Category Archives: AI

Some trees just don’t get barked up

Now and then, someone asks me for an old document and as I search for it, I stumble across others I’d forgotten about. I’ve been rather frustrated that AI progress hasn’t kept up with its development rate in the 90s, so this was fun to rediscover, highlighting some future computing directions that offered serious but uncertain potential exactly 20 years ago, well 20 years ago 3 weeks ago. Here is the text, and the Schrodinger’s Computer was only ever intended to be silly (since renamed the Yonck Processor):

Herrings, a large subset of which are probably red

Computers in the future will use a wide range of techniques, not just conventional microprocessors. Problems should be decomposed and the various components streamed to the appropriate processing engines. One of the important requirements is therefore some means of identifying automatically which parts of a problem could best be tackled by which techniques, though sometimes it might be best to use several in parallel with some interaction between them.


We have a wider variety of components available to be used in analog computing today than we had when it effectively died out in the 80s. With much higher quality analog and mixed components, and additionally micro-sensors, MEMs, simple neural network components, and some imminent molecular capability, how can we rekindle the successes of the analog domain. Nature handles the infinite body problem with ease! Things just happen according to the laws of physics. How can we harness them too? Can we build environments with synthetic physics to achieve more effects? The whole field of non-algorithmic computation seems ripe for exploitation.

 Neural networks

  • Could we make neural microprocessor suspensions, using spherical chips suspended in gel in a reflective capsule and optical broadcasting. Couple this with growing wires across the electric field. This would give us both electrical and optical interconnection that could be ideal for neural networks with high connectivity. Could link this to gene chip technology to have chemical detection and synthesis on the chips too, so that we could have close high speed replicas of organic neural networks.
  • If we can have quantum entanglement between particles, might this affect the way in which neurons in the brain work? Do we have neural entanglement and has this anything to do with how our brain works. Could we create neural entanglement or even virtual entanglement and would it have any use?
  • Could we make molecular neurons (or similar) using ordinary chemistry? And then form them into networks. Might need nanomachines and bottom-up assembly.
  • Could we use neurons as the first stage filters to narrow down the field to make problems tractable for other techniques
  • Optical neurons
  • Magnetic neurons

Electromechanical, MEMS etc

  • Micromirror arrays as part of optical computers, perhaps either as data entry, or as part of the algorithm
  • Carbon fullerene balls and tubes as MEM components
  • External fullerene ‘décor’ as a form of information, cf antibodies in immune system
  • Sensor suspensions and gels as analog computers for direct simulation


  • Carbon fullerene tubes as on chip wires
  • Could they act as electron pipes for ultra-high speed interconnect
  • Optical or radio beacons on chip


  • Transforms – create a transform of every logic component, spreading the functionality across a wide domain, and construct programs using them instead. Small perturbation is no longer fatal but just reduces accuracy
  • Filters – nature works often using simple physical effects where humans design complex software. We need to look at hard problems to see how we might make simple filters to narrow the field before computing final details and stages conventionally.
  • Interference – is there some form of representation that allows us to compute operations by means of allowing the input data to interact directly, i.e. interference, instead of using tedious linear computation. Obviously only suited to a subset of problems.

And finally, the frivolous

  • Schrodinger’s computer – design of computer and software, if any, not determined until box is opened. The one constant is that it destroys itself if it doesn’t finding the solution. All possible computers and all possible programs exist and if there is a solution, the computer will pop out alive and well with the answer. Set it the problem of answering all possible questions too, working out which ones have the most valuable answers and using up all the available storage to write the best answers.

The future of reproductive choice

I’m not taking sides on the abortion debate, just drawing maps of the potential future, so don’t shoot the messenger.

An average baby girl is born with a million eggs, still has 300,000 when she reaches puberty, and subsequently releases 300 – 400 of these over her reproductive lifetime. Typically one or two will become kids but today a woman has no way of deciding which ones, and she certainly has no control over which sperm is used beyond choosing her partner.

