The most important scientific problems have yet to be solved (1897)
thereader.mitpress.mit.edu
thereader.mitpress.mit.edu
A few years after this was written, Planck proposed energy quanta. And in 1905, Einstein published his four Annus Mirabilis papers, introducing the photoelectric effect (applying quantum), special relativity, and the mass-energy relationship.
https://www.amazon.com/End-Science-Knowledge-Twilight-Scient...
and that most remaining science is just find of filling in the tiny bits.
I personally don't expect anything that will change with respect to backwards time travel or faster than light travel.
For the first two, we'd need to have a radically different physics than the current model, while the last two, they seem like reasonable extrapolations from modern technology.
(based on my understanding of transistors, the first ones were conceived before the theory for them existed, and the first ones were built around the same time the quantum theory for them was expressed).
Who knows, maybe we'll find that we actually are living in a simulation and then figure out how to hack the matrix. The idea of "travel" and "time" would become obsolete then; you'd just poke new values for your wave function into the simulation's RAM.
Did you just invent these two words? I googled them separately and your comment is litterally the only hit. Chapeau!
(I happened to be watching How A Plumbus is Made when I wrote the comment, btw).
I think there's a noteworthy distinction between science and its applications. In my mind, science is about understanding the world, whereas fields like engineering/medicine are about their practical applications.
I do think that there's a tremendous amount of progress that could be made in sciences like Biology, Psychology etc. But I would draw a distinction between the things that fundamentally change the way we understand the world, vs building really cool toys that we would love to have.
For example, CRISPR. Many people think that CRISPR was an amazing discovery, but really, it's just a biological system that has existed for a long, long time, where a collection of smart people realized that with some engineering it could be used for effective genetic modifications with high precision and no need for engineering custom proteins to bind specific sequences. That seems fundamentally different from, for example, the experiments that established that DNA is the molecule of heredity when nobody had an idea how DNA could encode information.
> merely be elaborations of basic principles that already exist, rather than elucidations of any as-yet undiscovered principles.
This is not a meaningful or thoughtful examination of even chemistry. 3D structure of proteins is "merely" an elaboration of physical properties, yet "physics" doesn't have the tools to make much progress on solving the 3D structure of a sequence of amino acids, despite it being a purely physics process.
Is the world "physical" in the sense that probably don't have new fundamental forces of nature? Of course. That doesn't mean that physics helps understand much of the physical world, because the "elaboration" in the "merely elaboration" has nothing to do what physicists or other scientists consider "physics."
Also, we can simulate protein folding well enough from classical physics and quantum approximations such that "rapid two-state folders" are considered solved. That was a major outcome in the course of my career, to which I contributed significantly :)
I worked in protein folding over 30 years ago at EMBL, and have loosely followed it since. I could easily have been led astray, but I was absolutely not under the impression that we can do this even close to "well enough".
The CASP results weren't really a big deal. It was a modest advancement using techniques that were already spreading throughout the community, coupled with a skilled team that understood the score metric very well.
Two state folders can be reversibly folded using empirically determined force fields (two state folders basically go from "any totally unfolded configuration" to "fully folded single structure" in milliseconds); we can just run simulations and let the (quantum-inspired, classically embedded) physics do the folding, or we can use other techniques, like Rosetta (monte carlo plus lots of empirical data from known structures), or evolutionary data-based techniques (like Deepmind and others used).
Is there a paper that describes the parameters of the peptide structure that go into the "physics do the folding" part? When I was at EMBL, I was focused on using local hydrophobicity to see how predictive it was (not at all). Is the physics model operating at this level, above it, or below it?
Well done!
However, we more or less understand that morality of larger lifeforms is encoded in our DNA (e.g. telemers). Mortality seems to be a defense against cancer.
There is no particular reason that a human needs to grow old, except for the accidents of evolution.
Btw, in this sense cancer is just another tool, that limits lifespan and ensures generations change. Of course, it didn't appear as such, but most species have no natural incentive to develop a resistance to it.
