If someone had said, "I am generally not opposed to regulation, but this is a place where I don't support it.", you could have replied to it in a similar fashion, but reversed.
What's the conservative best practice for a solo founder (a one person company; assume the person spends ~20 hours per week on software development/maintenance and the rest of the time on other stuff)?
The main issue here is not UX, but rather that you did something which degraded quality without transparency. You should have documented this and also highlighted the change in an announcement. There should never be an undocumented change that reduces quality. There should never be something the user can do (or fail to do) that reduces quality without that being documented. To regain trust, Anthropic should make an announcement committing to documenting/announcing any future intentional quality-reducing changes.
In addition, the following is less important, but as other commenters have stated: walking away from a conversation and coming back to it more than an hour later is very common and it would be nice if there were a way for the user to opt to retain maximum quality (e.g. no dropped thinking) in this case. In the longer term, it would be nice if there were a way for the user to wait a few minutes for a stale session to resume, in exchange for not having a large amount of quota drained (ie have a 'slow mode' invoked upon session resumption that consumes less quota).
Note that inventory already in Amazon fulfillment centers as of March 31, 2026 is still commingled
"Also what happens after March 31st with the leftover commingled inventory that’s already there?
No action is required for stickerless inventory currently in-transit to or stored in our fulfillment centers. These products will continue to sell under their original SKUs.
Since they were on a boat with a Raspberry Pi and not much battery power or internet, in addition to execution speed and portability, they were probably also concerned with:
- speed of compilation and linking (on small machines like Raspberry Pi)
- binary size of anything that might have to be updated or shared over the internet
- having to troubleshooting emergent issues without the ability to lookup documentation or download updates or tools from the internet
In this situation, a simpler language on a simpler VM is probably going to be faster to develop with than compiling/linking a subset of C, and after the initial implementation of the VM, might present less opportunity for an unintended interaction of leaky abstractions in your libuxn and your toolchain to ruin your day on a day when you don't have internet connectivity to check Stackoverflow or to update some buggy dependency.
Yes, I think it's very possible that human brains unconsciously generate-and-test surprisingly large numbers of small candidate programs when solving a problem.
This approach is https://en.wikipedia.org/wiki/Embarrassingly_parallel, which is a good fit for biological neural architectures, which have very many computing nodes but each node is very slow (compared to electronic computer CPUs/GPUs).
The first thing to do is to put LLMs to work to generate large knowledge bases of commonsense knowledge in symbolic machine-readable formats that Cyc-like projects can consume.
I don't understand why an Income Sharing Agreement would be classified as loans. They seem more like equity than debt; the amount that students would pay depends on their future income, and can be arbitrarily small or large (right? or maybe I am misunderstanding the terms of these agreements).
I had thought that debt is when you have to pay back at least the "principal" no matter what, and equity is when the financier shares the risk of you failing. Maybe that's not correct, though?
Does the definition of a "loan" include any sort of financing, even if the amount that needs to be "paid back" to the "lender" can be arbitrarily small or large? That would make equity financing a special case of debt.
Even if other users (or possibly, sock puppets of the attacker) had not been complaining, the original maintainer probably would have began to trust the attacker after enough real contributions.
This thesis provides empirical support that a specific measure of software architectural complexity is costly. Specifically, they look thru source code in an automated manner, construct the graph whose nodes are source code files and whose edges are the following cross-file relationships (page 73, section 5.1.2.1):
- The site of function calls to the site of the function's definition
- The site of class method calls to the site of that class method's definition
- The site of a class method definition to the site of the class definition
- The site of a subclass definition to the site of its parent class' definition
- The site at which a variable with a complex user-defined type is instantiated or accessed to the site where that type is defined. (User-defined types include structure, union, enum, and class.)
Then they compute the transitive closure of this graph.
Then they compute two metrics for each node by looking at the transitive closure graph (page 76, section 5.1.2.3):
- Visibility Fan In (VFI): how many other nodes have edges that go from the other node to this node?
- Visibility Fan Out (VFO): how many other nodes have edges that go from this node to the other node?
They observe that by looking at the VFI metric across various files, files tend to sharply cluster into either 'low VFI' or 'high VFI', and similarly for VFO (although some files may be high in one metric and low in the other) (page 79, section 5.1.3).
They then classify each file as:
- low VFI, low VFO: 'peripheral'
- high VFI, low VFO: 'utility'
- low VFI, high VFO: 'control'
- high VFI, high VFO: 'core'
They then find that 'core' files are the most costly, in terms of defect density, developer productivity, and probability of staff turnover.
The university system is a mechanism to fund public goods. The problem is the professors are judged according to their production of novel knowledge, and maintaining useful software does not produce novel knowledge. We should endow chairs of "open-source professors", who are judged according to their production/maintenance of useful software, in order to re-use the infrastructure of the university system to fund this other type of public good.
Describes the motivations for and design of a massively parallel computer with many (millions? 64k?) of very simple processing nodes that serve as both memory and CPU. Shows how you can have "active data structures" where each item of data is in a different CPU (or clusters of nearby CPUs) and literally migrates between CPUs as computation proceeds. I think it gives an example of the parallel bitonic sort algorithm being executed in this way. A relatively thin book and relatively easy to read for a programmer.
You could probably make everyone happy just by copying that text to the top of the landing page, as an additional paragraph just above where the "Current progress" button is, right after "..ensure clean and correct multi-threaded designs."
This paper might be of interest: David Harel, Guy Katz, Rami Marelly, Assaf Marron. Wise Computing: Towards Endowing System Development with True Wisdom https://arxiv.org/abs/1501.05924
It describes an idea called "wise computing" or "behavioral programming" which i'm not sure that i fully understand, but it sounds like the idea is to allow IDEs to help more, via additional formal reasoning about code in the manner of an expert system AI.
Has there been any progress in software to allow individual unaffiliated volunteers to help make decentralized third-party backups of the Internet Archive's WWW Wayback machine data?
My opinion is that it may be difficult to find enough volunteer storage to fit the entire Archive, but if we focus on prioritizing plaintext HTML, plus perhaps graphics included in web pages constrained to a size limit, we can do it.
- list memory right-to-left so the lowest memory address is on the right and the highest is on the left (i guess i prefer this solution because it's compatible with the convention of the least-significant-bit being the rightmost bit, which is enshrined in the name of "right shift", and with the convention of the least-significant-bit being bit 0, which makes sense in formulas like "value = sum_digitindex digit[digitindex]*radix^digitindex")
or you could
- write hexadecimal values with the most-significant-digit on the right, so the byte 2 followed by the byte 10 (in decimal notation) would be written 20 A0 instead of 02 0A.
I don't know if popular hex dump programs have switches for either of those, though?
Your point about bit shifts is good, too. If the rightmost bit is the least-significant bit, then for consistency perhaps memory should be written with the lowest memory address on the right. Then 0xDEADBEEF makes sense both in terms of bytes within the value and bits within the byte; the first 4 bits within the lowest byte in memory are F, then next 4 bits within the lowest byte are E, the first four bytes within the second-to-lowest byte are E, the next 4 bits within the second-to-lowest byte are B, etc. So if 0xDEADBEEF were stored in little-endian, a hex editor could display DE AD BE EF