In The Crapper

In the Crapper

Have you ever had your mouth washed out?

I spent a lot of my time in fishing communities, and some of the language was “colorful”.
I recall one engineer after crushing his finger in a machine let go a string of non-repeating expletives that went on for several minutes, and seemed to me to be quite high up on the creativity scales.

On another occasion I was in a bar in Greymouth and a skipper came in after working on the engine of his vessel and someone asked how it was going – his reply was:
“The f*ck’n f*cker’s f*cked.”
I believe everyone in that bar knew both exactly what he meant, and exactly how he felt about it.

So language seems to me to be a very context sensitive thing.

How I talk when speaking to a ladies church group about environmental issues is very different from how I talk to a pub full of fishermen.

Provided I don’t get the two mixed up, it seems to work.

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Giving Thanks

November 25 – December 2 ’17 ~QofDay~ Giving Thanks

What are you giving thanks for these days?

Giving thanks doesn’t quite work for me.

Appreciation does.

I appreciate many things:
Family (William Jewelia, siblings, cousins, etc…..)
Life (evolution, ecosystems, etc)
All the amazing people and technology that surround me
Plate tectonics, mountains, earth (with its quakes and volcanoes, etc)
Computers and the internet, and what that makes possible
The possibility of global cooperation and global security
Every day I get to exist

So much exists, and so much more is possible.

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Tom’s Facebook post on Unity

Tom’s facebook post on Unity

Kinda, almost Tom.
We seem to be many levels of pattern – about 20 of them.
We seem to be based in matter, in the patterns of matter and energy within us, as well as the interactions with matter and energy outside of us. And matter flows through us, to sustain the general form of the many levels of patterns and structures that make us each what we are.

And yes – we have many levels of connectedness possible, and as the number of levels instantiated grows, the number of instances drops (both within individuals and populations).

And at many of those levels we are a very close approximation to pure information, instantiated within the information processing systems that are our physicality and our culture and our relationships with others.

And all systems require boundaries to maintain their form.

So it is a very complex set of complex systems we find ourselves in.

[followed by]

Hi Tom,

My “problem” is the nature of the properties available in any level of “system”. It seems clear from experiments at the level of Quantum Mechanics that at base this system we find ourselves in is a mix of the lawful and the random. QM seems to describe a system based in probabilities, where all possibilities allowed have an influence on the outcome, and as such the “outcomes” may only be “deterministic” in terms of probabilities (as the square of some vector in some “space” of dimensions).

As new levels of boundaries are instantiated, those boundaries allow for new levels of properties to emerge, which can be a recursive process. In us as human beings that process seems to have recursed about 20 times (varies somewhat between individuals). Some of those levels are more “material” than information, some more “informational” than material (and as with QM, I don’t see any hard boundary between such things, but they are useful heuristics to allow us to simplify something to the point it may be discussed with some sort of clarity).

So it is yes in a sense, in the sense that there is a degree of connectedness across all things, but that level of connectedness seems to be fairly well down the hierarchy of complexity.

When thinking about the complexity of emergent levels of systems, the interesting properties seem to relate to the nature of the boundaries present, how flexible they are in various dimensions (ideas like permeability and transmissibility, as well as ideas like deformation and resilience and absorption – across the spectra of matter and energy and information forms present).

Thus it is important to understand the sorts of minimum boundary requirements for the existence of certain classes of pattern, and that imposes certain limits on the notion of “unity”. In respect of any given class of pattern, one cannot push it past the minimum boundary set required to “contain” or “instantiate” that pattern.

I hope that makes my “Kinda” above a bit more clear – though it may not.

[followed by]

Hi Tom,

I think we be very much on the same page.

I see every distinction as a “trap” in a sense, as it tends to attract things which are similar, and classify them as same, to some degree.

In the sense of polarity being the bothness of the necessary complimentarity of the differentiation of anything, then yes – that sense must be present, and it need not be a single dimensional “thing”, it can become highly dimensional.

[followed by]

The reality for human beings is that we cannot deal with infinities, so we have to chunk them down to something useful.

For many – that means a binary in many cases – and there is a certain utility in that, in terms of the requirement of reality for us to make complex decisions in short times.

So for me, I accept a certain sense of my profound ignorance, a certain sense in which reality is unknowable, at the same time as I use the heuristics that I do to survive on a day to day basis.

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AI Arms Race

Artificial intelligence is now an arms race. What if the bad guys win?

Like others here have noted, the problem has been around a long time, and I for one have been thinking about it for over 40 years.