Not exactly and i believe there are a rare few that are much much more resistant to it and as such have become subject of research (trough TP53 in elephants or P16 and P27 in naked mole rats)
At the end of the day this natural incentive depends on when the cancer can appear (generally right away at every step of the cell cycles) and how likely it is which probably depends on the turnover and amount of cells of a particular type or in the being overall which one would assume increases as the being grows and additionally how likely it is to inhibit reproduction as it grows.
As it stands i'd say whilst they're not too inhibiting on this front (for example humans are most fertile at relatively young age well before most cancer occurrences become a problem. We've just extended our lifespan quite a bit) they still can be (kids can die of cancer too) and thus an evolutionary incentive against it however minor is present.
Did I tell you about the time, in 7th grade biology class, the kid sitting next to me was asked to read something aloud from the textbook about ”organisms”, but of course she said “orgasms”. She might have died a little right there, whilst the rest of us got her energy recycled as a power-up.
It may very well be that understanding emergent phenomenon at the appropriate level of emergence will turn out to be vitally important, and that reductionism (while undoubtedly useful in many scenarios) is impeding our understanding of emergent phenomena like consciousness and evolution.
The assumption that any of these new technologies would be desirable and create a net positive effect in the world sounds very naive after seeing the results of something as simple as "connecting the world".
We need to have a better understanding of how new technologies interact with our existing technologies (including institutions and communities) and our environment, or else we risk (further) destabilizing everything that has allowed us to get this far.
People need to have a point of contact with that extrapolated future to became a popular science fiction work, even the culture in the far future fiction is usually pretty similar to our own (or at least, the one of the moment where that book was written).
Present works (not the ones with inherited universes from old ones) are updated to our current expectations of the future, so you have sentient computers and other "possible" technology, and probably in 50 years we will have a different set of standards and not something as naive as what used to stand as possible 50 years before.
"But time travelling is just too dangerous. Better that I devote myself to study the other great mystery of the universe..."
(looks upwards at the stars)
"women."
Backwards time travel or FTL are not measure of progress. Even with the field of "fundamental" physics:
1. There are lots of things we do not understand in cosmology (cosmological constant, nature of dark matter, matter/antimatter asymmetry, force unification at very high energy scales, gravity at high energies, etc). Each of those could potentially revolutionize our understanding of the universe
2. There are lots of things we do not understand at small scales (Casimir effect/vacuum energy relationship, plank scale effects, why the particle soup, gravity on very small scale, reason behind asymmetry in helicity/weak interaction and other parity/symmetry related effects, doing "useful" calculation with renormalization group, etc). Each of those could potentially revolutionize our understanding of the universe.
There is also a lot to be done in our understanding of computing (as in, nature of computation)
1. Computation related problems (Church-Turing thesis, novel algorithmics + computing platforms such as quantum computing). Is approximately correct/probabilistic computing a loophole for getting essentially/mostly correct results in P time for NP-hard problems? Nature of AGI/what enables sapience when doing computing.
Of course as we go into "less fundamental" sciences like chemistry/biology/etc then the amount to be learned is just overwhelming, we truly know very little.
E.g. https://gizmodo.com/we-could-solve-the-mysteries-of-time-and...
"We Could Solve the Mysteries of Time and Space—If We Had a Particle Accelerator the Size of the Solar System"
That's the problem. Our collective civilization will need to move a few levels forward before we can afford to tackle these problems.
Which leaves the obvious path forward...
I'm saying that imagine 50% of the population works in blue collar general labor or semi-skilled labor fields. Now in this hypothetical worlds, all those jobs are managed by autonomous robots. Also we have a green power that is sustainable, storable, sufficient for even double the population, and can be held in high densities at low volumes. So there are now innumerable sectors within the economy that we don't need people themselves to learn. That leaves more time for people to take extended amounts of time to learn and study. I mean quite literally a Star-Trek "post-scaricity world" in a lot of ways. People use time to further themselves and expend time on cultural or scientific endeavors. Life is no longer about struggle and survival since money clearly would have no value if any and everything can be made or consumed for free. I mean it's really interesting to think that the only "conflict" that would exist is between people trying to min-max life in terms of achievement. There would be no achievement in religion, money, or ownership since everybody can do it.
