Flaws in modern AI paradigm

We’re not mature in full understanding.

Number of natural neural networks vastly outnumber artificial ones.

Benefit in numbers, different training and different design.

Latest understood brain dynamics, in order to react quickly have a stable-unstable system and fail to correct in the direction you want to go.

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A developer taxonomy

Ars totally nails the definition of development

A developer taxonomy

At one level, you have people who are basically business analysts; they’re using Access or Excel or VB6 to write data analyzing/number crunching applications. These things are hugely important in the business world, totally unexciting to anyone else, and the people writing them aren’t really “programmers.” I mean, they are, in the sense that they’re writing programs, but they’re not especially interested in programming or anything like that. They don’t really care about the quality of the libraries and tools they’re using; they just want something simple enough that they can pick it up without too much difficulty. They’ll never write the best code or the best programs in the world; they won’t be elegant or well-structured or pretty to look at. But they’ll work. Historically, as I said, these are the kind of people who Access is made for. Access is a great tool, quite unparalleled. Sure, it’s a lousy database engine with a hideous programming language, but the power it gives these people is immense. So Access and VB6 and Excel macros are where it’s at for these guys.

At the next level, you have the journeyman developers. Now these people aren’t “business” people—they are proper programmers. But it’s just a job, and they’ll tend to stick with what they know rather than try to do something better. They might be a bit more discerning about their tools than the business types, but they’re not going to go out of their way to pick up new skills and learn new things. They might use VB6 or Java or C# or whatever; it doesn’t really matter to them, as they’ll use whatever offers them the best employment opportunities at any given moment. Their code will probably look more or less the same no matter what. They’re not going to learn the idioms of whatever specific language they’re using, because there’s no need, so it’s just not for them.

A key feature of these developers is that, most of the time, they’re writing “enterprise” software. This isn’t software that will sit on a shelf in a store for someone to buy; it’s custom applications to assist with some business process or other. Truth be told, it probably won’t have to look very nice or work very well; it just has to get the job done. With “enterprise” software, you can often get away with a clunky program, because the people who are using it have all been trained on what to do. If doing X makes the application crash, that’s okay—they can just be taught not to do X any more.

In spite of the often mediocre quality of the software these people write, they’re a group that’s immensely important to Microsoft. These programs are a key part of the platform lock-in that Microsoft craves. If a company has some business-critical custom application written in Visual Basic 6, that company isn’t going to roll out Linux to its desktops; it’s trapped on Windows.

At the final level, you have the conscientious developers. These are people who care about what they’re doing. They might be writing business apps somewhere (although they probably hate it, unless they are on a team of like-minded individuals) but, probably more likely, they’re writing programs in their own time. They want to learn about what’s cool and new; they want to do the right thing on their platforms; they want to learn new techniques and better solutions to existing problems. They might be using unusual development platforms, or they might be using C++, but they’ll be writing good code that’s appropriate to their tools. They’ll heed UI guidelines (and only break them when appropriate); they’ll use new features that the platform has to offer; they’ll push things to the limit. In a good way, of course.

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Where is the intelligence in AI

Intelligence = abstract thinking

See related https://arstechnica.com/information-technology/2017/09/digital-transformation-3/

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Life, consciousness and belief

A few ramblings…


Real life is abstract thinking represented by continuous consciousness, it’s definitely a long way off stacked machine learning which we consider AI currently. Just look at the flexibility of the human brain – change the stimulus and its able to rapidly adapt and reform the same constructs. However if you ever sleep or pass out, effectively the continuous stream of conciseness has been lost, does this mean you die? depends on you definition, but if it’s continuous stream of consciousness then certainly yes. Imagine you cloned or teleported your body multiple times, would each body think it was unique and think it was the same person – almost definitely yes, hence why each consciousness is disconnected – if you sleep you effectively die.


Given that we sleep, does this mean that consciousness is fragile or takes a lot of effort to sustain, yes, but I don’t believe that consciousness is unstable and cannot be sustained within our own human bodies. I believe the lack of continuity is actually a great benefit, to prevent us getting stuck in loops and to give us a lot of resets – hence keeping us reliable and in perspective.


Motivations? I believe always true and need to take everything that comes out with a pinch of salt as does not reflect thinking, but what understanding of what can or should be said given environment – change the environment / stimulus and you can expect different response, but thinking will be constant – you cannot determine thinking from one stimulus

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What re-enforced knowledge and politics can teach us to help make better AI

Re-enforced knowledge – when you have a belief that gets questioned, you seek out a fact that helps re-enforce your own belief rather than consider the fact that caused you to question your belief in the first place (the Google effect through easy access to ‘facts’).

Neural networks follow this pattern, and rely on  volume of information, not intelligence to train them (see microsoft’s experimental twitter fail).

What’s needed is a process to look at sanity of what they are learning and pick the right input and check the output.

The output can be tested from the real environment  (multiple neural networks, with application of natural selection).

Dividing the input up to feed the neural networks properly is the difficult bit.

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Fastest way to count…

Improved method of counting large numbers of objects just occurred to me…

Pick the centre one visually (skip this step if there’s no symmetry), then count the number of groups you can easily count visually to the edge (I.e. count numbers of pairs or groups of five etc.)

Then double your edge number and add one for the central one.

Selecting the central item half’s the amount of counting you need to do, and our brains are pretty good at identifying this visually.

By counting visually in groups your brain has less back and forth between your visual and mental arithmetic.

This works great if you are counting something that’s rapidly moving and you want to identify size!

The counting in groups is how my grandmother used to count sheep really quickly on their farm near Theniet El Abed, Algeria, but the symmetry bit is my contribution ☺

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Vedic astrology and the science of cycles and macro influence

Vedic astrology, derived from very meticulous observation of the world around us, including ourselves, earth and the planets. The cycle of life, especially the earth and the planets is actually extremely regular. This has a big impact over millions of years.

Influence of the planets is very small on us (influence of Jupiter is 10 000 000 less than anything here on earth [maths]). This probably gets drowned out.

However Jupiter does have a small bug significant influence on earth and earth has a very significant influence on our selves.

Do butterfly wings – influence weather, not really unless you have thousands in a regular cycle – evaluation of small vs large

Actually small effect can have an influence over a large time, but there comes a point where the noise in the big impacts drowns out the noise of the small impacts?

Effect x time = impact

But that doesn’t answer Vedic astrology and how it can tell what happens in those cycles. Is there some commonality between the cycles of life.

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Can you break your brain’s programming?

Our brains consist of a massive neural network. Used to react, adapt and learn from our environment.

But what about our consciousness, is it merely a result of these pathways, is what I’m writing now driven purely by that? Continue reading

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Psychological evolution – why we all do what we do, the motivation of life

Think for a moment, if you were born in to a world on your own, who would you be?

An interesting question that requires some thought, and I think the answer is difficult to remove from expectations that we’ve been set as a child.

Continue reading

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The boundary theorem

Everything develops around boundaries. One of the most prominent is life.

Consider that life is found mostly in the boundaries between different environments.

Boundaries represent change, mixing, and are catalysts for new things.

Our brain is a neural network that learns patterns and takes the change around us and turns it in to a normalised constant.

What our consciousness does is then take that constant and present a user friendly version, summarised as the change relative to the norm learned by our neural networks – it constantly leads the edge.


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