Please explain what you mean by “rotate”. The thermostat is physically turning in-place, as though a wall clock?

One way to make this more Pythonic – and less C or POSIX-oriented – is to use the pathlib library for all filesystem operations. For example, while you could open a file in a contextmanager, pathlib makes it really easy to read a file:

from pathlib import Path
...

config = Path("/some/file/here.conf").read_text()

This automatically opens the file (which checks for existence), reads out the entire file as a string (rather than bytes, but there’s a method for that too), and then closes up the file. If any of those steps go awry, you get a Python exception and a backtrace explaining exactly what happened.

To many of life’s either-or questions, we often struggle when the answer is: yes. That is to say, two things can hold true at the same time: 1) LLMs can result in job redundancies, and 2) LLMs hallucinate results.

But if we just stopped the analysis there, we wouldn’t have learned anything. To use this reality to terminate any additional critical thinking is, IMO, wholly inappropriate for solving modern challenges, and so we must look into the exact contours of how true these statements are.

To wit, LLM-induced job redundancies could come from skills which have been displaced by the things LLMs can do well. For example, typists lost their jobs when businesspeople were expected to operate a typewriter on their own. And when word processing software came into existence for the personal computer, a lot of typewriter companies folded or were consolidated. In the case of LLMs, consider that people do use them to proofread letters for spelling and grammar.

Technologically, we’ve had spell-check software for a while, but grammar was harder. In turn, an industry appeared somewhere in the late 2000s or early 2010s to develop grammar software. Imagine how the software devs at these companies (eg Grammarly) might be in a precarious situation, if an LLM can do the same work. At least with grammar checking, even the best grammar software still struggles with some of the more esoteric English sentence constructions, so if an LLM isn’t 100% perfect, that’s still acceptable. I can absolutely see the fortunes of grammar software companies suffering due to LLMs, and that means those software devs are indeed threatened by what LLMs can do.

For the second statement, it is trivial to find examples of LLMs hallucinating, sometimes spectacularly or seemingly ironic (although an LLM would be hard-pressed to simulate the intention of irony, I would think). In some fields, such hallucinations are career-limiting moves for the user, such as if an LLM was used to advise on pharmaceutical dosage, or used to draft a bogus legal appeal and the judge is not amused. This is very much a FAFO situation, where somehow the AI/LLM companies are burdened with none of the risk and all of the upside. It’s like how autonomous driving automotive companies are somehow allowed to do public road tests of their beta-quality designs, but the liability for crashes still befalls the poor sod seated behind the wheel. Thoss companies just keep yapping about how those crashes are all “human error” and “an autonomous car is still safer”.

But I digress.

My point is that LLMs have quite a lot of capabilities, and people make a serious mistake when they assume its incompetence in one capacity reflects its competency in another. This is not unlike how humans assess other humans, such as how a record-setting F1 driver would probably be a very good chauffeur for a limousine company. But whereas humans have patterns that suggest they might be good (or bad) at something, LLMs are a creature unlike anything else.

I personally am not bullish on additional LLM improvements, and think the next big push will require additional academic research, being nowhere near commercialization. But even I have to recognize that some very specific tasks are decent using today’s availabile LLMs. I just don’t think that’s good enough for me to consider using them, given their subscription costs, the possibility of becoming dependent, and being too niche.

Using an MSP430 microcontroller, I once wrote an assembly routine that (ab)used its SPI peripheral in order to stream a bit pattern from memory out to a GPIO pin, at full CPU clock rate, which would light up a “pixel” – or blacken it – in an analog video signal. This was for a project that superimposed an OSD onto the video feed of a dashcam, so that pertinent vehicle data would be indelibly recorded along with the video. It was for one heck of a university project car.

To do this, I had to study the MSP430 instruction timings, which revealed that a byte could be loaded from SRAM into the SPI output register, then a counter incremented, then a comparison against a limit value in a tight loop, all within exactly 8 CPU cycles. And the SPI completes an 8-bit transfer every 8 SPI clock cycles, but the CPU and SPI blocks can use the same clock source. In this way, I can prepare a “frame buffer” of bits to write to the screen – plenty of time during the vertical blanking interval of analog video – and then blast it atop the video signal.

