic circuit [see mastring.html@nbci which is by Bill Ditto] and have them bidirectionally...or have talk to both...to each other,to understand exactly what the dynamics are of that so that we can actually get it to do some simple computation,and this is just the very beginning of all of that.We've been quite successful at having leech neurones talk to other leech neurones through artificial synapses,and so now what now we want to do is have them talk to circuitry,through the same type of language this artificial synapse and so there's just the early experiments are getting that all to work.

Peter Evans :   Can we just talk a little bit about how you marry the inanimate to effectively the animate,because these nerve cells have got to be viable,they've got to behave biologically,so they're still alive to all intents and purposes?

Bill Ditto : Yes,and so the there are certain basic things,you've have to make certain that they don't die because of toxic effects,and that's been some breakthroughs over the last 4-5 years,not by us but by other groups across the country that enables us to do that.
So there are techniques for laying down protein layers other layers on silicon circuitry to keep things alive,and to keep things profusing through it.
There's a problem - a natural question people are going to ask is "Well what good will this be if these things only live a week or two?",right? Well,there's two answers to that. One of which is we can keep replenishing them,keep growing more,the other answer is that,that's not true anymore,we can actually keep them alive indefinitely,okay the group,Steve Potter at CalTech has managed to seal neurones in with the circuitry,and they've kept them going for over 8 months.

Steve Potter : Nerve cells are very touchy cells to grow,a lot of people who do cell culture I would say the great majority of people who do cell culture are growing some kind of cells that can divide and if a large number of them die off,that's no big deal,because they just divide and produce more,and nerve cells,for the most part,are done dividing by the time that the animal's born,so the cells that we start our culture's off with are the ones that we're stuck with for the duration of the experiment,in our case several months,so we have to take care of them very carefully,so that means that we have to feed them with the proper nutrients,the basic recipe is just a lot of the same stuff that's in your blood,and we feed them about once a week,meaning that we take the dishes out of the incubator and we open the up and take out the old medium and put some new medium in,and we have to prevent the cultures from getting infected.

[Wow,imagine that,instead of a Melissa virus - if your computer caught a cold and wouldn't work because it had flu symptoms! -LB]

That's the primary cause of death of these types of cultures.So ,one of the ways we keep cells from getting infected is to grow them in completely sealed chambers,that are sealed with a special membrane that allows gases to get through,so that they can still receive oxygen and carbon dioxide,which they need to stay alive,however the bugs can't get in,and another thing,and added benefit from that is that it's very hard to spill some medium onto your electronics when your being a little too clumsy handling these things.

Paul Garcia :  Wait,there,it looks like we're getting close,there we are.

Peter Evans :  Ahhh.

Paul Garcia :  See there we are and here's my electrode tip just above it,it's a ...I'm just slowly going to drop onto the membrane of the cell and try and form a patch.
(tone sounds)

Peter Evans :  And we can hear this tone in the background...

Paul Garcia : That's right.

Peter Evans :  ...okay.

Paul Garcia :  And then when I get onto the cell you're going to hear an increase in the frequency,of the tone.

Peter Evans : So there...(tone pitch rises abruptly) ...ah! You made it,and the tone is so high I don't think we can hear it,it's beyond audible frequencies,but you're on basically,well congratulations.

Paul Garcia :  Well thanks.

Peter Evans : We can now run it. (laughs)

Paul Garcia : We'll do our best.

Peter Evans :  So contact is made between a fine wire electrode and a living brain cell. It's a vital first frontier you have to cross in order to build a biocomputer.But it is only one neurone being brought into play.Computing demands quite a lot more.

Bill Ditto : What we'd like to get to,and we're not anywhere near there yet, is that we'd like to be able to grow our computers,you could have bioreactors to be able to cultivate these things and grow many many hundreds of millions of cells okay? And right now we're really concentrating on just one to hook up to one particular circuit.
What is in the design phase,is to actually use three dimensional cubes or chunks of tissue which typically have 500,000 to a million neurones,say about a millimetre on each side [Oh back to metric also in the USA -LB] and so then once we can manipulate that type of construct,then we're going to go to larger structures that have hundreds of millions of neurones.
I don't know how long that's going to take,that's quite a bit into the future,because right now we're in the single digits of neurones,okay.But fundamentally it's still a dynamical system,and what we want to work is that if we're not solving a fast enough,we'll just throw in another hundred million neurones,or another hundred million connections,you know? Or manipulate a hundred million connections,and let them throw in the connections themselves,and we'll manipulate them.So really it comes down to control.

Peter Evans :   And that's where silicon chips come into the picture to give the necessary control over complex arrays of brain cells.