Surely it can’t be very far in the future (as a wild guess, say 2050) before we fully understand the links between how someone is and their genetics (and all the other biological factors involved in determining outcome too). That knowledge could then notionally be used to create some sort of nanotech (aka magic) gate that would allow her to choose which of her eggs get to be ovulated and potentially fertilized, wasting ones she isn’t interested in and going for it when she’s released a good one. Maybe by 2060, women would also be able to filter sperm the same way, helping some while blocking others. Choice needn’t be limited to whether to have a baby or not, but which baby.

Choosing a particularly promising egg and then which sperm would combine best with it, an embryo might be created only if it is likely to result in the right person (perhaps an excellent athlete, or an artist, or a scientist, or just good looking), or deselected if it would become the wrong person (e.g. a terrorist, criminal, saxophonist, Republican).

However, by the time we have the technology to do that, and even before we fully know what gene combos result in what features, we would almost certainly be able to simply assemble any chosen DNA and insert it into an egg from which the DNA has been removed. That would seem a more reliable mechanism to get the ‘perfect’ baby than choosing from a long list of imperfect ones. Active assembly should beat deselection from a random list.

By then, we might even be using new DNA bases that don’t exist in nature, invented by people or AI to add or control features or abilities nature doesn’t reliably provide for.

If we can do that, and if we know how to simulate how someone might turn out, then we could go further and create lots of electronic babies that live their entire lives in an electronic Matrix style existence. Let’s expand on that briefly.

Even today, couples can store eggs and sperm for later use, but with this future genetic assembly, it will become feasible to create offspring from nothing more than a DNA listing. DNA from both members of a couple, of any sex, could get a record of their DNA, randomize combinations with their partner’s DNA and thus get a massive library of potential offspring. They may even be able to buy listings of celebrity DNA from the net. This creates the potential for greatly delayed birth and tradable ‘ebaybies’ – DNA listings are not alive so current laws don’t forbid trading in them. These listings could however be used to create electronic ‘virtual’offspring, simulated in a computer memory instead of being born organically. Various degrees of existence are possible with varied awareness. Couples may have many electronic babies as well as a few real ones. They may even wait to see how a simulation works out before deciding which kids to make for real. If an electronic baby turns out particularly well, it might be promoted to actual life via DNA assembly and real pregnancy. The following consequences are obvious:



Demands by infertile and gay couples to have babies via genetic assembly


It is clear that this whole technology field is rich in ethical issues! But we don’t need to go deep into future tech to find more of those. Just following current political trends to their logical conclusions introduces a lot more. I’ve written often on the random walk of values, and we cannot be confident that many values we hold today will still reign in decades time. Where might this random walk lead? Let’s explore some more.

Even in ‘conventional’ pregnancies, although the right to choose has been firmly established in most of the developed world, a woman usually has very little information about the fetus and has to make her decision almost entirely based on her own circumstances and values. The proportion of abortions related to known fetal characteristics such as genetic conditions or abnormalities is small. Most decisions can’t yet take any account of what sort of person that fetus might become. We should expect future technology to provide far more information on fetus characteristics and likely future development. Perhaps if a woman is better informed on likely outcomes, might that sometimes affect her decision, in either direction?

In some circumstances, potential outcome may be less certain and an informed decision might require more time or more tests. To allow for that without reducing the right to choose, is possible future law could allow for conditional terminations, registered before a legal time limit but performed later (before another time limit) when more is known. This period could be used for more medical tests, or to advertise the baby to potential adopters that want a child just like that one, or simply to allow more time for the mother to see how her own circumstances change. Between 2005 and 2015, USA abortion rate dropped from 1 in 6 pregnancies to 1 in 7, while in the UK, 22% of pregnancies are terminated. What would these figures be if women could determine what future person would result? Would termination rate increase? To 30%, 50%? Abandon this one and see if we can make a better one? How many of us would exist if our parents had known then what they know now?