I think I ended up running it at 8 MHz, which gave me sufficient pixel resolution on a 480i analog video signal. Also related was the task of creating a set of typefaces which would be legible on-screen but also be efficient to store in the MSP430’s limited SRAM and EEPROM memories. My job was basically done when someone else was able to use printf() and it actually displayed text over the video.

This MSP430 did not have a DMA engine, and even if it did, few engines permit an N-to-1 transaction to write directly to the SPI output register. Toggling the GPIO register directly was out of the question, due to taking multiple clock cycles to toggle a single bit and load the next value. Whereas my solution was a sustained 1 bit per clock cycle at 8 MHz. All interrupts disabled too, except for the vertical and horizontal blanking intervals, which basically dictated the “thinking time” available for the CPU.

For a single password, it is indeed illogical to distribute it to others, in order to prevent it from being stolen and misused.

That said, the concept of distributing authority amongst others is quite sound. Instead of each owner having the whole secret, they only have a portion of it, and a majority of owners need to agree in order to combine their parts and use the secret. Rather than passwords, it’s typically used for cryptographically signing off on something’s authenticity (eg software updates), where it’s known as threshold signatures:

Imagine for a moment, instead of having 1 secret key, you have 7 secret keys, of which 4 are required to cooperate in the FROST protocol to produce a signature for a given message. You can replace these numbers with some integer t (instead of 4) out of n (instead of 7).

This signature is valid for a single public key.

If fewer than t participants are dishonest, the entire protocol is secure.

Related to moderation are the notions of procedural fairness, including 1) the idea that rules should be applied to all users equally, that 2) rules should not favor certain users or content, and 3) that there exists a process to seek redress, to list a few examples. These are laudable goals, but I posit that these can never be 100% realized on an online platform, not for small-scale Lemmy instances nor for the largest of social media platforms.

The first idea is demonstrably incompatible with the requisite avoidance of becoming a Nazi bar. Nazis and adjoining quislings cannot be accommodated, unless the desire is to become the next Gab. Rejecting Nazis necessarily treats them different than other users, but it keeps the platform alive and healthy.

The second idea isn’t compatible with why most people set up instances or join a social media platform. Fediverse instances exist either as an extension of a single person (self-hosting for just themselves) or to promote some subset of communities (eg a Minnesota-specific instance). Meanwhile, large platforms like Meta exist to make money from ads. Naturally, they favor anything that gets more clicks (eg click bait) than adorable cat videos that make zero revenue.

The third idea would be feasible, except that it is a massive attack vector: unlike an in-person complaints desk, even the largest companies cannot staff – if they even wanted to – enough customer service personnel to deal with a 24/7 barrage of malicious, auto-generated campaigns that flood them with invalid complaints. Whereas such a denial-of-service attack against a real-life complaints desk would be relatively easy to manage.

So once again, social media platforms – and each Fediverse instance is its own small platform – have to make some choices based on practicalities, their values, and their objectives. Anyone who says it should be easy has not looked into it enough.

Reddit has global scope, and so their moderation decisions are necessarily geared towards trying to be legally and morally acceptable in as many places as possible. Here is Mike Masnick on exactly what challenges any new social media platform faces, and even some which Lemmy et al may have to face in due course: https://www.techdirt.com/2022/11/02/hey-elon-let-me-help-you-speed-run-the-content-moderation-learning-curve/ . Note: Masnick is on the board of BlueSky, since it was his paper on Protocols, Not Platforms that inspired BlueSky. But compared to the Fediverse, BlueSky has not achieved the same level of decentralization yet, having valued scale. Every social media network chooses their tradeoffs; it’s part of the bargain.

The good news is that the Fediverse avoids any of the problems related to trying to please advertisers. The bad news is that users still do not voluntarily go to “the Nazi bar” if they have any other equivalent option. Masnick has also written about that when dealing at scale. All Fediverse instances must still work to avoid inadvertently becoming the Nazi bar.

But being small and avoiding scaling issues is not all roses for the Fediverse. Not scaling means fewer resources and fewer people to do moderation. Today, most instances range from individual passion projects to small collectives. The mods and admins are typically volunteers, not salaried staff. A few instances have companies backing them, but that doesn’t mean they’d commit resources as though it were crucial to business success. Thus, the challenge is to deliver the best value to users on a slim budget.

