a device that is generating concepts

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Skills network

Anything related can be a network. Any network got a hidden magic inside. Building a network is unleashing another part of the beauty of this world. And when you do this, when you find the secret clusters, when you connect the lonely entities of existence – then this magic is flowing though this network, enlightening and reviving nodes, breaking out over the invisible strings into the life, connecting everything and everyone.

Our skills are shaped by the templates of education and jobs, by human behaviors and to get a glimpse of this bias we can do a simple experiment.

Let’s build s crawler that is getting LinkedIn skills from many people, connect those skills based on cross-correlation and build a network that is based on highly correlated skills.

Even small amount of people I took (about 150), is giving a network of over 400 correlated skills, connected by 3500 links and lots of interesting insights.


So… Mainly pics and less words.

Parts of the network, related to declared programming language-based networks (per language). Pay attention on differences:languages

Design (Since this is a small network, it is biased by my occupation, so the design is mainly represented by word of semiconductors – doing it widely would expose other meanings of design):


…with zoom-in on SOC (System On Chip) skills network (pay attention on lack of connection between “microprocessors” and “dsp”  skills. hhhhh…) :soc

Declared Skills, related to “Microsoft”:microsoft

This one is coming from my MBA friends (“Merges” as an anchor):


Hmm… Interesting positioning for Leadership skill:Leadership

Strategy cluster:


Those are just several examples, but the applications of this network are giving a big potential value. Amazing HR models and mode of work, Personal effective definition of skills and positioning… It can take the LinkedIn to a whole new level.

And as usually – Do not forget to Enjoy Your Life!

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Annual Feedback quantitative analysis

Yes, I am more than 10 years in Intel Electronics and every year I’ve got the annual feedback (called “Focal”). I thought to look at the nature of the work that I am doing by analyzing the semantic data of those documents. From confidentiality reasons I cannot bring parts of it here, but I can show you some quantitative analysis that I ran on the data.

Among various perspectives, I wanted to look at the verbs that are used there to describe my accomplishments (one out of three components together with “strength” and “areas for improvement”). Out of 30 paragraphs (3 each year) and 4.1k words in total, here is the distribution of all top verbs (overall about 200):


The thought was that verbs of accomplishments are the nature of the work. Now, when I look at it, the direction is amazingly correct – this is what I actually did.

Taking “worked” as a baseline (100%), I have calculated the rate for the rest of verbs relatively.

In addition, grouping verbs by their nature (excluding neutral “worked”), I can tell now, precisely how my work looks like:

nature of work

Know yourself. 🙂


Cellular Automata in excel

Had some time recently while flying from one place to another and played with simple Cellular Automata rules in excel. It is very simple to do – you create a rule within the cell as function of other cells and extend it (you can simply copy/paste) to other cells.


Here, if A2 is equal to B1, we define a value within the cell “Set”, otherwise it remains empty. That’s all.

Now, if we will keep the first row and column empty (let’s call them “boundaries”), while extending the rule to bigger area, we are going to get a beautiful pattern:


Here I took the area of 200×200

The size of the “triangles” are recursive 2N+1 (1,3,7,15,31,63…)

So by very simple rule we have created pretty complex pattern

Now what is interesting that by simple change of the reference cell the pattern complexity can dramatically increase.

If we change the “offset” of the reference cell by one i.e. apply this kind of rule:


We will get the next pattern:


Continue reading

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Network of physical quantities

Had couple of evenings of fever 😦

Took International System of Units (SI units) as a baseline and created a network:



Nodes – Physical Quantities. Size of Node is based on OutDegree Ranking (kind of “Importance”). Colors are based on Subject:


Edges – relation based on Units, expressed in terms of other SI units. Color is based on relation (Blue – multiplier, Red – divider). Width/weight is based on power (log).

Gephi layout – “Force Atlas 2”

You can see that most “important” Physical quantities are basic Length, Mass, Time, but also derived Force and Energy.

Taking a look at the Betweenness Centrality, we can see that Force and Energy are the biggest and then Voltage, Resistance and Charge. Maybe this is why it is so native to learn them first right after the basic physical quantities.

betweenness centrality

Enjoy and feel free to download, modify and correct (surely got some mistakes). If you do, please mention the source 😉

Files: Excel/Gephi

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Annual pattern of Demand for Laptops

As I am working on analysis of Lenovo company (hobby/investment), here is an interesting chart out of the work.