Whether and how late terminations should be permitted is still fiercely debated. There is already discussion about allowing terminations right up to birth and even after birth in particular circumstances. If so, then why stop there? We all know people who make excellent arguments for retrospective abortion. Maybe future parents should be allowed to decide whether to keep a child right up until it reaches its teens, depending on how the child turns out. Why not 16, or 18, or even 25, when people truly reach adulthood? By then they’d know what kind of person they’re inflicting on the world. Childhood and teen years could simply be a trial period. And why should only the parents have a say? Given an overpopulated world with an infinite number of potential people that could be brought into existence, perhaps the state could also demand a high standard of social performance before assigning a life license. The Chinese state already uses surveillance technology to assign social scores. It is a relatively small logical step further to link that to life licenses that require periodic renewal. Go a bit further if you will, and link that thought to the blog I just wrote on future surveillance:

Those of you who have watched Logan’s Run will be familiar with the idea of  compulsory termination at a certain age. Why not instead have a flexible age that depends on social score? It could range from zero to 100. A pregnancy might only be permitted if the genetic blueprint passes a suitability test and then as nurture and environmental factors play their roles as a person ages, their life license could be renewed (or not) every year. A range of crimes might also result in withdrawal of a license, and subsequent termination.

Finally, what about AI? Future technology will allow us to make hybrids, symbionts if you like, with a genetically edited human-ish body, and a mind that is part human, part AI, with the AI acting partly as enhancement and partly as a control system. Maybe the future state could insist that installation into the embryo of a state ‘guardian’, a ‘supervisory AI’, essentially a deeply embedded police officer/judge/jury/executioner will be required to get the life license.

Random walks are dangerous. You can end up where you start, or somewhere very far away in any direction.

The legal battles and arguments around ‘choice’ won’t go away any time soon. They will become broader, more complex, more difficult, and more controversial.

Future Surveillance


They used to say

“Don’t think it

If you must think it, don’t say it

If you must say it, don’t write it

If you must write it, don’t sign it”
















The future for women, pdf version


Women and the Future

Augmented reality will objectify women

Microsoft Hololens 2 Visor















Who controls AI, controls the world

This week, the fastest supercomputer broke a world record for AI, using machine learning in climate research:

I guess most readers thought this is a great thing, after all we need to solve climate change. That wasn’t my thought. The first thing my boss told me when I used a computer for the first time was: “shit in, shit out”. I don’t remember his name but I remember that concise lesson every time I read about climate models. If either the model or the data is garbage, or both, the output will also be garbage.

So my first thought reading about this new record was: will they let the AI work everything out for itself using all the raw, unadjusted data available about the environment, including all the astrophysics data about every kind of solar activity, human agricultural, industrial activities, air travel, all the unadjusted measurements of or proxies for surface, sea and air temperatures, ever collected, any empirical evidence for any corrections that might be needed on such data in any direction, and then let it make its own deductions, form its own models of how it might all connected and then watch eagerly as it makes predictions?

Or will they just input their own models, CO2 blinkering, prejudices and group-think, adjusted datasets, data omissions and general distortions of historical records into biased models already indoctrinated with climate change dogma, so that it will reconfirm the doom and gloom forecasts we’re so used to hearing, maximizing their chances of continued grants? If they do that, the AI might as well be a cardboard box with a pre-written article stuck on it. Shit in, shit out.

It’s obvious that the speed and capability of the supercomputer is of secondary important to who controls the AI, and its access to data, and its freedom to draw its own conclusions.

(Read my blog on Fake AI:

You may recall a week or two ago that IBM released a new face database to try to address bias in AI face recognition systems. Many other kinds of data could have biases for all sorts of reasons. At face value reducing bias is a good thing, but what exactly do we mean by that? Who decides what is biased and what is real? There are very many potential AI uses that are potentially sensitive, such as identifying criminals or distinguishing traits that correlate with gender, sexuality, race, religion, or indeed any discernible difference. Are all deductions by the AI permissible, or are huge swathes of possible deductions not permitted because they might be politically unacceptable? Who controls the AI? Why? With what aims?

Many people have some degree of influence on  AI. Those who provide funding, equipment, theoreticians, those who design hardware, those who design the learning and training mechanisms, those who supply the data, those who censor or adjust data before letting the AI see it, those who design the interfaces, those who interpret and translate the results, those who decide which results are permissible and how to spin them, and publish them.