The most stable solution seems to be to change the context, and take it from being two sides, to a multifacet intersection of cooperative groups of cooperative individuals. In my understanding, the most powerful instantiation of that is distributed trust networks.

Some have tried using corporations and trade networks, yet the fact that market values are based in scarcity fundamentally undermines that approach when it intersects with the universal abundance possible from fully automated production.

So long as we frame the issue in terms of good and bad, we have lost.

As far as I can see, the only stable solutions have us all in this cooperative together. And that is a non-trivial set of issues.

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MILE – living a long time

Movement for Indefinite Life Extension

Scenario question – time travel to live a long time

Time seems to be a local phenomenon – thus time is travel not an option.

And I will do what it takes to generate the greatest probability of living the rest of eternity.
And I am clear that part of that is living a fundamentally cooperative life, where I value life and liberty universally. Thus compromising those values in the short term would destroy my long term probabilities, so isn’t an option.

So right now, building distributed trust networks, and working to put the amazing productive capacity we have from fully automated systems in the service of all humanity, to guarantee life and liberty, to the greatest degrees possible, would seem to be what is demanded.
And part of that is being responsible in both social and ecological contexts, as they are required components of life.

So it is a very complex system we find ourselves in.
Hard rules are not a viable option in complex adaptive systems, and there are necessary complex boundaries required to support any and all levels of complexity.

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Can computers keep getting faster?

November 8 – 15 ’17 ~ Computers

Can computers keep getting faster?

Short answer – yes, and long answer a lot more complicated.

There are limits imposed on particular technologies, by things like the speed of light, and switching speeds for types of switches, and there is a sense in which you can just keep adding more processors, and to the degree that problems can be broken into bits that can be worked on separately – that can help.

And maintaining coherence is an issue.

In classical von Neumann machines like this laptop I am using, the maximum clock speed is given by the time it takes light to travel along the maximum path between sub components, plus the time it takes a transistor to change states. So we are already seeing laptops with multiple “cores”, and the super computers all contain massive numbers of “cores”. Shrinking the size of components allows faster clock speeds, but also introduces heat dissipation issues. So it is a very complex topic. And there are all sorts of tricks, like creating temporary storage close to the processor, and having smart algorithms that guess what data and instructions will be needed, and “pre fetch” them into temporary storage before they are needed. So it isn’t just hardware issues, software plays an issue also, even within the operation of the machines themselves.

So the class of problems that can be solved by breaking them into bits that can be worked on more quickly can be sped up, but other classes of problems that require coherence across the entire system will reach real limits.

Artificial General Intelligence may be much faster than people, but not infinitely so.

Human beings will likely always be very efficient at solving certain classes of problems.

[followed by]


The thing about having infinitely dimensional distinction spaces, and infinite algorithm spaces, is that there need be no end.
No finite entity can explore any single infinity, let alone an infinite stack of them.

No one can know what they don’t know that they don’t know.

Novelty contains risk.
Risk mitigation requires allies and explorers.

As far as I can tell, the only solution to that problem which offers any significant probability of survival long term is cooperation.
And that alone is all one requires to derive ethics – when one is dealing with very long lived entities, with very good memories, that may have powers you know nothing about (infinite stacks of infinities allow such things – demand them actually).

It is a very interesting strategic environment.
A lot more interesting than von Neumann’s MAD (mutually assured destruction), though it was a powerful tool in its time, the space of problems is now much larger, and open.

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Errors and Risk

A tool to debug “black box” deep-learning neural networks

Researchers at Columbia and Lehigh universities have developed a method for error-checking the reasoning of the thousands or millions of neurons in unsupervised (self-taught) deep-learning neural networks, such as those used in self-driving cars.

All great in a sense, yet in another sense it perpetuates the myth that total security is possible.

I’m all for detecting and correcting failure modalities that can be identified, and that must be balanced against the fact that many real world problems are so difficult, that heuristics must be used in solving them, and all heuristics are subject to failure if their domain is exceeded. That applies at any level – always.

So we humans are good at solving some classes of really difficult problems because of the heuristics selected by evolution that are embedded in our biology and our culture. That is how it must be.

AIs can learn new sets of heuristics, and they will still be heuristics – the nature of the complexity present demands it.

So great work in doing what has been done, and great for going open source with it, and please be explicit that total security is impossible, which is not an excuse for being lazy, and it is an acceptance that no matter how diligent people are, and how smart we make systems, mistakes will happen.
And I am all for getting that error rate as low as we can; and I am being explicit that the idea that it will ever reach zero has no basis in reality or logic.
So uncertainty and tests for reasonableness would seem to be our eternal companions.

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