Yes they are. They are transitioning through levels in the conduction band where you have plenty of them.
Every time you see a macroscopic phenomena, you are looking at a stupidly high amount of quantum levels with very similar energies.
HN user
Yes they are. They are transitioning through levels in the conduction band where you have plenty of them.
Every time you see a macroscopic phenomena, you are looking at a stupidly high amount of quantum levels with very similar energies.
How else are you sure your team does not conflict with itself?
/s
Imagine if they hired those 1111 to do the most massive nine-month-long live coding interview and only 11 pass the bar.
I want to learn Forth. Do you have any good reference or know about some good code examples?
Just learned the stack operations and trying to get used to them, but I have some bigger projects in my personal backlog.
The power to destroy a thing is the absolute control over it.
I don't have enough time now to work out how are the movement described in your representation to evaluate its convenience. If you have worked out something, could you share it?
I don't know anything about the cube world as I'm just a noob in this.
I don't understand why I would push to origin my local branch. This will (potentially) require multiple push -f. I prefer to share the work in a state I considere complete.
As an alternative, just create a new branch! `git branch savepoint-pre-rebase`. That's all. This is extremely cheap (just copy a reference to a commit) and you are free to play all you want.
You are a little more paranoid? `git switch -c test-rebase` and work over the new branch.
Then is not rebase your problem, but all your other practices. Long lived feature branches with lot's of unorganized commits with low cohesion.
Sometimes it's ok to work like this, but you asking git not being judgamental is like saying your roomba should accomodate to you didin't asking you to empty it's dust bag.
False
For your example, if both lists are small enough, the constant factor on the cost of creating the hashmap eliminates any advantage you could have. Anyway, it's not like most places were I've seen a nested loop used for search the developer had cared. Today I am in a bad mood.
I have to touch some of the most unnerving modules in a legacy project and everything is a trap. Lot's of similar repeated code with ugly patterns and some big brain trying to hide the ugliness with layers and layers of indirections and inheritance, and calling it clean because there is a factory class. The biggest joke? each implementation have a different interface for key methods, so later you to check what instance got created.
I want to keel myself. Anyone could assist me in a seppuku?
I don't know what JJ brings over git, but what sold me worktrees around 2 years ago was this article: https://matklad.github.io/2024/07/25/git-worktrees.html
Heck. I need any replacment to be at least equally capable of PDFs. The minimum I expect is for it to be able to run Linux in them.
https://github.com/ading2210/linuxpdf
/s
But most common noises are not white. you had to decolor it before.
Should Archeologist rebase or merge when new evidence is undercover?
Netflix and to some level spotify drowned piracy for a time. But then a lot of companies tried to rap the same "winings" splitting the ecosystem and trashing the user experience.
- ¿could we watch x movie? - let me see. no, it in this other service beside the 3 we are paying.
The cost is in the context switching. Throw 3 tasks that came 15, 20 and 30 min later. The first is mostly ok, you finish by hand. The second have some problems, ask for a rework. Then came the other and, while ok, is have some design problems. Ask another rework. Comes back the second one, and you have to remember the original task and what things you asked for change.
Ecosystems are dynamic by nature, so "make them like where 222.22 years ago" is a little meaningless.
But biodiversity is a good target and as unbiased as you can get. More biodiversity means more adaptability and resilience of the system.
I could try to answer myself, but this will be far better that I could express in english:
The only "real" thing I've done with ruby, many, many years ago. A little script to extract the functions definitions from a FORTRAN project. The idea was to add more data. Later I learned about ctags and never added another feature.
I'm sure there is a copy in an external ssd I lost 2 summers ago.
I don't know if you are talking about Drunken tree (palo borracho in spanish) but once playing soccer in a field with some of them I ended with around 15 funny parallels cuts. Good old times.
I remember reading an article about different behavior between summer and winter. So, working better/worst in business hours doesn't sound completely crazy.
But they turning some knobs based on load also looks razonable.
You need to provide more information.
Is your data organized or is just a dump of unrelated content?
- If you have a bag of files without any metadata the best option is to create something like a RAG, with a pre OCR step for image files (or even some multimodal model call).
- If the content is well organized with a logic structure an agent could extract information with a little look around.
Is static or varies day by day?
- If is static you could index all at once, if not, an agent that pick what to reindex would be a better call.
I'm not aware of a solution like this, but seems doable as an MCP server. But the cost will scale quiclky.
I partially agree with you. But the selling point of artificial sweeteners was that they were a healthier substitute.
It's better to teach people that there is no free lunch, and they should take care about the calories they are consuming, even if that imply reduce frequency of sweet foods, than sugar coating an equally bad alternative to make it sound like it's healthier.
I don't know where you can read about this, but you are in the good track
If there is no authenticationData then the if !Ok is never run and the code continues execution as it were authenticated.
k v⍪←↓⍉↑(2 0.33)(2 0.01)(3 0.92) ⍝ insert values k{str[⍺] ⍵}⌸v ⍝ pretty print k v⌿⍨←⊂k≠str⍳⊂'buggy' ⍝ deletion
I like your funny words. No, really, I should expend some time learning APL.
But your idea deeply resonate with my last weeks struggle.
I have a legacy python code with too much coupling, and every prior attempt to "improve things" went adding more abstraction over a plain wrong data model.
You can't infer, reading the code linearly, what methods mutate their input objects. Some do, some don't. Sometimes the same input argument is returned even without mutation.
I would prefer some magic string that could be analyzed and understood than this sea of indirection with factories returning different calculators that in some instances they don't even share the same interface.
Sorry for the rant.
Have they trained o1 with my inner thoughts?
What complexity class will be the problem of construct only hards to solve knapsack (or others) problems?
The entire stack down to silicon exploded multiplied by 3 or 4 in that time.
Vectorization, more cache levels, branch prediction, multiple cores and processors, gpu, virtual machines, (operating systems, but they didn't change much, I only let the placeholder for the layer), containers, but all that in the cloud, distributed databases, frameworks written in a language that need to be compiled to a language that is actually implemented by a web browser in the client (we are far better on compatibility between browsers, but much libraries or practices keep stuck in the past).
I haven't touched shift in practices that make it far worse.
That make it more unreasonable.
I don't see that contuer-intuitive at all. If you have a barrier in your cost function in 1d model you have to cross over it no matter what. In 2d it could be only a mount that you can go around. More dimensions mean more ways to go around.
I don't think there is enough (non syntetic) data available to get near what we are used to.
The big breakthrough of GPT was exactly that. You can train a model with (for what that time was) stupidly high amount of data and make it okis to a lot of task you haven't trained explicitly.