People are often impressed when a big powerful computer outputs results of massive amounts of processing. Outputs may often be used to control public opinion and government policy, to change laws, to alter balance of power in society, to create and destroy empires. AI will eventually make or influence most decisions of any consequence.

As AI techniques become more powerful, running on faster and better computers, we must always remember that golden rule: shit in, shit out. And we must always be suspicious of those who might have reason to influence an outcome.

Because who controls AI, controls the world.



Future AI: Turing multiplexing, air gels, hyper-neural nets

Just in time to make 2018 a bit less unproductive, I managed to wake in the middle of the night with another few inventions. I’m finishing the year on only a third as many as 2016 and 2017, but better than some years. And I quite like these new ones.

Gel computing is a very old idea of mine, and I’m surprised no company has started doing it yet. Air gel is different. My original used a suspension of processing particles in gel, and the idea was that the gel would hold the particles in fixed locations with good free line of sight to neighbor devices for inter-device optical comms, while acting also as a coolant.

Air gel uses the same idea of suspending particles, but does so by using ultrasound, standing waves holding the particles aloft. They would form a semi-gel I suppose, much softer. The intention is that they will be more easily movable than in a gel, and maybe rotate. I imagine using rotating magnetic fields to rotate them, and use that mechanism to implement different configurations of inter-device nets. That would be the first pillar of running multiple neural nets in the same space at the same time, using spin-based TDM (time division multiplexing), or synchronized space multiplexing if you prefer. If a device uses on board processing that is fast compared to the signal transmission time to other devices (the speed of light may be fast but can still be severely limiting for processing and comms), then having the ability to deal with processing associated with several other networks while awaiting a response allows a processing network to be multiplied up several times. A neural net could become a hyper-neural net.

Given that this is intended for mid-century AI, I’m also making the assumption that true TDM can also be used on each net, my second pillar. Signals would carry a stream of slots holding bits for each processing instance. Since this allows a Turing machine to implement many different processes in parallel, I decided to call it Turing multiplexing. Again, it helps alleviate the potential gulf between processing and communication times. Combining Turing and spin multiplexing would allow a single neural net to be multiplied up potentially thousands or millions of times – hyper-neurons seems as good a term as any.

The third pillar of this system is that the processing particles (each could contain a large number of neurons or other IT objects) could be energized and clocked using very high speed alternating EM fields – radio, microwaves, light, even x-rays. I don’t have any suggestions for processing mechanisms that might operate at such frequencies, though Pauli switches might work at lower speeds, using Pauli exclusion principle to link electron spin states to make switches. I believe early versions of spin cubits use a similar principle. I’m agnostic whether conventional Turing machine or quantum processing would be used, or any combination. In any case, it isn’t my problem, I suspect that future AIs will figure out the physics and invent the appropriate IT.

Processing devices operating at high speed could use a lot of energy and generate a lot of heat, and encouraging the system to lase by design would be a good way to cool it as well as powering it.

A processor using such mechanisms need not be bulky. I always assumed a yogurt pot size for my gel computer before and an air gel processor could be the same, about 100ml. That is enough to suspend a trillion particles with good line of sight for optical interconnections, and each connection could utilise up to millions of alternative wavelengths. Each wavelength could support many TDM channels and spinning the particles multiplies that up again. A UV laser clock/power source driving processors at 10^16Hz would certainly need to use high density multiplexing to make use of such a volume, with transmission distances up to 10cm (but most sub-mm) otherwise being a strongly limiting performance factor, but 10 million-fold WDM/TDM is attainable.

A trillion of these hyper-neurons using that multiplexing would act very effectively as 10 million trillion neurons, each operating at 10^16Hz processing speed. That’s quite a lot of zeros, 35 of them, and yet each hyperneuron could have connections to thousands of others in each of many physical configurations. It would be an obvious platform for supporting a large population of electronically immortal people and AIs who each want a billion replicas, and if it only occupies 100ml of space, the environmental footprint isn’t an issue.

It’s hard to know how to talk to a computer that operates like a brain, but is 10^22 times faster, but I’d suggest ‘Yes Boss’.




Universal Basic Income









Culture tax









Monopoly and diversity laws should surely apply to political views too













Thoughts on declining male intelligence






