outside


if you're a man
and feeling that you're touched
from inside

you are dead

it's a sword
or a knife
or a tumor just arrived
or a broken bone
around your heart

for men
the joy is outside

so keep out
and lightly play
from your side

unlike women
we can never know both sides.

My Data, Your Algorithm

 

Vacheron Constantin Calibre 3750, the most complicated watch in the world. 

I was skimming the future of jobs report by WEF which was released in October 2020. Like most of the WEF reports, it is lucid and comprehensive. I strongly recommend you to have a look if you have not done yet. 

My key take aways from the report are: 
  1. Data & AI jobs are increasing
  2. Cloud computing jobs are rising as well
  3. Information technology super cluster is being splitted to more specialized sub clusters such as Data & AI, Cloud Computing, Engineering etc. 
  4. For popular jobs in Data & AI family, there is a very big skill gap
  5. Critical thinking, problem solving and self management are the top desired professional skills 
If your professional activity is around software, cloud technology, data and AI; and if you are a good problem solver, you are going to have good news at least until 2025. Even under pandemic measures... However, notice the huge skill gaps emphasized in the report. Nothing is going to be so easy, you need to learn, develop, adapt new professional skills faster and faster, in a continuous manner.

Being a person who started programming computers by using Commodore 64 in early 90s and living on computers for more than 20 years, I am lucky enough to watch how software related industry has been evolving. So in this post, I am planning to touch a topic which is very important for me in terms of being aware of what data & AI professionals should consider.

In the good old days, when a software engineer was requried to build a system, the steps we all were following could be roughly listed as follows:
  1. Define the required outputs of the system
  2. Design the interaction model and process flow
  3. Design the data flow
  4. Design data structures
  5. Build the algorithms
  6. Integrate
When we were followig such a discipline, the systems developed and all the sub components were authentic entities in most of the times. The main difference in software development and data business is that nowadays, no one is developing authentic algorithms any more. The tendency is using the algorithms of others as much as possible. Software reuse, remote procedure call and fostering frameworks were always popular topics, even in the ancient times but today, through shared libraries and APIs, literally no one is developing algorithms. Therefore, no one is designing decent data structures. Flat data in, flat data out. And I find this strange.

Especially in analytical model development process, companies are only configuring the algorithms of others by using native company data. At the and of the process, the model developed is just another instance of the foreign function which was originated from the algorithms of some other company. It is like you impose your memories into the brain of somebody else.

In the traditional software development process, the meta equation is like below

Equation 1: INPUT + INTERACTION + ALGORITHM = OUTPUT

In analytical model development, more or less, the equation becomes the one below

Equation 2: INPUT + OUTPUT = ALGORITHM

Please remember that, ALGORITHM of equation 2 is just a re-configured form of the algorithm of others.

Let's analyze this a bit more. Chronologically thinking, all the company data we are to use for developing machine learning models were generated by the software systems, which were developed traditionally, for years. That means INPUT + OUTPUT part of equation 2 is coming from equation 1. Therefore, data have been shaped by the authentic algorithms and interaction models for many many years. Today, you are trying to have a look at the company data to extract a version of some one other's algorithmic function. Isn't it strange too? I think it is.

Moreover, the notion of algorithm itself is not sufficient enough to model real world because an algorithm is a closed symbolic system. It takes inputs, processes finite steps and produces outputs. However, life is composed of interactions. Many interactive computer systems, which contain different algorithms, are running simultaneously, generating many events, getting feedbacks, triggering other systems etc. This bigger interactive picture is not reducible to algorithms.

On the other hand, in most of the cases, analytical models are developed by using non-inteactive, low dimensional, batch, historic data. By using that form of historic data, some one other's algorithm is tried to be configured to handle real life situations. Where is the effect of interactions there? Of course, some analytical models are formed to analyze streaming data. There is a proximity in this area but even such models are trained by following the batch data load practices. The scope of the problems to be solved by using analytical models can be narrowed down to fit into the nature of real life situations. This may handle the shortcomings of non-interactive, pure algorithmic approach. But it deserves another discussion...    
  
To sum up, I have 2 questions:
  1. Can we survive unless we create our authectic algorithms?
  2. How can we add the interaction notion better to the analytical model develoment process?
One of my bosses, whom I respect a lot, were saying "build the clock". I think we should follow the advice.   

cumhuriyet

 

hayatı severken
yarın için heyecan duyarken
geleceği kurarken

hayatı ciddiye alırken
giyinirken
düşünürken
çalışırken

baskı altındayken
başarırken

özgür bir nefes alıp
yanındakine omuz verirken

ve yalnızken

eğlenirken
öğrenirken

ezberleri unutup
tekrar öğrenirken

asla vazgeçmeyip
bıkmadan
yeniden
daha güzel yaparken

ilhamımız hep senden.