Ultimately what I'm saying is that a lot of our advances are contingent upon other sectors becoming automated and allow for more people to get into academic sectors.
Because that's the only way you get to post-scarcity.
This is a non-problem that has always taken care of itself in any developed country and we have no reason to believe it will not take care of itself in the developing world as well.
The UN for instance does not believe there will be 10 billion humans on earth ever (where "ever" means "as long as projections have any value").
The fact that we're cooking the planet with ~8B does not bode well for what even 10B looks like.
I'm not saying that 100% of that 50% will be employable in this world. I'm saying that over time that 50% will inevitably become that bare minimum. The way I see it is 150 years ago, your idea would be that we couldn't possibly get all children to become educated at an 8th grade level, yet here we are, even making an HSD the bare minimum.
Eventually your masters thesis will be an area for you to study and pursue to make an attempt at furthering society.
Not a physicist so excuse the ignorance, but do we understand gravity at all?
I mean afaik we can observe and predict it's behaviors but do we understand what underlying force causes it, and if it potentially has a counter force.
So the word "understand" is a bit loaded. GR is a certain understanding of how gravity works, but it is not a "quantum mechanical" understanding.
Although, life can be reduced to chemistry and chemistry to physics I feel we are missing some high-level self-organizing principle of the universe.
Sorry, could you explain why you think life is not evolvable exactly? Assuming you take the existence of a single celled organism with DNA as a given (we still don't know the origin of life), evolution gets you the rest of the way rather nicely. Notably, "life" usually contains the assumption that it is evolvable as part of the definition. If the children of the organism can't adapt to the environment, we don't consider those things to be "alive" (e.g. a 3d printer that can print a copy of itself isn't alive).
As for the origin of life, all serious scientists are onboard with abiogenesis, though we don't know the mechanism. Every year, new science comes out showing how microfluid droplets with organic compounds + the natural environment, can result in behavior that looks similar to a cell.
For example, this one shows fairly interesting "cell like" movement without any life, and there was another last year that proposed a possible abiogenesis of cell walls through evaporation and organic compounds that suck up large molecules into the interior when evaporated.
https://qz.com/487712/why-these-colored-water-droplets-seem-...
Evolution implies a relatively smooth path through "DNA space" from, say for example, an early single cell eukaryote to a mushroom. However the search space is enormous. Even if we account for billions of years of evolution and a trillions of evolutionary experiments each year, a simple random walk with selection through DNA space should go nowhere because of the numbers involved. The curse of dimensionality[0] means there has to be some other principle of nature to make the search space yield a path from one viable life form to another. The search space of life would have to be 'smooth' in some sense. That 'smoothness' is something we don't understand.
If DNA space is just 256 bits (as a dramatic simplification), then 2^256 is a very very big space to search just by chance [1]. Now imagine a space orders of magnitude bigger.
[0] https://en.wikipedia.org/wiki/Curse_of_dimensionality
[1] https://youtu.be/S9JGmA5_unY?t=22 (3Blue1Browns wonderful illustration of how large 2^256 is)
Imagine flipping a fair coin 256 times. The particular outcome ('HTTTTHHTTTTTTTTHTHHHTHHTHTHHHHH...') is extremely difficult to replicate, but getting any outcome is very easy: just flip the coins again. In this case we also have a lot of selection bias: all the paths through DNA space that don't result in intelligent life don't result in anyone having this conversation.
Regarding the curse of dimensionality: it's a statement about the available data rapidly becoming sparse in high dimensional spaces. It doesn't really say that high dimensional spaces are necessarily sparse, it's just hard to "fill" them in with the amount of data available.
