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.
📉 #DidYouKnow that the technology adoption life cycle is the result of studying US-farmers' behavior in the 1950s?
Although it has been popularized as a bell, the original work actually shows the cumulative distribution over time, a much more powerful visualization, if you ask me.
🗒️ The pitch deck is not the company. The pitch deck is one of the marketing materials a company uses to sell a product: itself.
In many cases, pitch decks have come to replace written business plans. They are easier to digest, quicker to consume.
One book I regret not reading before starting my #scipreneur journey: "The Founder's Dilemmas". It's a perfect mix of statistical analysis and annecdotal evidence.
I could have avoided falling into so many pitfalls if I would have known about it before...
Harrowing but entirely unsurprising analysis on the prevalence of bullying & harassment in these science fields. All data pointing to how marginalised groups experiencing these epidemic proportions of bad behaviours at work. The data is so striking, but will it lead to meaningful change?🧪
Are you a #scipreneur and would like to get a free pitch deck review? I'm opening up few slots in my calendar for the firsts who send the form
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.
Today, Argentina will wake up to a massive demonstration by public universities. The current government is destroying the funding of many sectors backed by the state (pensions, education, infrastructure, research).
They are implementing the disastrous "shock doctrine", in the hope of what?
"Failure at every level", that's the conclusion of the case against Raoult, a shady scientist in a prominent French institution.
www.science.org/content/arti...
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.
📚 I'm reviewing my book, Python for the Lab, adding plenty of insights I gained during the years since I published it. The community has grown, and companies have payed attention, but there's a long road ahead:
Misconception 3: you need someone with business experience to start the #scipreneur journey.
🗽 Misconception 3: you need someone with business experience to start the #scipreneur journey.
"Business experience" is not rocket science, it's something that accumulates through exposure to given practices.
🤷🏽♂️ Have you ever experienced decision fatigue? I know I have. At some point you can't keep up, and the inability to choose hinders the performance of your team.
When a #scipreneur starts a new venture, there are a lot of decisions to be made.
I have to confess that I'm a fan of e-mail (especially with PGP encryption and singing), and could never get used to Slack-type of chats. I found Notion an amazing tool for team work in written (and unstructured) format.
Do you work in a team that is used to writing? What tools do you use?
I like having meetings where there was some written exchange beforehand. Then the meeting can be focused at resolving and deciding, but it'll never be "I should look for that information and come back to you next week." It's harder to be unprepared for such meetings.
It also allows for an async form of creative thinking, since I can focus on what was written on my own terms, and can reply consciously pondering alternatives.
And since what we write stays on record for a while, people are a bit more cautious about what they are saying, and how they are saying it.
