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Comment by strogonoff | Hacker News Reader

Are there many von-Neumann-like multidisciplinaries nowadays? It feels like unless one is razor sharp fully into one field one is not to be treated seriously by those who made careers in it (and who have the last word on it).

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IMO they do exist, but the popular attitude that it's not possible anymore is the issue, not a lack of genius. If everyone has a built in assumption that it can't happen anymore, then we will naturally prune away social pathways that enable it.

I think there are none. The world has gotten too complicated for that. It was early days in quantum physics, information theory, and computer science. I don’t think it is early days in anything that consequential anymore.

It’s the early days in a lot of fields, but they tend to be fiendishly difficult like molecular biology or neuroscience.

More than that, as professionals' career paths in fields develop, the organisations they work for specialize, becoming less amenable to the generalist. ('Why should we hire this mathematician who is also an expert in legal research? Their attention is probably divided, and meanwhile we have a 100% mathematician in the candidate pool fresh from an expensive dedicated PhD program with a growing family to feed.')

I'm obviously using the archetype of Leibniz here as an example but pick your favorite polymath.

Are they fiendishly difficult or do we just need a von Neumann to come along and do what he did for quantum mechanics to them?

Centuries ago, the limitation of most knowledge was the difficulty in discovery; once known, it was accessible to most scholars. Take Calculus, which is taught in every high school in America. The problem is, we're getting to a point where new fields are built on such extreme requirements, that even the known knowledge is extremely hard for talented university students to learn, let alone what is required to discover and advance that field. Until we are able to augment human intelligence, the days of the polymath advancing multiple fields are mostly over. I would also argue that the standards for peer reviewed whitepapers and obtaining PhDs has significantly dropped (due to the incentive structure to spam as many papers as possible), which is only hurting the advancement of knowledge.

Sounds like the increased difficulty could be addressed with new models and right abstraction layers. E.g., there’s incredible complexity in modern computing, but you don’t need to know assembly in order build a Web app, to reason about architecture, to operate functional paradigms, etc. However, this doesn’t seem to happen in natural sciences. I wonder if adopting better models runs into the gatekeepers protecting their status, tenures, and status quo.

Of course it happens in natural sciences. The neuroscientist doesn't need to to quantum mechanical calculations to do research.

Neither does a Web app developer need to know how to use CNC or make a transistor. Your example is about different levels of abstraction than what I meant.

I was replying to “even the known knowledge is extremely hard for talented university students to learn”. If complexity of the known knowledge one must learn to substantially contribute is the reason becoming an accomplished multidisciplinary is impossible nowadays, then it sounds like we could use some better models and levels of abstraction.

There have been a very small number of thinkers as publicly accomplished as von Neumann ever. One other who comes to mind is Carl F. Gauss.

Is it fair to say that the number of publicly accomplished multidisciplinaries alive at a particular moment is not rising as it may be expected, proportionally to the total number of suitably educated people?

Euler.

JVM was one of the smartest ever, but Euler was there centuries before and shows up in so many places.

If I had a Time Machine I'd love to get those two together for a stiff drink and a banter.

Genius Edward Teller Describes 1950s Genius John Von Neumann

https://youtu.be/Oh31I1F2vds?t=189 Describes Von Neumann's final days struggle when he couldn't think. Thinking, an activity which he loved the most.

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