dudeami0

Yea this is just syntax, every language does it a little different, most popular languages seem to derive off of C in some capacity. Some do it more different than others, and some are unholy conglomerations of unrelated languages that somehow works. Instead of saying why is this different, just ask how does this work. It’s made my life a lot simpler.

var test int is just int test in another language.

func (u User) hi () { ... } is just class User { void hi() { ... } } in another language (you can guess which language I’m referencing I bet).

map := map[string]int {} is just Map<String, Integer> map = new HashMap<>() in another (yes it’s java).

Also RTFM, this is all explained, just different!

Edit: I also know this is a very reductive view of things and there are larger differences, I was mostly approaching this from a newer developers understanding of things and just “getting it to work”.

Sadly it wasn’t a bid to open source the AI, rather than a bid for payment.

My question would be, why do you need a more powerful server? Are you monitoring your load and seeing it’s overloaded often? Are you just looking to be able to hook more drives to it? Do you need to re-encode video on the fly for other devices? Giving some more details would help someone to give a more insightful answer. I personally am using a Raspberry Pi 4, Chromebox w/ an i7, an old HP rack server, and an old desktop PC for my self hosting needs, as this is cheaper than buying all new hardware (though the electricity bill isn’t the greatest haha, but oh well). If you are just looking for more storage, using the USB 3.0 slots on the Raspberry Pi 4b you can add a couple extra SSDs using a NVMe to USB 3.0 enclosure. For most purposes the speeds will be fine for most applications.

As for SSD vs HDD, SSD hands down. The only reason you’d pick an HDD is if your trying to get more storage cheaper and don’t mind a higher rate of failure. If your data is at all valuable, and it almost always is, redundancy should be added as well.

And as for running Linux, if it can’t run Linux I wouldn’t want to own it.

Edit: Fixed typo

This might help, sorry if it doesn’t, but here is a link to CloudFlares 5xx error code page on error 521. If you’ve done everything in the resolution list your ISP might be actively blocking you from hosting websites, as it is generally against the ISPs ToS to do such on residential service lines. This is why I personally rent a VPS and have a wireguard VPN setup to host from the VPN, which is basically just a roll your own version of Tailscale using any VPS provider. This way you don’t need to expose anything via your ISPs router/WAN and they can’t see what you are sending or which ports you are sending on (other than the encrypted VPN traffic to your VPS of course).

A blockchain is just an verifiable chain of transactions using cryptography and some agreed upon protocol. Each “block” in the chain is a block of data that follows a format specified by the protocol. The protocol also decides who can push blocks and how to verify a block is valid. The advantages it has comes from the fact the protocol can describe a method of giving authority across a pool of untrusted third parties, while still making sure none of them can cheat. Currently the most popular forms are Proof of Work (PoW) and Proof of Stake (PoS).

Bitcoin for example is just an outgoing transaction to a specific crypto key (which is similar to a checking account) as a reward for “mining” the block, followed by a list of transactions going from a specific account to another account. These are verified by needing a special chunk of data that turns the overall hash of the entire block to a binary chunk containing a number of 0 bits in front, which makes it hard to compute and a race to get the right input data. This way of establishing an authority is called Proof of Work, and whoever is first and gets their block across the network faster wins. Other cryptocurrencies like Ethereum use Proof of Stake where you “stake” currency you’ve already acquired as a promise that you won’t cheat, and if someone can prove you cheated your stake is lost.

The problem it solves is not needing a trusted third party to handle this process, such as a government agency or an organization. Everyone can verify the integrity of a blockchain by using the protocol and going over each block, making sure the data follows the rules. This blockchain is distributed so everyone can make sure they are on the same chain, else it’s considered a “forked” chain and will migrate back to the point of consensus. This can be useful for situations where the incentive to cheat the system for monetary or political gain outweigh the cost of running a distributed ledger. It can also be useful when you don’t want anyone selectively removing past data as the chain of verifiability will be broken. The only issue with this is you need some way to reach a consensus of who gets to make each block in the chain, as someone need to be the authority for that instant in time. This is where the requirement of Proof of Work (PoS) or Proof of Stake (PoS) come in. Without these or another system that distributes the authority to create blocks, you lose the power of the blockchain.