Comparing a mule with it’s parents shows how much novelty can be produced in a single generation (in this case an evolutionary dead-end of course)
Just because many of the questions we want to solve today are of practical significance (inventing new medicines, perhaps) doesn't make it any less scientific.
Indeed, almost 20 years after the Human Genome Project, we have only scratched the surface on how to understand what any particular genes are doing, and are very far from doing anything more than "hacking" on existing genes, let alone writing a biological program from the ground up.
Tell that to Einstein.
Einstein's advance was quite spectacular, and early.
Source: Am gravitational experimentalist.
https://www.newscientist.com/article/mg24032022-600-exclusiv...
This is why category theory was not discovered, it was reverse engineered! The reverse engineering steps were:
3. Natural transformations
2. Functors
1. Categories
Edit: Of course, when he said theorist I think he meant people who don't experiment physically.
When we went from 1 coconut -> the set {1}, then we were being really abstract for the times.
But I think your point is that category theory synthesises group theory, linear algrebra, topology, etc. into one concept, which was very much the spirit of the origins of category theory. However, Mac Lane and Eilenberg thought that their diagrams were just an aid to mathematics (much like a Venn diagram, Cayley diagram or a Feynman diagram). But when they realised that natural transformations are so ubiquitous and fundamental, then they realised that their graphs were not just a useful shorthand, but in fact would lead to a whole new type of mathematics. When people thought (not Mac Lane though) category theory was "abstract nonsense" they were making this mistake of thinking that the diagrams are illustrations rather than concrete mathematics.
In the same way, you might thing that {1,2,3} is just an illustration, but in fact it is a rigorous shorthand for a very specific set.
The real meat behind category theory are things like natural transformations and adjunctions. But to get to category theory from there, you do a kind of reverse engineering.
But as we all know (especially those of us who have refactored many systems), every once in a while you find a new way of looking at a thing that makes it all much simpler. A geometric way to look at an algebraic thing, or vice versa. Or a unifying structure to combine disparate pieces. Or just a "wow that was dumb" undoing of unnecessary complexity. It makes further progress easier.
I could imagine that, as the boundaries of science get more complex, there will be more scientists working on making the rest of it less complex. Meanwhile, maybe we get smarter and live longer. The calculations involved with many areas of modern science have already outpaced what we can do by hand, but we invented computers, so I can take the mean of a zillion numbers without much effort and spend my time elsewhere.
And in med school, apparently they say "half of what we teach you will be false, but we don't know which half." As science progresses, you don't just add, you prune too.
With software being as slow as it is despite massive speedups, and even despite despite massive speedups, we really are still not good enough at using our computers to their fullest capacity which still means getting insights into complexity before crunching the numbers.
Operating systems might be slow. Applications might be slow. SaaS might be slow.
But computation is not slow, and if you care about speed, you do computation in a context where the aforementioned issues are not issues.
There definitely is a lot of bloat in the software world, but even large bioninformatics organizations have their own data-pipeline management teams to keep these issues in spec.
We started out that way, I dunno if we'll end that way.
And even if it does eventually come down to 30 rules that explain everything? How many rules does Chess have? Way more than Go, and both can take decades to really understand.
Abstractions are the key.
But you're right, will the human race ever "retire"?
For instance, you might be satisfied you know how a pendulum works. Now put another pendulum on it.
Or you think you understand gravity, because you got taught the inverse square law. And you then get Kepler's laws. But then with three bodies, things get really hairy.
Or you understand statics and materials. But how do we shove that into finite elements? Not an obvious thing, and required some real investigation.
There's also completely new ways of seeing things. Who would come up with information theory? Doesn't seem like something that would obviously be found, despite not really requiring any physical experiment.
And then there's things like algorithm research that turn out to be really big once there's a bit of computational power on the horizon. (Probably people think about the algo before they can try it on a machine.)
