I've found wood screws work well for this. The wood screw can cut its own threads without needing to use a tap.

It does put some stress on the part, though. I mostly print in PETG, which is strong enough; but PLA might split if the hole was parallel to the layers.

> A design limitation of threaded inserts is that they are not reliably usable for screws inserted from the back side. During insertion, heat-set inserts often push some molten plastic into the hole beneath them, preventing easy insertion of a screw from the back side.

A trick I sometimes use:

1. Before installing the insert, insert the screw from the back side

2. Screw the insert onto the protruding screw

3. Use a soldering iron to install the insert+screw together into the plastic

Because the screw is filling the hole, the molten plastic can't block the hole. Instead, the molten plastic forms itself around the screw, and it acts like a Nyloc nut.

That doesn't sound right...? Credit/debit card chargebacks are handled by the bank. If the merchant doesn't pick up the phone, the bank will take the money from the merchant and return it to the customer.

https://www.usatoday.com/money/blueprint/credit-cards/credit...

Were you using a different payment system with fewer consumer protections than credit/debit cards?

No, that's not the _only_ fair way. Suppose the $2B creditor bids $200M in cash and also agrees to forfeit their share of the proceeds from the sale. Then the $1B creditor would receive the entire $200M, which is more than the $167M they would have received from a $500M cash sale. The bid is effectively equivalent to $600M.

Isn't that what happened in the InfoWars case? The bankruptcy judge agreed that the structure of the Onion's bid was valid; he just said the auction would have continued for more rounds.

(Also: If T=0, then β would be undefined/infinity. This corresponds to the fact that absolute zero temperature is impossible. β is arguably a more natural way of thinking about temperature than T is.)

To get a true sense of scale, here's the same view on Google Earth: https://earth.google.com/web/@44.48152905,11.33820409,94.604... You can see the towers that are still standing. They visibly stick out from the shorter buildings, but they're nowhere near as big as in the picture.

Some general tips for algorithmic complexity in Python:

- Python's list is equivalent to C++ std::vector. If you need to push/pop at the head of the list, use Python's "collections.deque" to avoid the O(N) cost. Python's standard library doesn't have a linked list implementation.

- Python's dict is a fast unordered hashmap. However, if you need order-aware operations like C++'s std::map::lower_bound(), you're out of luck; Python's standard library doesn't have a tree implementation.

- Python has a "bisect" module for binary searching in a Python list, and a "heapq" module for using a Python list as a heap. However, neither one is nicely encapsulated in a data type.

If your Python program is seriously CPU-bound, the normal solution is to use a C/C++/Rust extension. For example, if you're doing large numeric calculations, use NumPy; it can store a vector of numbers as a single contiguous array, which is much faster than a list-of-Python-floats.

If you want to parallelize across CPU cores, it's important to understand the Python GIL (global interpreter lock). Often you need to use multiple Python processes. See e.g. https://superfastpython.com/multiprocessing-pool-gil/

Maybe also worth reading about __slots__ (https://wiki.python.org/moin/UsingSlots); it's a micro-optimization that helps when allocating a lot of tiny Python objects.

Hope some of that is helpful! Good luck with your job interviews.

The general public pays enough money to pay the artists' salaries, plus the marketing budget and all the other costs. Otherwise Hollywood would go out of business.

> There's an endless continuum libraries, languages, tools and machines out there which have trivial impact on the world but are absolute objects of beauty when you know what's inside.

Imagine if the SF MOMA were replaced with a museum full of those niche libraries and languages, showing these absolute objects of beauty to the general public, and (implicitly) saying "you ought to appreciate the beauty; if you can't appreciate e.g. the beauty of the Haskell programming language is, you're ignorant".

The "high art" world, on the other hand, fetishizes the original physical work of art. If an expert painter spends weeks on a painting, then they must sell it for enough money to cover "weeks of an expert's income"; so of course only wealthy people will be able to afford it. How is this price more "appropriate" than the prices that non-wealthy people pay?

I've heard the cache is the biggest part. Per https://en.wikipedia.org/wiki/Apple_A17, the A17 has 72MB of cache. Cache is typically SRAM. Per https://en.wikipedia.org/wiki/Static_random-access_memory, a single bit of SRAM typically uses 6 transistors, but it could be anywhere from 4 to 10. So that's between 2.3B and 5.7B transistors for the cache.

That leaves about 1B transistors for each of the 12 cores (6 CPU + 6 GPU). The instruction set is a few hundred instructions. Surely it doesn't take millions of transistors to implement each instruction. Other than the cache, which parts of the processor need millions of transistors?

etymology: "the punch probably so called for resemblance to the wide swinging stroke of a scythe"

DC AG Karl Racine filed a lawsuit over this in May 2021. The judge threw it out, supposedly for lack of evidence that it actually raised prices: https://www.jurist.org/news/2022/03/dc-trial-court-dismisses... I can't find details; it's unclear what the evidence or lack thereof was.

CA AG Rob Bonta filed another lawsuit over the same issue in Sept 2022. Some juicy quotes here (although only one side of the story): https://oag.ca.gov/news/press-releases/attorney-general-bont... The CA lawsuit is set to go to trial in 2026.

People would submit fewer applications, but each individual application would have a higher chance of success, because everyone else would _also_ be submitting fewer applications. The number of job openings is the same either way, so the same number of people get hired in the end, right?