Examples I’ve heard of are tracking shipments or parts (similar to how the FAA already mandates part traceability) and medical records. This way lots of organizations can publish records relating to these to a central system that isn’t under any single entities control, and can’t change their records to suit their needs.

These systems are not fool proof though, PoW has the ability to be abused using a 51% attack and PoS requires some form of punishment for trying to cheat the system (in cryptocurrency you “stake” currency and lose it if you try to cheat the system). Both of these run into issues when there is no incentive to invest resources into the system, a lack of distribution across independent parties, or one party has sufficient power to gain a majority control of the network.

Overall you are right to be skeptical of cryptocurrency, it’s been a long time since I participated due to the waves of scam coins and general focus on illegal activities such as gambling. The lack of central authorities also perpetuates the problem of cryptoscams, as anyone can start one and there are limited controls over stopping such scams. This is not dissimilar to previous investment scams though, it’s just the modern iteration of such scams. The real question is does it solve a real problem, as Bitcoin did in the sense it helps facilitate transactions outside of government controls. You might not agree with that but it does give it an intrinsic value to a large number of people looking to move currency without as much paperwork. Now if it makes it worth $68.5k USD (at current prices) is a different story, different people have different use cases and I only highlighted one of those.

I use my own router with DD-WRT in-between the ISPs router/modem and my LAN, and use a different subnet. I haven’t had any issues with this myself, and my router just sees the ISP router/modem as the WAN.

I’ve never ran this program, but skimmed the documentation. You should be able to use the SHIORI_DIR (or a custom database table following those instructions) along with the -p argument for launching the web interface. A simple bash script that should work:

export SHIORI_DIR=/path/to/shiori-data-dir
shiori serve -p 8081

To run multiple versions, I’d suggest setting up each instance as a service on your machine in case of reboots and/or crashes.

Now for serving them, you have two options. The first is just let the users connect to the port directly, but this is generally not done for outward facing services (not that you can’t). The second is to setup a reverse proxy and route the traffic through subdomains or subpaths. Nginx is my go-to solution for this. I’ve also heard good things about Caddy. You’ll most likely have to use subdomains for this, as lots of apps assume they are the root path without some tinkering.

Edit: Corrected incorrect cli arguments and a typo.

SQL is the industry standard for a reason, it’s well known and it does the job quite well. The important part of any technology is to use it when it’s advantageous, not to use it for everything. SQL works great for looking up relational data, but isn’t a replacement for a filesystem. I’ll try to address each concern separately, and this is only my opinion and not some consensus:

Most programmers aren’t DB experts: Most programmers aren’t “experts”, period, so we need to work with this. IT is a wide and varied field that requires a vast depth of knowledge in specific domains to be an “expert” in just that domain. This is why teams break up responsibilities, the fact the community came in and fixed the issues doesn’t change the fact the program did work before. This is all normal in development, you get things working in an acceptable manner and when the requirements change (in the lemmy example, this would be scaling requirements) you fix those problems.

translation step from binary (program): If you are using SQL to store binary data, this might cause performance issues. SQL isn’t an all in one data store, it’s a database for running queries against relational data. I would say this is an architecture problem, as there are better methods for storing and distributing binary blobs of data. If you are talking about parsing strings, string parsing is probably one of the least demanding parts of a SQL query. Prepared statements can also be used to separate the query logic from the data and alleviate the SQL injection attack vector.

Yes, there are ORMs: And you’ll see a ton of developers despise ORMs. They is an additional layer of abstraction that can either help or hinder depending on the application. Sure, they make things real easy but they can also cause many of the problems you are mentioning, like performance bottlenecks. Query builders can also be used to create SQL queries in a manner similar to an ORM if writing plain string-based queries isn’t ideal.