Ideally, users will behave themselves on most days, but moderation is precisely required on the days they’re not behaving.

Used for AI, I agree that a faraway, loud, energy-hungry data center comes with a huge host of negatives for the locals, to the point that I’m not sure why they keep getting building approval.

But my point is that in an eventual post-bubble puncture world where AI has its market correction, there will be at least some salvage value in a building that already has power and data connections. A loud, energy-hungry data center can be tamed to be quiet and energy-sipping based on what’s hardware it’s filled in. Remove the GPUs and add some plain servers and that’s a run-of-the-mill data center, the likes of which have been neighbors to urbanites for decades.

I suppose I’d rehash my opinion as such: building new data centers can be wasteful, but I think changing out the workload can do a lot to reduce the impacts (aka harm reduction), making it less like reopening a landfill, and more like rededicating a warehouse. If the building is already standing, there’s no point in tearing it down without cause. Worst case, it becomes climate-controlled paper document storage, which is the least impactful use-case I can imagine.

Racks/cabinets, fiber optic cables, PDUs, CAT6 (OOBM network), top-of-rack switches, aggregation switches, core switches, core routers, external multi-homed ISP/transit connectivity, megawatt three-phase power feeds from the electric utility, internal power distribution and step-down transformers, physical security and alarm systems, badge access, high-strength raised floor, plenum spaces for hot/cold aisles, massive chiller units.

Absolutely, yes. I didn’t want to elongate my comment further, but one odd benefit of the Dot Com bubble collapsing was all of the dark fibre optic cable laid in the ground. Those would later be lit up, to provide additional bandwidth or private circuits, and some even became fibre to the home, since some municipalities ended up owning the fibre network.

In a strange twist, the company that produced a lot of this fibre optic cable and went bankrupt during the bubble pop – Corning Glass – would later become instrumental in another boom, because their glass expertise meant they knew how to produce durable smartphone screens. They are the maker of Gorilla Glass.

I’m not going to come running to the defense of private equity (PE) firms, but compared to so-called AI companies, the PE firms are at least building tangible things that have an ostensible alternative use. A physical data center building – even one located far away from the typical metropolitan area that have better connectivity to the world’s fibre networks – will still be an asset with some utility, when/if the AI bubble pops.

In that scenario, the PE firm would certainly take a haircut on their investment, but they’d still get something because an already-built data center will sell for some non-zero price, with possible buyers being the conventional, non-AI companies that just happen to need some cheap rack space. Looking at the AI companies though, what assets do they have which carry some intrinsic value?

It is often said that during the California Gold Rush, the richest people were not those which staked out the best gold mining sites, but those who sold pickaxes to miners. At least until gold fever gave way to sober realization that it was overhyped. So too would PE firms pivot to whatever comes next, selling their remaining interest from the prior hype cycle and moving to the next.

I’ve opined before that because no one knows when the bubble will burst, it is simultaneously financially dangerous to: 1) invest into that market segment, but also 2) to exit from that market segment. And so if a PE firm has already bet most of the farm, then they might just have to follow through with it and pray for the best.

I presume we’re talking about superconductors; I don’t know what a supra (?) conductor would be.

There are two questions here: 1) how much superconducting materials are required for today’s state-of-the-art quantum computers , and 2) how quantum computers would be commercialized. The first deals in material science and whether more-capable superconductors can be developed at scale, ideally for room-temperature and thus wouldn’t require liquid helium. Even a plentiful superconductor that merely requires merely liquid nitrogen would he a bit improvement.

But the second question is probably the limiting factor, because although quantum computers are billed as the next iteration of computing, the fact of the matter is that “classical” computers will still be able to do most workloads faster than quantum computers, today and well into the future.

The reality is that quantum computers excel at only a specific subset of computational tasks, which classically might require mass parallelism. For example, breaking encryption algorithms is one such task, but even applying Shoe’s Algorithm optimally, the speed-up is a square-root factor. That is to say, if a cryptographic algorithm would need 2^128 operations to brute-force on a classical computer, then an optimal quantum computer would only need 2^64 quantum operation. If quantum computers achieve the equivalent performance of today’s classical computers, then 2^64 is achievable, so that cryptographic algorithm is broken.