I would say the great problem of science right now is integrating all of the knowledge there is.
It's time scientists stopped publishing dumb weakly connected PDFs, and start switching to a GitHub like pull request model.
We could build a single strongly typed peer-reviewed repo of all of the world's scientific information, complete with definitions, experiment protocols and data, and make it universally downloadable and usable by all.
You underestimate the number of cranks who have "great ideas" and "just need someone else to work out the math."
You're not wrong, but, it is important to note there also isn't a shortage of great physicist who "just need someone else to work out the math."
For example in 1846, Faraday proposed that visible light is a form of electromagnetic radiation. But because he couldn’t back up the idea with mathematics, his colleagues ignored it. It took 18 years for Maxwell to come along and prove it.
This sentiment about math is so cringe, because it is the same type of prejudice of social class that Faraday himself fought against his whole life being the son of a poor smith. Not to mention physicists such as Carl Sagen, generally held in high esteem within the physics community, always preached of an eventual point in physics that transcends math (i.e. something more fundamental and basic) to describe the universe.
Camp out in an IRC channel like #physics on any network and prepare to be bombarded by idea people who just want someone else to do the heavy lifting, from math to the experiments. And woe betide those who want to say "by the way, your idea leads to perpetual motion/faster-than-light travel, so I will not bother." I personally have experienced soul-crushing numbers of philosophers who happen to think they've disproven special relativity who are also under the impression that the Michelson-Morley experiment was performed precisely once and everyone just sort of ... ran with it, never looking back.
Who has time to weed through this sort of thing? It isn't ideas that physicists lack for, not in the least.
Like I said you aren't wrong...its just important to note, that some of the best minds in physics didn't have the math chops to prove their ideas. But if we ask why there are so many more people with ideas of how the world works and such a small number that can validate/disprove them speaks directly to classism. Being able to prove/disprove physics theories is generally, going to require a significant investment in education from early childhood that has been, and still is, out of reach for most. Its not a lack of intellect or talent, but lack of investment across the board.
In other words until the ideas are disproven you shouldn't call them a cranks simply on the basis they don't have the math chops to prove their own theories.
>Camp out in an IRC channel like #physics on any network and prepare to be bombarded by idea people who just want someone else to do the heavy lifting, from math to the experiments.
Seems to be a pretty efficient strategy. The entire point of this website is to support a similar model where YC is bombarded by investors who want someone else to do the heavy lifting, and business and make the returns.
Cranks are cranks. I will most definitely call them that and continue to do so. I no longer camp out like that because I could not bear it any longer. If you would like to spend your life attempting to work out the particulars of some FTL drive that supposedly works by repeatedly raising magnets above the Curie temperature and then lowering them back under it, have at it. Fire up IRC. I suspect you will spend much time laboring to support the ideas of cranks because it simply is not a good use of your time. It was a good use not of my time, either.
That's all it is -- efficient allocation of limited resources. My time, your time, someone else's time. How are these decisions made? How do we decide which of the ideas do we examine first?
If it is "possible greatest payout," then we would spend all of our collective time on perpetual motion devices. They would, after all, be the greatest payout. And yet the patent office won't even look at them.
No, our first filter is: can this be tested? And to test, we must measure. To measure, we must calculate. And there is our math.
Good ideas will bubble up from the bottom, and more than one person will have a good idea. If one of those people does not have the math and another does, then science will eventually get around to the person who has the math.
What's your algorithm for deciding whose ideas get worked on? I bet that it has some kind of criteria attached to it. I doubt you are suggesting selecting humans from across the planet purely at random and asking for their scientific ideas.
Simply put, this is the scientific method. Make a new, better scientific method if you have a better (by whose standards?) algorithm for deciding whose ideas are worth examining first.
Education is not a finite resource (I think you know that and hence you changed the goal post from math to experiments).
Nevertheless, when those that have the resources look down on those without (calling them cranks), based not on the merit of their ideas but based on the lack of resources to prove the ideas...that is classism.
