Amusingly, some of the earliest AI research was using Lisp which beget AI winter. Now we’ve come full circle with LLMs that struggles to write valid Lisp. Almost poetic.
I have a feeling we'll care less about untyped languages going forward as LLMs prototype faster than we do, and fast prototyping was a big reason why we cared about untyped languages.
Pedantic but Lisp is not "untyped". (Neither are JS or Python.) All data has a type you can query with the type-of function. The typing is strong, you'll get a type-error if you try to add an integer to a string. Types can be declared, and some implementations (like SBCL) can and do use that information to generate better assembly and provide some compilation-time type checks. (Those checks don't go all the way like a statically typed language would, but Lisp being a programmable programming language, you can go all the way to Haskell-style types if you want: https://coalton-lang.github.io/)
Just be prepared near the end for refinements. When I did mine, I had to do another 6 months of refinements near the end to help get the locking of my bite grip to be where it needs to be. I was otherwise expecting that day to be when I’d be done, and later learned refinements are a fairly common occurrence when going through Invisalign.
As the sibling comment, it’s definitely worth it. Best of luck!
This isn’t the case with 3D printed bracket systems. Studies have shown that the 3D personalized bracket system from LightForce will cut down treatment time over 40%. The refinement phase is also spot on and finishes much faster, and recent studies have shown further improvements. Also, the more complex the case, the larger the delta on the performance. Not all orthos are practicing this way but this is where the future is going whether it is LightForce or another company. The physics just works out better than the best plastics.
Disclaimer: I’m a health nerd and was an employee a couple years ago.
LightForce still requires a lot of visits to the doctor. Nice source of revenue for orthos. Aligners may become more accessible to patients, because that tech is more scalable by design.
Ivan worked at Align and was CTO of European DTC competitor. I agree with Ivan that both technologies have their sweet spot. I disagree with the scale piece and the frequency of visits as there are practices doing both those things differently using the placement and remote monitoring technology.
For younger patients that haven’t had braces before which is the majority of historical patient populations and future ones, 3D printed personalized braces systems are better as the tooth movement needed is more clinically substantial at tougher angles. Many younger patients forget and lose their plastic aligners.
That said: what is chosen should be what for the whole person at multiple levels.
This sounds like AI-written comment, at least in the first part. What I do not get is why are you dismissing the argument about number of visits. 3D printed braces are still braces. They require manual adjustment for each treatment stage. Aligners do not need that - they may need a check-up in the middle of the treatment, maybe one or two mid-course corrections, maybe an appointment for installation of attachments, but that's it. You change aligners at home without visiting doctor.
>Many younger patients forget and lose their plastic aligners.
Not who you asked, but I think making the nuance between retail and corporate credit. With firms being corporate credit (i.e. we aren’t talking about individuals / retail).
- bonds. Loans interned to be bought by a range if investors and traded over time. Arranged and unwritten by investment banks.
- bank loans. The classic loan. The bank takes depositor money (that the depositor can take back anytime!) and loans it to someone or some company. The bank holds the loan
- private credit. Like a bank loan, but they get their money from long term investments by wealth people and institutions, add bank loans for leverage, and then hold the loan.
These are mostly syndicated. The traditional difference between loans and bonds was bank versus investment bank. The modern difference is in underwriting technique, degree of syndication/securitisation and loans mostly being floating and bonds mostly being fixed.
Convergent evolution in finance is actually a pet interest of mine. It seems like it's mostly driven by regulation. But the more you stare, the more the regulation appears like a canyon wall and the hydrology customs and connections. I'm not sure what the underlying geology is, however. Something bigger than customs or laws, but not so grand that it becomes ethereal.
The Banks get in trouble, and Gov has to step in. So Gov, reasonably, add regulations and restrictions. But the law can't be really specific, it requires gov employees to actually examine the bank and make decisions (eg about risk levels, etc).
The banks have a really large incentive to chip away at the effectiveness of the regulation. They hire lots of lawyers, consultants, notable economists, etc and just keep pushing on these rank and file gov regulators. They buy influence with politicians, and use that to pressure the regulators. They hire some of the regulators at very high pay, sending a signal to the others: play ball and a nice job awaits you.
Over time, they just wear down the regulators. The rules are interpreted to be mostly ineffective and nonsensical. Often at that point the politicians come in and just de-regulate.
The banks just have the incentive and focus to keep at it every day for years. No one else with power is paying attention.
I think Raymond Hettinger is called out specially here because he did a well known talk called [Modern Dictionaries](https://youtu.be/p33CVV29OG8) where around 32:00 to 35:00 in he makes the quip about how younger developers think they need new data structures to handle new problems, but eventually just end up recreating / rediscovering solutions from the 1960s.
“What has been is what will be, and what has been done is what will be done; there is nothing new under the sun.”
I think he was always reluctant to add features, and his version of Python would be slimmer, beautiful, and maybe 'finished'. His voice is definitely not guiding the contemporary Python development, which is more expansionist in terms of features.
Personally, I’ve been using a wrapper around `collections.namedtuple` as an underlying data structure to create frozen dictionaries when I’ve needed something like that for a project.
That works if you're dealing with a known set of keys (i.e. what most statically-typed languages would call a struct). It falls down if you need something where the keys are unknowable until runtime, like a lookup table.
I do like dataclasses, though. I find them sneaking into my code more and more as time goes on. Having a declared set of properties is really useful, and it doesn't hurt either that they're syntactically nicer to use.
The way Git computes diffs is by more or less storing all the source code in the .git directory as objects. At first glance it looks like a bunch of hashes, but tools can pull out source code from the objects tracked within the .git directory. Not least of which, the remote URL points to their username on GitHub and the author for commits can give you their email.
Not least of which, and even more so the URL had an auth secret in it. None of mine do, hence the question. I'm confused, because git has a credentials helper specifically designed to avoid storing secrets like that, or so I thought. So what tool is storing secrets in the git remote URL?
Yes, the git directory has all current and historical versions of the files packed into it, but that's not what the OP used to get information about the scammer.
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