Beautiful pattern of demand for Laptops (relative demand per week, comparing to an annual average of demand) during the last decade:

Demand for Laptops - annual pattern

The pattern is very precise and stable since 2004 during most of the year except maybe some end of the year behavior inconsistency. Though there are expected two peaks of demand at winter holidays, year-to-year  variance during ww48 to ww52 is still high. Extremely high peaks at 2007 holidays, driven by Intel Core 2 Duo products wave.

You can see a clear back-to-school growth towards August from the (-10%) dead-season of Laptops marketing at Spring.

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Annual pattern of jobs searching

Are you looking for a job? Most probably this is not a coincidence. Eventually there is a clear annual pattern in amount of people searching for new opportunities.

Here is a normalized relative pattern of amount of people searching for a jobs for a last decade.

Data is based on worldwide statistics based on millions of people and can be used as a model for Human Resource organizations, headhunters or just people that are part of the trend.

X-axis is weeks (1-52), Y-axis is growth in jobs hunting comparing to the average of the year.

X-axis is weeks (1-52), Y-axis is growth in jobs hunting comparing to the average of the year.

We see a nice and clear behavioral pattern that shows a gradual decline throughout the autumn to the annual minimum of job searches by the end of the year and the slight spike before holidays (people that remind that they need money for presents?). Then enormous spike to the annual maximum at the beginning of the year (motivation to change things in the new year? worldwide layoffs pattern?) and then spring decline followed by growth to a summer “hill”.

Same, but with average profile (Rsq > 0.8):

WW Job Search Profile

What can I say? In my company this profile would be one of base components of HR organization budget. I find it cool.

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Ropes and the Perception of Risk

Couple days ago I had an amazing experience at Kos Island (Greece) and tried a ropes course, where I had to pass through all the stages of the cool facility, going from one column to another over the ropes and bricks with increasing complexity. It looked like this:


Six phases x three wings x two levels i.e. 36 stages of fun and challenge for my equilibrium. Beyond the unique experience, I learned something very interesting from the instructor (on the pic above, he is at the middle stage, waiting for me).

After I have passed several stages, he said to me: “You know that there are three points of support, required for equilibrium here. One is the left leg, another is right leg, while the third is usually the hand.” Indeed, I have mentioned that to feel stable, I had to hold the rope (or anything else available) with (at least 🙂 one hand. “BUT the interesting part is that you DO NOT HAVE TO HOLD the rope. It is enough just TO TOUCH it. Even slightly with the side of the finger”. Obviously I have tried it and it was amazing! I could relatively freely walk while tip of the finger was touching the rope, and at the same time I could not walk from the moment after it was detached. So for me it was no more the holding rope, but just the reference point.

Immediately as an engineer I thought about the negative feedback that my brain required to do this task, I thought about sensing lines from power electronics, I thought about feedback in control system of my brain, I thought about continuity of nerve that is running from my finger to some place in the brain and realized that this third point, required for the equilibrium was not actually the finger itself, but that place in the brain that required this sensing for better control of my body.

Now I need to distinguish my experience from a single line “Tightrope walking” (funambulism) or slacklining where there are a totally different biomechanics and brain control of the balance.


I am talking about purely psychological effect of the fear of the failure where you can “easily” go at the height of half a meter and make not a single step at fifty meters. I am talking about effect that you slowly go two thirds of the path and then run freely when you see the end.

This was very much related to the work I am doing these days on Risk Modeling in Complex Systems generally and on Perception of Risk particularly. I shall release some interesting parts of the work here… By now, to touch the Perception of Risk model, I would like to mention two major components of the risk – Perception of the probability of failure and Perception of the impact of failure. Each of those components got multiple assessment biases and this is a whole separate talk by itself. In this case of equilibrium reference point, the signal in the brain was impacting the part, responsible for mitigation of the failure probability component of risk perception, since the impact of the failure was same. The mitigation was possible because of the constant signal to my brain that in case of loss of balance, would ensure that the hand is very close to the rope to catch it. If this is true, then the brain mapping (if it is going one day possible not in static lab conditions) of walking person at the same height with and without the finger touched, would show the area of brain that is responsible for the Perception of Probability component of risk, while the different heights would expose the area responsible for the Perception of the Failure Impact.

Interesting that once I passed some stage the second time it was much simpler to detach the finger and in some cases even not use the hand at all and stretch out my arms to increase the moment of inertia for better balance. It was nearly impossible for me to do it for the first time per stage due to the lack of risk assessment and perceptional bias (a.k.a. fear)))).