Bill Ditto : It's like a hundred years ago we didn't have enough control over electrical circuits,we kind of...people still thought electricity was a fluid in those days okay,and they said "Oh it's something else and we have some theory here,but we have no control over it", and then people started putting together resistors and light bulbs and all that stuff,and the natural outcourse of that is the..well this technological marvel that we see around us or hazard as the case may be.
So why do we start hooking up circuits into this? It's because if I can take living tissue and make them part of a system that involves living tissue,which is hard to control and electronic circuits that we have a hundred years experience in controlling,then all of a sudden  I have a hybrid object that has the same flexibility and adaptability as a biological system or most of it,but then the the controllability of an electronic circuit.

Peter Evans :    Let's roll the clock on say a few years to a time when Bill Ditto's able to build a neuro - silicon hybrid.One part of it a huge number of working brain cells,the other a computer chip control mechanism for offering up problems and outputting the solutions.How would you program such a strange piece of bioengineering? Theory suggests it can be done.

Bill Ditto :  I was actually in a conference in India,and I met an extremely bright young woman,a Professor in India by the name of Sadesh Nosinhar and we both were talking like we are now,and we were saying,well why don't...? The brain is a dynamical system,we;re looking at nonlinear dynamics and chaos,we say well why can't dynamical systems do computation? We've heard of quantum computers and DNA computers and boolean computers,and so on,and so she and I started working on trying to develop the mathematics behind how to make dynamical systems do computation,and after a year or two we managed to find out that not only could we get them to do computation,but we almost can't stop them from doing computation,once we looked,and you know,the mathematics gets a little hairy at times [That's the nature of the hairy beast -LB],but what we really basically are doing are exploiting the fact that real world nonlinear systems have an almost infinite richness of behaviour and pattern. [See members.aol.com/Templarser/fractals.html],and that each of those patterns can do information processing,if you do it right,okay? And through manipulation of those patterns,well we started with the kind of the stupidest thing possible.Let's see if we can do binary arithmetic,and do a logic operation and those kind of things,and of course we could. So then we said okay well let's get it to do like addition and multiplications and things like that,but not doing...not using binary algebra [All modern PCs do -LB],but using dynamics pure and simple,it worked beautifully.
 As it turned out we could take a system and we could tune it and we could get it to do you know addition,we could get it to do multiplication.Lo and behold we could actually hook it up in order to do some specialised mathematical operations,which were quite surprising,one of which involved something called the "Least common multiplier" which is just an operation on integers,but it's not a simple one.All of a sudden our dynamical system could spit it out,and do it reliably,okay?
So that led us to some recent work where we were starting to look at the type of problems that the quantum people look at ,because they have the same problem,"where am I faster, where am I better,how am I going to solve it in a different way?" and so we were looking at a couple of basic computer science problems that become very complex very quickly,which are related or have the same kind of problems associated with the travelling salesman problem [see loglimit.html,qcomp2.html @nbci].
I think you and I and everybody,you know could figure out,that if I have 2 or 3 cities to get to what's the best way to organise it? If I'm going to sell you know say pigs in 3 cities,how do I go?
[I'll let the speciesism go,pigs are known for their curly tails,perhaps this is a (Pigs)tail of 3 Cities? -LB]

No problem.Now imagine 100 cities,now it gets difficult,now it's really difficult.So what we manage to do is get dynamical systems to solve the rudiments of those kind of problems,kind of a proof of concept that yeah they can solve things exponentially faster than conventional computers.That ....because it's a dynamical system,we can choose any dynamical system we want.We can do it with living tissue,because it's a dynamical system,

[I wonder if you could use fluids,even water,as fluids are dynamical systems,or maybe gases,and then maybe people would get the Frankenstein reaction -LB]

Peter Evans : What applications then [Here's the utilitarian bit!  "What use is a baby?" -LB] will there be for tomorrow's biocomputers,using Chaos to find solutions to the kinds of problems that today's computers can't touch?
Well,one use will clearly be in faster and more versatile machines for tackling perennially difficult tasks such as recognising faces and deciphering untidy handwriting.
Biocomputers would also be adept at tackling horrendously difficult scientific problems such as weather prediction [see forecast.html,beffect.html @nbci].
For Michael Firman,there's also a host of other less expected applications.

[In other words things that it can do it wasn't designed for,you can't foresee where it will go,or what potential benefits it has,you cannot therefore do "only good science" or make "only good applications".We take on the spectre of Frankenstein and have to deal with it,it's no use hand-wringing about Robocops and Terminators -LB]

Michael Firman : I'm working on another idea where we use this interface to allow quadriplegics to drive a wheelchair,and you know I was concerned when I said that,you would probably cause.....cost implants into the brain that are actually fused in some fashion to the brain or inside the brain,and batteries inside and so forth,and transmitters and so forth,to where they would be able to control the movement of their wheelchair and things of that nature,and I thought,you know "is anyone going to let you do that?".