“From March 1, 2024, an order will come into force to block VPN services providing access to sites banned in Russia,” Sheikin was quoted as saying by state news agency RIA.

I assume this means it’s regarding outgoing communications, for censorship purposes most likely. I’d be surprised if they were blocking incoming VPN traffic, and I don’t think the Russian government has an issue with Yandex operating.

For your own sanity, please use a formatter for your IDE. This will also help when others (and you) read the code, as indentation is a convenience for understanding program flow. From what I see:

• Your enable and disable functions are never called for this portion of code
• You use a possibly undeclared enabled variable, if so it never passes scopes between the handleClick and animation methods
• You do not use any callback or await for invoke or updateCurrentBox, causing all the code after either to immediately run. As a result, enabled is never false, since it just instantly flips back to true. I’m not sure what library invoke is from, but there should be a callback or the function returns a Promise which can be awaited.

You can add streamlink-ttvlol with one of the known compatible proxies to remove the ads. Works great for me.

Also if there are issues with VLC crashing, I recommend MPV as it handles malformed stream data a little better. VLC will work great 99% of the time on twitch though.

Also, any plugin that Twitch doesn’t like (for example TTV LOL) is detected and will prevent a log in. You’ll need to disable the plugin to login, but can use it after logging in.

In my humble opinion, we too are simply prediction machines. The main difference is how efficient our brains are at the large number of tasks given for it to accomplish for it’s size and energy requirements. No matter how complex the network is it is still a mapped outcome, just the number of factors weighed is extremely large and therefore gives a more intelligent response. You can see this with each increment in GPT models that use larger and larger parameter sets giving more and more intelligent answers. The fact we call these “hallucinations” shows how effective the predictive math is, and mimics humans abilities to just make things up on the fly when we don’t have a solid knowledge base to back it up.

I do like this quote from the linked paper:

As we will discuss, we find interesting evidence that simple sequence prediction can lead to the formation of a world model.

That is to say, you don’t need complex solutions to map complex problems, you just need to have learned how you got there. It’s never purely random attempts at the problem, it’s always predictive attempts that try to map the expected outcomes and learn by getting it right and wrong.

At this point, it seems fair to conclude the crow is relying on more than surface statistics. It evidently has formed a model of the game it has been hearing about, one that humans can understand and even use to steer the crow’s behavior.

Which is to say that it has a predictive model based on previous games. This does not mean it must rigidly follow previous games, but that by playing many games it can see how each move affects the next. This is a simpler example because most board games are simpler than language with less possible outcomes. This isn’t to say that the crow is now a grand master at the game, but it has the reasoning to understand possible next moves, knows illegal moves, and knows to take the most advantageous move based on it’s current model. This is all predictive in nature, with “illegal” moves being assigned very low probability based on the learned behavior the moves never happen. This also allows possible unknown moves that a different model wouldn’t consider, but overall provides what is statistically the best move based on it’s model. This allows the crow to be placed into unknown situations, and give an intelligent response instead of just going “I don’t know this state, I’ll do something random”. This does not always mean this prediction is correct, but it will most likely be a valid and more than not statistically valid move.

Overall, we aren’t totally sure what “intelligence” is, we are just an organism that has developed more and more capabilities to process information based on a need to survive. But getting down to it, we know neurons take inputs and give outputs based on what it perceives is the best response for the given input, and when enough of these are added together we get “intelligence”. In my opinion it’s still all predictive, its how the networks are trained and gain meaning from the data that isn’t always obvious. It’s only when you blindly accept any answer as correct that you run into these issues we’ve seen with ChatGPT.

Thank you for sharing the article, it was an interesting article and helped clarify my understanding of the topic.

Disclaimer: I am not an AI researcher and just have an interest in AI. Everything I say is probably jibberish, and just my amateur understanding of the AI models used today.

