De what we all want at work

Spoiler: whatever is our trade, we all crave for novelty and complexity: to do it if possible, to study it otherwise. But we almost never get to do it.

Immunovirologists are interested in working the deadliest virus on Earth, yet they likely get a job working on allergies.

Architects are interested in building the crazyest building, yet they likely get a job designing the most boring building.

Artificial intelligence scientists want to create confusingly smart algorithms, yet they get to do teaching or project management first and software engineering second.

Computer security experts are interest in studying and attacking the hardest networks, yet they got to do consulting selling useless product and services to clueless consumers.

Software engineers are interested in doing some algorithmics, yet they got to do just simple and boring coding.

De how to invest in R&D

Money is the nerve of war - imperial wars.

Motivation is the nerve of war - partisan wars.

Same applies to economy, the real economy.

Large companies have the power to invest swaths of money and get little for it. 

Small companies led by passionate people could with little money create real value.

The issue are that:

- large company have too much money and not enough ideas -> they tend to invest in many wrong (because unsuccessful) directions, hopping for the best, i.e. that what they were working on takes off almost inexplicably.

- small companies, even individual, have more motivation than means -> they tend to work in one unique direction, the one they hardcore believe in, and as such are not rational. However, they might strike gold, because they are actually doing.

Both act irrationally, but there is a way to combine rationaly both: for large companies to buy small companies or individual and give them means.

And that's what happens.

I don't speak about buying sucesful startups like youtube, flickr, snapchat.

I speak about buying unknown companies or individuals that have little to show for.

There is a whole business in that. But this works properly not microcredit styles. It works strong backing style. If you put too much pressure on paying bills, you'll burn the usefull effort and time of people in useless stuff. If you want a solid product, you have to give a solid backing, without conditions. Just empower people by giving them the responsabilites of working for themselves - not a picky manager.

Because, at the end of the day, large companies manage many bullshit products most of which die, and real work gets done by passionate people that have their feet on the ground, project and management of little to do with it. The only thing that is needed in a project is the cash to develop something.

Same with individuals and small companies: you only do go work when you believe in what you do. And individual know more closely than large companies what works: because they are end users they know their needs. They don't need market studies, they are the market. Layers of hierarchy is an hindrance.

So for R&D tasks, hire normally talented and widely passionate people, they do the real stuff. You'll get much more from them than from people who work for money - and they are in much greater availability than highly talented ones. Work is about money only when you have no interest in what you do, otherwise you could do it for free.

Give R&D staff cash an freedom, and they'll do great stuff. Better invest 1 million in 8 yp than in 1 preventive patent.

Climbing the hierarchy ladder gives you more money, but also there it is mainly for the pleasure of being in command (to say the least) that drives people. That's why CEO guys for whom work is a passion can not understand regular employees for whom work is a hassle.

Anyway, the more money you pay an employee, the less life looks like a script and the more life looks like a game where you have the upper hand over it, therefore the more enjoying it is, and an happy employee is a productive one. So raise the salaries to raise the profits.

Mathematical Notations are Hell

The problem with mathematics is simple: notations. It make everything hard. Specially for the student that freshly joins the university and has to deal with a lot of similar yet incompatible notations and corresponding way of thinking. There are a lot of loosely defined conventions (when not an article's author ones) that make understanding mathematical text .

For instance:
f: is it a function, is it a scalar?
a: is it a function, is it a scalar?

What a strange notation system where letter of item of the same set have implictly different type, unless explicitly stated otherwise.

For instance:
f: should be a function
a: should be a scalar, or a vector
m : shoud be an integer index

if the value of the character is so important to its type then why changing case, changes types, but in unrelated and incompatible ways?

For instance:

F: integral of f
F: set named F
F: function named F
A : matrix
A : vector
A : set
M : matrix (and only a matrix)

What a strange notation system, where a space and lack of it have a signification?

For instance:
aa = a*a
a a = a*a

What a strange notation system where symbols have very different meanings:

For instance, what do you read here?

f(a) : apply the function f with the parameter a
f(a) : multiply the scalar f with scalar a
f(a) : multiply scalar f with vector a

f^a : scalar f to the power a
f^a : function f in a set of family of functions indexed by a?
f^a : scalar noted f^a

What a strange language where the semantics of operation can change:

For instance:

f(a) : apply the function f with argument a
f(a) : declare a predicate f for argument a
f(a) = : define the value of f for a variable called a (unbound variable, ie generic)
f(a) = : define the value of f for a value called a (bound variable, ie given)

Maths are hard to understand because mathematical notation are notation, they are not a language. Which means that with every field, subfield and individual research paper tou have to learn from scratch what the scrible you read mean.

In a sens they are a spreceise a writing "todo: buy stuff" on piece of paper: when you'll read it you'll have to struggle a lot to understand what the author meant.

That's too bad to crush the opportunity of the masses to understand an use mathematics on the whim of using notations. Like the dreadful conventional direction of current in electrical engineering... which is like calling a fish a pig an then trying to understand how do pig swim.


A great source of confusion come from the fact that sometimes letter denote vectors rather than scalar, and operations apply differently to them. Because summation and combination operations are implicit, it makes it more difficult to understand. For instance when considering matrices, it is important to know it it is a product or a tensorial product that is applied.

When multiplying two letters, possibly:
- we multiply a vector by a scalar which yields a vector,
- we multiply a line vector by a column vector, which yields a scalar
- we multiply a column vector by a line vector, which is an error
- we multiply a matrix and a vectors,  or a matrix and a scalar, etc.