Education is absolutely a finite resource. We have finite universities and finite educators. The lifetime required to attain an education is also a finite resource, as you simply cannot have a workable society while also requiring that everyone get a PhD in anything they have an "idea" about.
Limitations about. We must make choices against them. We could do quite a lot of particle research should we decide to disassemble the solar system and re-purpose it into an accelerator, yet I will gently suggest that this proposal will not achieve much traction.
However, knock yourself out. You can manage to join IRC and fight against classism by spending your time working to support the ideas of people whom you will not call cranks. Prove me wrong by doing it for the next ten years. Time isn't a finite resource, right?
You still will not engage with the most basic thrust of this: we cannot entertain everyone's ideas simultaneously and decisions must be made as to which are examined first. Anything but that is some form of -ism because you have a selection criteria that might ignore an idea.
So we are left having to come up with some kind of heuristic to examine some ideas and not others. This is the scientific method. Is your idea testable? And if you claim it is, what values will we measure that are different from what currently exists?
Propose your alternate method. Then, tell me how you are going to exclude the people who, say, want to glue crystals to engine exteriors to improve the combustion efficiency, without anything seeming even a trifle discriminatory.
Might there be a constructive way to benefit from the comments provided by cranky behavior? I'm not suggesting taking direction from folks with no experience, but perhaps cataloging the comments on this IRC channel to see what the distribution is.
Perhaps don't think too hard about the solutions proposed in these comments, but instead what problem areas do they fall into. And then from that perhaps there's an opportunity, if not for new research, for creating some better synthesized educational resource that might help people get up to speed faster.
John Baez has a lovely "Crackpot Index" that is an excellent jumping off point for a description of your average crank contact. It would be different for IRC but not dissimilar.
I know you're trying to give people the benefit of the doubt, but experience hasn't shown that it is worth it or even feasible.
As I said before, even the patent office has given up on perpetual motion machines.
One serious problem for any such system is ontology selection: how is one to represent the entire body of scientific knowledge under a single type system? Different fields of inquiry make use of extremely diverse conceptual models. I suppose mathematics are in a way a unifying language, but there's hardly a single homogeneous mathematical discipline.
The present "weakly" connected network has almost zero technical barriers to entry. It uses well-established technology within a well-established workflow, and it offloads the hard, fuzzy work (e.g., all the model-binding that would presumably take place in the proposed system) to the most flexible computing device we know of: the brain. Everything is already freely downloadable/usable, for the most part (lots of research is open access, and what isn't can often be obtained from the investigators by request).
That said, maybe the sort of thing you describe could be translated into a research question. One could try to compare the shape of various data under different encodings, for instance (some sort of topological analysis?) to identify similar structure? I think category theory has been used to unify previously disparate regions of mathematics.
There are already a few entries in the social network/resource-sharing platform space. Have a look at Open Science Foundation. Academia and ResearchGate are similar, but without the materials-and-data-sharing.
Great breakdown, thanks.
> One serious problem for any such system is ontology selection: how is one to represent the entire body of scientific knowledge under a single type system?
I think you can do it through market forces and forking. Similar to Linux distributions you could have "science" distributions. As for the type system and unifying language, I think you can do a thing that can start from just a dot and no dot and build up characters and numbers and words and types etc, with no extra parts. So perhaps if you had something like that, where simplicity could be rigorously defined, you could get consensus on base level types. If people had strong differences, you could go off and fork a new distribution. I'd imagine you'd have a few distros emerge with decent gravity.
Pull request could be really neat. I can imagine you'd have the speed of light defined somewhere in a science distro, and there would be data from reproducible experiments that people have done. Perhaps someone comes up with an ingenuous at home experiment that is just a few steps and sends a pull request that would add that, and perhaps prune some more complex experiment.