If. And it’s kinda easy to see how to avoid this problem: use “bigger” cryptographic algorithms. So what would quantum computers be commercialized for? Quite frankly, I have no idea: until such commonly-available quantum computers are available, and there is a workload which classical computers cannot reasonably do, then there won’t be a market for quantum computers.

If I had to guess, I imagine that graph theorists will like quantum computers, because graphs can increase in complexity really fast on classical machines, but is more tame on quantum computers. But the only commercial applications from that would be for social media (eg Facebook hires a lot of graph theorists) and surveillance (finding correlations in masses of data). Uh, those are not wide markets, although they would have deep pockets to pay for experimental quantum computers.

So uh, not much that would benefit the average person.

Weather station, terrestrial/satellite TV DVR (TVHeadend), Git repository (Forgejo for a nice web UI, cgit for a classic UI), DNS resolver.

If the town is Bielefeld in Germany, then at the Old Market square. But that city doesn’t exist.

I see my typo, and it’s too funny and I’m just going to roll with it haha

As a practical matter, relative directions are already hard enough, where I might say that Colorado is east of California, and California is west of Colorado.

To use +/- East would mean there’s now just a single symbol difference between relative directions. California bring -East of Folorado, and Colorado being +East of California.

Also, we need not forget that the conventional meridian used for Earth navigation is centered on Greenwich in the UK, and is a holdover from the colonial era where Europe is put front-and-center on a map and everything else is “free real estate”. Perhaps if the New World didn’t exist, we would have right-ascension based system where Greenwich is still 0-deg East and Asia is almost 160-deg East. Why would colonialists center the maps on anywhere but themselves?

Assuming this is in the USA, I want to note that there are many other available jobs in the protective services occupation, that can be public or private sector, that face the general public (or not), and that don’t have any particular positive or negative connotation attached to the job, even after hours.

The Bureau of Labor Statistics (BLS) has a fantastic reference for available occupations:

https://www.bls.gov/ooh/protective-service/home.htm

Citizens != Their Government != The State

This is a fundamental proposition, even in a semi-functional democracy where the citizens elect the government.

I’m not any sort of expert in the laws of Canada, but having tourists come into the country and spend money, buy goods, form interpersonal relationships, and otherwise not be levying war against Ottawa nor the several provinces, that does not sound like any sort of definition of treason, whether in law or in casual usage of that word.

American tourists to Canada are explicitly rejecting spending that same money domestically at American tourist attractions, and are going to Canada to spend it instead. In times where the USA is battering its northern neighbor, I feel like the visiting tourists are coming as allies, not enemies.

But I defer to Canadians about how they feel, and pass no judgement from here in California.

Block, ignore, and continue living your non-bot life.

Restaurants (including franchises of chains) are indeed a major segment of small businesses. Looking more broadly, any industry which: 1) offers a service/product/utility, and 2) has proven to not have a tendency to inflate beyond its fundamental target audience, those are likely to be small businesses. Those are the parameters which stave off any sort of corporate takeovers and consolidations, because they won’t invest in a small business if the prospect of infinite growth isn’t there. So the business stays small. And small is often perfectly fine.

That is to say, restaurants (humans can only eat so much food), bicycle stores (humans can only ride so much per day), and local produce shops (even in the Central Valley of California, there’s only so much produce to sell, and humans can’t eat infinite quantities) have these qualities.

But compare those to a restaurant supply warehouse or music equipment store, since those items can be shipped and need no customization by the end user. Consolidation and corporate meddling is possible and probable.

Then you have industries which are often local and small but are prone to financial hazards, such as real estate agents and used car lenders. Because they get paid as a percentage of the transaction size, if the price of houses or cars go up in an unchecked fashion, the profit margins also increase linearly, which makes them more tempting for corporate involvement.

There are corporate-owned national chains of real estate agents, self storage, department stores, and payday loan offices in the USA. But I’m not aware of a national chain for bicycle or bicycle accessories. Even regional chains for bicycles are few and far between. Some consolidation has happened there, but by most definitions, a bicycle shop is very much a small business.