Ask HN: What can I do to accelerate scientific research?

Efficiency is often compromised institutionally, so I know this is an obstacle.

I've got a lifetime of business models for scientific software, but that wasn't the question above.

One way to accelerate many types of laboratory research would be to offer a workflow alternative where very high performance individuals can make the choice to spend almost all their working time at the bench(es) rather than being distracted or sitting down at desks or office & lab computers. While maintaining overall leadership of the organization, so this requires a different type of team structure as it scales.

That way someone who can really invent a lot doesn't get bogged down by the bureaucracy of their earlier inventions.

I wouldn't recommend it for everyone seeking commercialization because of accompanying roadblocks due to the systematic financial pressure against individuals coming from survival conditions.

But it is good knowing what this gear can really do.

I think one of the biggest impediment to acceleration of scientific research is writing research papers the way they are written now. I write this with a perspective gained from roughly reading 1-5 papers thoroughly a month, scan 1-10 papers per week as a part of my work as AI engineer.

I cannot emphasize more on how much garbage I have to ignore (even in good papers) and arduously search for the bottom line statements being made by the authors. No wonder, people (at least ones I know including some professors and researchers) just want to see if the code or related materials were published on GitHub and go directly to it. Sometimes scan through Paper Review website.

One improvement I suggest is -- write two separate papers

1. First one, makes succinct points, explain the mathematics / system design, results following some broad set of formatting guidelines. This paper could only be studied by someone who understands the vocabulary used in the field.

2. Write another paper explaining the background and inference of results etc. Someone with no expert knowledge could make efforts to understand that.

If the thing could have been written in rust in the first place, tons of time would have been saved on trying to optimize python, waiting for simulations to complete before (and to a lesser extent after) I ported a portion of it to rust. Dealing with language interop and build systems.

The main reason I can't suggest that for future similar problems to the person who I did this for is because of the lack of libraries like plotting (plotting is by far the most important one, numpy is second but rust comes a lot closer in that regard).