Maybe we just parse a pattern in the light of a very broad generalization of human behavior. Perhaps early adopters are just early because they found out first. Perhaps it's only a rate-limited diffusive system, where identities are less important.

In the meantime, if I see a chasm I'll cross it.

Everything that came after is a derivation from the observations published in 1956, leading to the most famous one: "Crossing the Chasm".

Intuitively, the adoption cycle makes sense. That's what we've seen when Apple released the iPhone, or when every entrepreneur chases "early adopters".

There were many observations, from the size of the farms that adopted ideas earlier, to the level of education of the farmers. They also established that people preferred talking to neighbors rather than to sales representatives.

The first paragraph reads almost like a modern patent application 😂

Today, even if at a distance, I wanted to draw the attention on what is happening in my home country. Today, I would have been marching in the streets asking the government to step in and do their job responsibly.

By no means I am claiming that public universities in Argentina are perfect. Studying has a large opportunity cost which is not always accounted for. Graduation rates are highly demography-correlated. However, public universities, for me, are more that just beacon of hope.

Today, the intervention is done economically. The infamous "shock doctrine" has lead, in other places, to the complete replacement of public educational systems in favor of completely privatized ones. Accessible, of course, just to those who could afford them.

Public Universities in Argentina have survived many hardships, but they have nonetheless suffered them. In 1966, a government intervention of the university of Buenos Aires, led many professors and researchers to abandon the country. It took decades to recover from that exodus.

I am a strong believer in the crucial role that education has played and will keep playing for societies across the world. Access to quality education should not be based on economic status. We need a diverse leadership with diverse ideas to overcome future challenges.

I am looking forward to discussing with people who develop instrumentation software (either in Python or in other languages). I like learning from others' approaches and challenges ahead.
🔔 Drop me a line and let's connect!

Poor software leads to poor reproducibility.
But those topics are somewhat beyond my reach.

Still, the biggest bottleneck is that most instrumentation software is developed by PhD's in a rush to get things done and little oversight. We need to start giving software the same importance a lab journal has.

And the "View" is the tricky part, as always. Building GUI's is still daunting for many. I also believe that's the part were a good framework has the chances of creating the largest impact.

"Devices" become the first step on creating ownership, on laying out expectations. "Experiments" establish the procedural nature of experiments, from calibration to data acquisition and processing.

I am working on a slightly different approach: the Device-Experiment-View. In this case, the driver (what I called controller) is dropped from the spotlight. On the other hand, the relationship between experiments, devices, and views is systematized.

I am a big proponent of following clear design patterns to ease the onboarding of people. Induced by my web development hobbies, I proposed to follow the model-view-controller approach. But now I consider it outdated for instrumentation purposes.

One of the advantages of Python is that it has a low entry barrier. More and more people are developing software for controlling instruments.
In the past few years, the need to develop our own drivers decreased. Today, even companies like National Instruments and Hamamatsu provide Python drivers.