It seems these LLM’s use a clever trick in probability to give words meaning via statistic probabilities on their usage. So any result is just a statistical chance that those words will work well with each other. The number of indexes used to index “tokens” (in this case words), along with the number of layers in the AI model used to correlate usage of these tokens, seems to drastically increase the “intelligence” of these responses. This doesn’t seem able to overcome unknown circumstances, but does what AI does and relies on probability to answer the question. So in those cases, the next closest thing from the training data is substituted and considered “good enough”. I would think some confidence variable is what is truly needed for the current LLMs, as they seem capable of giving meaningful responses but give a “hallucinated” response when not enough data is available to answer the question.

Overall, I would guess this is a limitation in the LLMs ability to map words to meaning. Imagine reading everything ever written, you’d probably be able to make intelligent responses to most questions. Now imagine you were asked something that you never read, but were expected to respond with an answer. This is what I personally feel these “hallucinations” are, or imo best approximations of the LLMs are. You can only answer what you know reliably, otherwise you are just guessing.

Season 8 on more torrents is probably considered to be the new hulu reboot. This is due to the disparity in the home release seasons and the television TV seasons. So most likely if you have seasons 1-7, you have all the home release versions of the show, and therefore have the entire library.

Sounds like some QoS software is also limiting LAN traffic, seeing as it still works if the internet is disconnected. I would look if your router has “Adaptive QoS” or something similar enabled.

In most setups I have seen, the nginx instance provided by Lemmy is used due to the routing needed between lemmy/lemmy-ui being handled in nginx. Your reverse proxy can then point to the nginx instance to expose lemmy.

Why not a Raspberry Pi? The supply chain issues are clearing up.

In the US it seems the supply chain issues are alive as ever. Most of the official resellers are sold out on anything but the Pico and Zero boards. Some do have 4B boards for sale if you buy their starter kit with them, increasing the price by $65 on canakit. The supply issues are definitely not resolved for home users no matter what the CEO wants to say.

The numbers are a little higher than you mention (currently ~3.2k active users). The server isn’t very powerful either, it’s now running on a dedicated server with 6 cores/12 threads and 32 gb ram. Other public instances are using larger servers, such as lemmy.world running on a AMD EPYC 7502P 32 Cores “Rome” CPU and 128GB RAM or sh.itjust.works running on 24 cores and 64GB of RAM. Without running one of these larger instances, I cannot tell what the bottleneck is.

The issues I’ve heard with federation are currently how ActivityPub is implemented, and possibly the fact all upvotes are federated individually. This means every upvote causes a federation queue to be built, and with a ton of users this would pile up fast. Multiply this by all the instances an instance is connected to and you have an exponential increase in requests. ActivityPub is the same protocol used by other federated servers, including Mastodon which had growing pains but appears to be running large instances smoothly now.

Other than that, websockets seem to be a big issue, but is being resolved in 0.18. It also appears every connected user gets all the information being federated, which is the cause for the spam of posts being prepended to the top of the feed. I wouldn’t be surprised if people are already botting content scrapers/posters as well, which might cause a flood of new content which has to get federated which causes queues to back up; this is mostly speculation though.

As it goes with development, generally you focus on feature sets first. Optimization comes once you reach a point a code-freeze makes sense, then you can work on speeding things up without new features breaking stuff. This might be an issue for new users temporarily, but this project wasn’t expecting a sudden increase in demand. This is a great way to show where inefficiencies are and improve performance is though. I have no doubt these will be resolved in a timely manner.

My personal node seems to use minimal resources, not having even registered compared to my other services. Looking at the process manager the postgres/lemmy backend/frontend use ~250MB of RAM.

For now, staying off lemmy.ml and moving communities to other instances is probably best. The use case of large instances anywhere near the scale of reddit wasn’t the goal of the project until reddit users sought alternatives. We can’t expect to show up here and demand it work how we want without a little patience and contributing.

I currently am running the instance I am responding from on kubernetes. I published a helm chart, and others are working on them too. I feel being able to quickly deploy a kubernetes instance will help a lot of smaller instances pop up, and eventually be a good method of handling larger instances once horizontal scaling is figured out.