I could argue that ethanol has 1/3 the latent heat of vaporization of water, and would boil off 3 times quicker. However, what ultimately matters is the rate of heat transfer, so my nitpick may be irrelevant.
I'm looking for a language with the performance of C++ and the ease of Python, and I've been constantly told that Rust fits that spec.
I'll look into Zig, but I'm hesitant about using languages that nobody has ever heard of. Especially for a project that I might release as open-source.
There is no language that fits that bill perfectly afaik.
As someone who used to write a lot of Python, Rust feels easier for larger projects and for long-term maintenance. It’s also (for me) substantially easier in Rust to write anything with concurrency or parallelism, whether async or threads. The learning curve is significantly higher than Python. For my day to day coding, now past the learning curve, it does feel ~as easy as Python, most of the time.
Tolkien scholars would ask the question: is Sam Gamgee the warrior or the gardener? (The right answer is: he is a gardener, the Lord of the Rings is all about rebuilding after destruction.)
>"Today, there's a different language with ugly historical baggage that enjoys a strong following, *notably amongst people that don't identify as programmers*. *That language is Python*."
>"Python is the new BASIC because *Python is the language that non-programmers always seem to use*"
>"If even a *Python-hater like me* defaults to using Python, then I think it's pretty clear that Python has taken over the world, just as BASIC once did."
1) As a Python fan, I consider this hate speech.
2) I have yet to encounter a software development kit like Visual Basic that makes it easy to write executable files with a GUI.
You know, I am not actually much of free speech absolutist, but this is the kind of statement that makes me more sympathetic to them. When they sometimes express the worry that the category of "hate speech" is going to be stretched to cover any sort of dislike or disagreement, I think this is the kind of thing they have in mind.
I agree, this is a trash post full of hot stinky air :
- name-calling without any actual examples
- no actual comparison with Basic, the extremely simplistic "popular" sticker covers massive differences in use, users, functional coverage of libraries, and so on
- non-programmers that program use python? this is leveraging python's value as a teaching language in the most derogatory way possible
- "ugly historical baggage" ? sure, show me a better designed language, show me the baggage
“Hate speech” is usually reserved for speech involving people… can’t tell if it’s sarcasm.
I use python, I don’t love it. Don’t really hate it either. You use it because it solves a problem or has a library that makes solving problems easy.
It’s ok for people to have different opinions about what languages they like.
There is a video where someone asked for people to submit python scripts to control his Christmas lights. It was fun but slightly annoying because over half the programs wouldn’t run ( missing libraries/ tab space indenting mis match). He said we would but he tried to install one of the packages on the fly. It installed, he got the same missing package error on rerun. Sort of matched my experience using python trying to get others peoples code to run.
By all means, feel free to fact check our textbooks, news broadcasts, and statements from official sources.
But when I log on to social media to rant about how UFOs are time-traveling humans, I don't want a teal-colored, official-looking div element to alert the world that the online version of my personal expression is objectively wrong.
The problem is that someone can say "they are eating the cats, they are eating the dogs" and that turns into hate and violence in the real world. They are not separate spaces, both the physical and the digital are part of the same world
So where does the line get drawn? Many believe that American style free speech goes too far and enables the malicious freedom to manipulate
Also, online platforms are currently anti-competitive, so when you don't agree with the provider, there are significant costs to choosing another. That's why efforts like ATProto & ActivityPub are important to the next generation of social media applications.
There is a semantic issue here that's bothering me: the word "Fact" is a contronym.
I was taught in elementary school that facts don't need to be true to be a "fact". Nearly 3 decades ago, I was told that "facts" are either true or false, as opposed to "opinions" which are neither.
Then, as time moved on, I encountered what appeared to be a bifurcation in the English language, where half the people I encountered defined "fact" as a true statement, and the other half defined "fact" as any statement about the external world that did not rely on somebody's internal state of mind to make sense.
I challenge all of you to perform a quick experiment with Google.