> offloads the hard, fuzzy work to the...brain
Yes, exactly. I'd love it if it was computable (of course, this isn't an original idea--Wolfram Alpha is trying to pull it off). If I could "go to definition" of any scientific conclusion (not only to definitions, but to real data, and simple, repeatable experiments). If you kept "going to definition" all roads eventually would lead back to 0 and 1.
> One could try to compare the shape of various data under different encodings, for instance (some sort of topological analysis?) to identify similar structure?
I'm giving it a go with Trees. I think it will work, but still might be a few years before I know for sure.
> There are already a few entries in the social network/resource-sharing platform space. Have a look at Open Science Foundation. Academia and ResearchGate are similar, but without the materials-and-data-sharing.
I like those, especially OSF. Definitely a lot of activity in the space (I invested in some new ones as well). I haven't seen one yet that does the "science monorepo" thing, but hoping someone takes the lead there (and I'll do my best to support it with hopefully useful underlying tech and research).
An excerpt from Advice for a Young Investigator. https://www.goodreads.com/book/show/437689.Advice_for_a_Youn...
It is definitely easier to hear casually about Ramon y Cajal in "anglo countries" than in Spain. For example, I have spent my childhood in the spanish state, and I first heard about Ramon y Cajal during the first conference that I attended, in Switzerland, from a lovely presentation by an English professor.
One of the dramatically few spanish first-rate scientists, and he's not a household name. Very, very sad state of affairs.
Science, in general, is criminally underrated in Spain, but Ramón y Cajal is literally the household name.
I studied first in Madrid and later in Galicia.
Santiago Ramón y Cajal (1852 – 1934)
But I believe he's probably still right in 2020.
I think this could be used to describe almost any point in history though. The greatest discoveries in science have always required massive breakthroughs in thinking, that typically defy conventional intuition. Perhaps there are some rare moments in time following a major discovery where the fruitful areas of inquiry seem obvious. But “I don’t even know where to start looking for the next major scientific discovery” or “this hypothesis might be wrong and we could potentially spend the rest of time investigating it” seems to be the default state of trying to make major breakthroughs in science.
>most of the grand underlying principles have been firmly established and that further advances are to be sought chiefly in the rigorous application of these principles to all the phenomena which come under our notice. It is here that the science of measurement shows its importance — where quantitative work is more to be desired than qualitative work. An eminent physicist remarked that the future truths of physical science are to be looked for in the sixth place of decimals.
The problems today are either in areas where complexity is the limiting factor, like biology, or beyond current experimental reach, like string theory and dark matter. The complexity problem can probably be overcome with computer assistance. Experimental reach is harder.
The date definitely changes my perspective but I still think the essay is a little too waffley - it doesn't to give any actual examples or indications or where the author thinks important scientific problems lie. In fact it kind of begs the question. In response to a concern over whether there are important scientific problems left to solve, it simply lists some historical important scientific breakthroughs.
I suppose the point is that breakthroughs are unexpected...
https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...
It's true that moderation isn't consistent, but that's not because it's selective in the way you imply. Rather, it's because we can't come close to reading everything, and can't moderate what we don't see. If you notice a post that breaks the site guidelines and hasn't been moderated, the likeliest explanation is that we haven't seen it yet.
https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...
WTF is gravity? Why is gravitational mass and intertial mass identical (in all known situations)?
Do we orbit the Sun or the image of the Sun? In other words, what's the speed of gravity?
Can we control gravity?
- - - -
What is subjectivity?
Why is "it" always now?
"You" and "now" are synonyms, why?
- - - -
WTF is up w/ the structure and dynamics of the Solar System? ( 97.77° axial tilt!? Go home Uranus you're drunk!)
- - - -
QM and Relativity, chocolate and peanut butter?
Or the Universe is messing with us and actually is describable by multiple irreconcilable models?
That's metaphysics, not science.
> Do we orbit the Sun or the image of the Sun? In other words, what's the speed of gravity?
The image. Speed of gravity is the same as the speed of light.