Recipetips: Neuroscientist Brian Nosek on the Most Important Scientific and Technological Mutations of the Past Decade

Recipetips: Neuroscientist Brian Nosek on the Most Important Scientific and Technological Mutations of the Past Decade

Recipetips: Neuroscientist Brian Nosek on the Most Important Scientific and Technological Mutations of the Past Decade

Perhaps that intellectual leap isn’t just a state of mind. It can be supported by scientific evidence, too. At least in research from the University of Pennsylvania, it turns out that some of the most interesting and important innovations in technological advancement have been of the brain variety: those conjured up by those who think in terms of meta-systems and corresponding frameworks. According to neuroscientist and School of Engineering professor Brian Nosek, this meta-system paradigm is both intellectually enduring and emotionally potent.

We asked him for a list of the most important scientific and technological leaps of the past hundred years, based on research and theory that created a new field, for example, or inspired a new creative idea. Turns out that some of the biggest breakthroughs in the computing world—such as the notion of “programming,” and what may today be known as “big data”—are organized in ways we can understand and apply ourselves.

In order, here’s Nosek’s list of the most important scientific and technological leaps of the past century (in no particular order):

1. Programming. “There’s an important difference between basic programming and a master program. When a computer is programmed, the program’s author has to interpret the program, because it doesn’t communicate any external inputs like music or numbers. The programs that have really changed the way we live are the ones we’ve been programming [for years], like the structure of words or the programming tools on the spreadsheet that we use to log orders and repay debts. Those are standards we can understand very abstractly, and we can extrapolate from them in certain ways. For the first time, we have a set of tools that you can use to program an infinite number of models that are interconnected to further the plot. The computer is capable of transmitting this idea of scale.”

2. Hacking. “When I think of what inspired me to actually write this article, I think of the work of Josef Skvorecky. Skvorecky worked for [inventor Henry] Watson, and he had a head of fields and had had a series of successful hacks on those systems. Skvorecky was the most aggressive hacker of all time, and he was doing this from the edge of the system; he was essentially hacking without permission, and sometimes without getting the permission. For that, he was very frequently terminated by Watson, who was IBM. In The Computer Instinct, Gil Amelio describes Skvorecky as ‘bugging Watson to death,’ a role he later took over.”

3. Synthesis Theory. “Algorithms are built to accommodate individual variable effects. In practice, we might think of that as making applications do more of the same thing, whereas when we think of a computer, we think about a more holistic approach. Part of the rethinking on algorithms in recent years has been about how computation becomes automated and not just systematic, using machine learning and deep-learning techniques. Synthesis Theory is a collaborative framework for how these algorithms model the world around us, and what we use the digital world for. That starts with the fundamentals of programming. And then one can draw predictive inferences out of that.”

4. Quantum Mechanics. “Quantum mechanics and theory have paved the way for a rethinking of sorts for the way we think about our own simulation, on this microscopic level. Those two things interact. As a philosopher, I think about things like consciousness being linked to a form of simulation within a specific form of simulation, and that simulation becomes the larger continuum of consciousness. There’s a way that QML theory plays a role in helping us to distill complexity.”

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