Step 1: Google "Fact vs Opinion". Skim the results.
Step 2: Google "Fact definition" or "Fact meaning". Skim the results.
Step 3: Compare and contrast.
You are given a list of color names, written in font colors that are incongruous with the written word. E.g. "Red" will be written in a blue font, and "Green" will be written in a yellow font.
You have to say the font color and not the written word.
It's challenging, but it's yet another application where going cross-eyed confers an advantage.
The difference is that we know for a fact that the proper implementation works for integers up to 2^31, whereas the improper implementation deceived us into thinking that the code would work in situations where the code actually doesn't work.
I find it valuable to understand when my code will crash.
Interesting information... it prompted me to do more research.
According to wikipedia, Vitamin B-9 is broken down by our bodies into a family of compounds called "THF", which:
1. Help synthesize DNA,
2. Help repair/modify DNA,
3. Help create the amino acid "Methionine", which is a precursor to other amino acids, and is thus important for the synthesis of many proteins inside the body,
4. Activate Vitamin B12.
A deficiency in Vitamin B-9 can lead to a loss of appetite, weakness, heart palpitations, headaches, irritability, and anemia. Also interesting to note that a deficiency in Vitamin B-12 will cause the body to overcompensate and convert a large portion of Vitamin B-9 into the form that metabolizes Vitamin B12, which leads to a condition that mimics a deficiency of Vitamin B9.
One of these days, when I have enough free time, I want to develop a particle-level simulation of the human body, so that medical students, doctors, and curious laymen can see these processes in action on their personal computers. If I combine that with an affordable at-home blood test/diagnostic system, we will have a mechanism to bring affordable healthcare to every single person in the country. And perhaps a reliable method to find the true cause of a patient's depression, before prescribing them SSRI's or other psychiatric drugs.
The compound is a key product in the methionine cycle[1], which is responsible for synthesizing neurotransmitters like serotonin. Poor methylation in this cycle can reduce synthesis of rate-limiting compounds in the cycle, thus limiting production of neurotransmitters, perhaps inducing symptoms of mental illness.
Another product in this cycle is SAMe (S−adenosyl methionine), which has been marketed for decades as supplement for improving depression.
> One of these days, when I have enough free time, I want to develop a particle-level simulation of the human body, so that medical students, doctors, and curious laymen can see these processes in action on their personal computers.
Likely you wouldn't need/want a particle level simulation, but a kinetics level model. Just with kinetics you could draw simulations of "particle concentrations" or other fun things to show medical students, etc, but without the need to simulate the actual chemicals. Though eventually hopefully we could do that too! The AlphaFold breakthrough is a huge advance toward that IMHO.
> If I combine that with an affordable at-home blood test/diagnostic system, we will have a mechanism to bring affordable healthcare to every single person in the country. And perhaps a reliable method to find the true cause of a patient's depression, before prescribing them SSRI's or other psychiatric drugs.
Just getting all the kinetics together would be amazing. You could essentially do what you're talking about of calculating most likely causes (not just correlations). Though brain chemistry != entirety of depression or whatnot. Still just getting even the top 20 chemical cycles mapped from blood tests could be pretty awesome and help bring light to a huge range of conditions.
In my opinion, medicine currently is at a 1.0-1.5 order effects level. As in we can diagnose first order ailments pretty well. But second order effects? Not really, though I said 1.5 in that medical researchers and doctors are slowly figuring out some limited second order effects, like "X medicine with Y gene" or "X medicine with Y medicine" can have good or bad effects.
We're certainly not talking about 3rd order effects.. We have the math, we have the statistics, but it's just hard maths and stats.
Sadly even a kinetics level simulation for anything remotely complex is far beyond what current compute is capable of. Even simplified models of basic biological processes are immensity complex, and still potentially incomplete. Just as neural networks do not even attempt to reach the level of molecules, (practical) models must necessarily exist at a much higher abstraction.