Tele-communication

 

First of all, I must say that I am not an expert on communication theory and I know that it is a very deep field of study that may take one’s years to accumulate enough knowledge. On the other hand, I intend to share my observations on how our corporate communication styles have been changing since “COVID-19 triggered the digitalization” of the enterprises, schools, governments etc.

To me, we are just carrying our communication rituals to digital environments. This is the spirit of nowadays. Technology is given and available, infrastructure is ready for years but mindsets are anchored to the 1980s. Therefore, we are only simulating something very old and hardwired in our daily lives in teleconferencing media.

To make things more concrete, it is enough to have a look at the basic observables of meetings around. Those were the days that we were meeting in a room with 7 people, now we are still meeting with 7 people in the digital rooms. The nature of the information exchange and hierarchy based communication forms are the same, as well. In the so called non-digital times, meetings were usually planned as one hour sessions, today we still follow that rule. Office assistants are still exist and interestingly still planning the managers’ meeting schedules. And they usually plan the famous one hour sessions by putting one after another without adding any moments to take a fresh breath between sessions. It is a perfect way to die digitally. I call it digitally archaic.

So what has changed?

Frankly speaking, I exaggerated a bit because we are not meeting with 7 people any more. We meet 77 people in the one hour “digital” sessions. Almost always, the breakdown of 77 is like 7 aces and 70 more listeners. When that proliferation of meeting attendees occurs, the communications in the meetings become a monologue or minimized dialog. In a usual picture, the moderator who is the organizer of the session transfers information to the most senior manager in the session. Manager listens, gives necessary directives to the moderator or to the 7 aces in the session. Others listen in a “muted” fashion. When you compare the number of the distinct communications and the variety of the communication directions between attendees of the meetings that were planned traditionally with 7 people in the old days and the 77 attendees meetings of nowadays, I'm sure you’d see no significant difference. But, what is the role of additional 70 people? Some says, it is very good not to be limited by the physical conditions of meeting rooms so that any one can join my session and get my messages directly and it reduces the risk of information loss during message dissemination. It seems correct. However, it is not that easy. To test it, call 10 of your colleagues and explain them a complicated situation directly in the same room. Then, check their notes taken. You will see the differences between the notes. It is expected because every person puts her interpretation into the notes taken, their vocabularies are different, level of personal know-hows are different etc. Without asked questions, given answers and active dialogues it is not possible to assure high quality information exchange during the meetings. I can say that additional muted 70 only fosters the one way communication that kills effective knowledge transfer. The bottom line is digital meetings are becoming large conferences where the wiser person speaks and the others passively listen. In other words, monologue which is not that revolutionary.

In contrary, I am expecting real model changes in every aspect of corporate communications. As I said at the beginning, I am far from building a future communication model for the enterprises but I can ask a few questions:

Why don’t only 2 persons meet every time they need information exchange?

Why cannot those sessions last less or more than magical one hour?

Why corporate communication picture cannot be the set of those necessary 2 people meetings?

Why don’t we stop calling those sessions as “meetings” and give them a new name?

“I have a dialogue with Jane at 9 am.”

“Let’s arrange a dialogue after lunch.”

Why don’t we stop PowerPointing?

Why can’t we build our own schedule?

Why can’t we run multiple micro sessions at the same time?

Why don’t we stop taking screenshots of crowded Zoom meetings to share them in LinkedIn?

Why cannot we re-define?

I know we can, just a little more time.  


sur

cesur bir adım gibisi yoktur
o anda biraz ölürsün
ayakta kalacak kadar yaşarsın
kirli nefesi verirsin
kime afyon olacak bilirsin
biraz daha değişip
bir gram hafiflersin

cesur bir kaçış gibisi yoktur
bütün evreni tersten inşa edersin
aynayı nereye koyarsan
ardındaki duvarı yok edersin.

feeling

you sit down somewhere
with your heart fresh

maybe a train
maybe a cosy corner of
where you're dining

after you took care of everything
feeling satisfied
not saturated
there's still room for extra pleasing

you're at the table
comfortably handling
your small thing
dark
wood
red
walls
smoky 
light 
sneaks
in.

can

herhalde
o zaman geldiğinde
kim olsa yabancılık çeker

çocuklar
kitaplar
müzikler
dolapta katlanmış düzenler
bildik, küçük yemekler
evim, yuvam, köşem dediğin yerler
devam etsin istersin
bildik, küçük hisler

kim bilir
o zaman geldiğinde
can kuşu nereye gider...

sana ait olur mu senden kalan sensiz izler.