[Note here that a scientist is worrying about moral implications and the mood of society,because the naysayers and clock-turners and moral reactionaries keep bleating, suffering might continue.No doubt they'd say that these people would become like Davros out of Dr Who and be rendered evil by having machines in their heads,or like Darth Vader another misplaced metaphor for the evils of technology,when all it is is giving a better quality of life to people -LB]

And the few quadriplegics that I've talked with have said you know "What do you think about this idea? What's going to happen?",you know? If someone came up to you and said "This is a possibility",in every single case they've said,"Don't tell me about possibilities,tell me when it happens,I want to be first".

[And why should they be stopped because someone else has a moral problem with it? -LB]

Peter Evans : Not only can neuro-silicon computing be harnessed to create novel technological advances.Steve Potter and Bill Ditto believe that biocomputers may shed light on the most advanced piece of technology in the whole cosmos - that of the brain itself.

Bill Ditto : Once we start to try to design with them,we start to now all of a sudden say things like "Aha,now we understand why the brain doesn't do something,or why it does do something", because,you know,just because we can't do it,doesn't mean Nature can't do it,but if we understand like a major design problem with doing something in a particular way,then we come back and say "Well that's probably why Nature didn't do it".

[And if scientists are using Nature as the model how in Einstein's name can they be doing "unnatural things"? They are following Nature's lead and copying her -LB]

And so this is actually quite different from what neuroscientists do. Neuroscientists are kind of lurkers,they kind of,they want their presence to be as minimal as possible,and they want to observe,okay? What we're trying to do is say "Hey I'm going to try and design with this and I really want to fall on my face because I can write that into the 'don't do this' category"

[This makes a mockery of those that chide science for making mistakes,the mistakes are as if not more important for doing science,they are inevitable and necessary ,there therefore is no point in scoffing when it does fall on its face.Science is at least trying.Those that scoff have world views that don't even try to understand anything or progress -LB]

But that also then leads me back to the neuroscience where it says "Well does the brain do that?". If the brain does it then we're missing something,if the brain doesn't do it,maybe we have a clue of why it doesn't do it that way.

Steve Potter : I think that Bill Ditto is definitely onto something in believing that there are fundamentally different types of computation going on in nerve systems or in other systems, and the way I like to look at it is that we have embarked on a voyage and we struck ground on an island and have run into the natives and we have no idea what they are saying exactly,but we can listen into them clearly now,and we can also try to make sounds like they make and see how they respond.
(chaotic music plays)

Peter Evans : as I said at the beginning of the programme,Bill Ditto's research,for all its apparent eccentricity is finding more and more favour with his peers,indeed his isn't the only lab working on the sci-fi notion of silicon brain cell hybrids,even so he's used to people expressing scepticism,a little fear,and sometimes downright derision.
His response is typically not to hit the brake,but to press down on the accelerator.

[This shows the "shooting oneself in the foot" effect of those with qualms about such research. It's better to understand and take issue,rather than reject out of fear and ignorance -LB]

Bill Ditto : Our big motto here is that "fortune favours the bold" and even if we fall flat on our face,and I can guarantee one of two outcomes,either it will work or it won't,right? 
[Impeccable tautological reasoning -LB]
But even if we fall flat on our face,we're learning things every day that have not been explored before.

[Exactly and that exploration and learning is valuable ANYWAY regardless of whether it succeeds and finds application -LB]

New ways of looking at the brain,new ways of doing,you know,circuit design,in ways that people really haven't attempted. With that said,all of a sudden we've got competitors and some of those are pretty darn sharp people,and they're working very hard to go faster and further than we are,and so what I worry about every day,is not so much that we're taking too many chances,or that this idea is maybe a little bit too beyond what we know - we're reaching too far - I worry that we're not reaching far enough.
The technology is there,and the brass ring is whoever grabs it first.

[Whilst this maybe true,a gung-ho approach to science could be full of folly.Tentative assured steps maybe better,not least because of having to take public concerns and doubts into account.Whilst I feel most of the reaction against science is from ignorance,there maybe moral or ethical problems,and one cannot just ride roughshod over these and expect the public to thank you for it and provide funding to do it again (see com6.rtf@trans.html@nbci)-LB]

All web pages at members.nbci.com/Templarser/   unless otherwise stated.

20/10/2000