Although alphafold is a breakthrough, this is less optimisation, more chaos theory.
I'm not going to try to predict the shape of a protein from a chain of amino acids. I'm not going to try to predict the behavior of a human cell from Schrodinger's equation.
My project's scope is more along the lines of:
1. Taking a look at Roche's list of all biochemical pathways in the human body[0].
2. Creating a 3D model of a human body, assuming that all the molecules in the body interact only in the way that the chart prescribes.
3. Create a database of symptoms and sensations in the body, and use the 3D model to determine all the possible ways that the biochemical pathways could go awry in order to create the ailment.
The way I envision it, the model is simply going after low-hanging fruit.
Number 3 is very interesting - Methionine is a crucial precursor to producing glutathione, the body's "master antioxidant". If the inflammation / oxidation hypothesis of depression that I'm spruiking is correct, then B-9 supplementation may help alleviate depression by increase synthesis of glutathione which is turn would reduce the level of free-radical caused neuro-inflammation.
I'm all for your particle-level simulation of the human body, I've had thoughts along similar lines (but unfortunately lack the skills and knowledge to implementation something like this).
I’m not sure what you’re working on now - but the particle-level simulation seems exceptionally worthwhile to humanity and maybe uniquely suited to your skill and enthusiasm.
At this time, I mean every hormone and protein flowing in the bloodstream, along with the state of every single cell.
Essentially, enough detail to get a list of symptoms and bodily sensations, and predict the outcome of any potential blood test or urinalysis. Or, alternatively, enough detail to take the results of a blood test/urinalysis, and predict the state of every single tissue in the body.
I don’t mean to dissuade you, because simulating biology is a truly fascinating task. That said, what you’re describing would be a monumental task, not exactly a free time side project.
Consider protein folding. This occurs millions of times per second in the thirty trillion cells in the human body. We only just now built a machine learning model that can predict some of the conformations of individual proteins.
The crazy thing is that protein folding is the easiest problem in biology. Nice clean training data, static high resolution targets. Cell biology is not that. Cells are noisy and constantly changing, and its insanely difficult to even measure what they're doing. Like every time we try to determine how many different types of cells there are, we come up with a different, larger number than before. The reason for this is that all our measurements of the number of proteins, RNA, and other chemicals in cells are bad, like looking through a distorted broken lens.
Complicating all this is that biology is is insanely coupled across both spatial and temporal scales. Consider the KRAS protein. Its one of the most commonly mutated genes in cancer. The most common mutations in KRAS amount to about a dozen atoms being out of place in the protein, due to a single base change in DNA. This nanoscale change in a single cell propagates up to tumors that interfere with bulk physiology and result in death. Or, more specifically for the brain, consider huntington’s disease. Theres a section of DNA thats repeated in a gene called huntingtin. If you have less than 36 copies of the repeat, the you're fine. More than 36 results in a brain disease that typically takes 30-50 years to even manifest.
So, all that to say that simulating this is insanely hard. Like, you’re trying to write a simulation for a system where we dont know what it’s made of or how its individual parts work. Also, we just empirically know that changing the arrangement of a few atoms can result in massive changes that lay dormant for decades before they suddenly appear.
This is one of those hard problems in computing and medicine. Accurately simulating a neuron, for example, or other cells is beyond our capabilities. We have a difficult time even simulating individual receptors themselves on cells, which includes accurately predicting and simulating ligand binding on proteins.
It's something way beyond our current capabilities.
There's some interesting work on "organs on a chip" e.g. arrays of microfluidic cell cultures that allows some experimentation on a combination of a few types of tissue modeling an organ or some aspect of it, but even that's already pushing the state of art and not fully mature at the moment; doing something similar for many (much less all or most) organs is something that doesn't work yet; and these "organs on a chip" are useful because pure simulation is even less mature and is unable to do what these cell cultures can.
The goal you state is interesting, relevant, and potentially achievable, but it's still some decades away.
