dudeami0

To add to this spending some time in custody is inconvenient, but losing your rights being convicted of something you didn’t even do is more inconvenient. You think you know what to say until you say the wrong thing and start digging a hole.

This is good to know, but adds an additional step to simply requiring a passcode to unlock on screen lock.

Just the act of refusing makes the act of seizing your phone legal or not. If you legally give them your phone by your own will, they are able to use all evidence they find in the courts. If you deny to give them your phone, and they seize it anyways and access it you have a valid path to throw the evidence they discover out as an illegal search and seizure of your property. I’m not a lawyer but that is the general thought process on denying them access to your property.

Edit: Just want to say this mostly pretains to United States law and similar legal structures. This advice is not applicable everywhere and you should research your countries rights and legal protections.

I personally rather trust that my device isn’t able to be unlocked without my permission, rather than hope I am able to do some action to disable it in certain situations. The availability of such features is nice, but I would assume I would be incapable of performing such actions in the moment.

My other thought is, how guilty is one perceived if they immediately attempt to lock their phones in such a matter, by a jury of their peers? I rather go the deniability route of I didn’t want to share my passcode vs I locked my phone down cause the cops were grabbing me.

To add to this, don’t use bio-metrics to lock your devices. Cops will “accidentally” use these to unlock devices when they are forcibly seized.

The quotation marks did most of the lifting there, and it’s more of an anecdote of their own projections against themselves. They assume these “welfare queens” are driving around in high end cars and living luxurious lifestyles on the governments dollar, while they are the ones doing such. Sorry if there was any confusion. I agree with all the statements you have stated against Brett Farve though, they are the scum of the system they wish to project onto others.

Despite texts that show Favre sought to keep his receipt of the funds confidential, Favre has said he didn’t know the money came from federal funds intended for poor people. He’s paid the money back, but he’s being sued by the state of Mississippi for hundreds of thousands of dollars in interest that accrued on the money he received. Favre hasn’t been accused of any criminal wrongdoing.

Source: (Yahoo News)

So they could easily of have funded this themselves, but just rather steal public funds because “free money”? Sounds like a so called “welfare queen” to me.

They really wanted it to feel like a Bethesda title proper.

Semi-cold? That’s extra, you’ll be lucky to afford it. The affordable water been sitting out on the pavement for a few weeks.

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.

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.

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.

TL;DR: The bot is configured to condense certain instances and communities. At the moment, only beehaw.org is marked to be condensed.

Quickly looking at the source code, it seems ReplyToPostsCommand uses a SummaryTextWrapper, which contains an iterable for both CondensedSummaryTextWrapperProvider and DefaultSummaryTextWrapperProvider. The DefaultSummaryTextWrapperProvider has a priority of -1_000 (so it’s always checked last) and is set to always return true on the supports(Community $community): bool. CondensedSummaryTextWrapperProvider references the config/services.yaml for it’s supports(Community $community): bool call which lists 0 condensed communities and 1 condensed instance, being beehaw.org.

If you are expecting a more windows-like experience, I would suggest using Ubuntu or Kubuntu (or any other distro using Gnome/KDE), as these are much closer to a modern Windows GUI. With Ubuntu, I can use the default file manager (nautilus) and do Ctrl+F and filter files via *.ext, then select these files then cut and paste to a new folder (drag and drop does not seem to work from the search results). In Kubuntu, the search doesn’t recognize * as a wildcard in KDE’s file manager (dolphin) but does support drag/drop between windows.

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.

Looking over the github issues I couldn’t find a feature request for this, so it seems like it’s not being considered at the moment. You could make a suggestion over there, I do think this feature would be useful but it’s up to the devs to implement it.

That being said, I wouldn’t count on this feature being implemented. This will only work on instances that obey the rules so some instances could remove this feature. When you look up your account on my instance (link here), it is up to my server to respect your option to hide your profile comments. This means the options have to be federated per-user, and adds a great deal of complexity to the system that can be easily thwarted by someone running an instance that chooses to not follow these rules.

If your goal is to stop people looking up historical activities, it might be best to use multiple accounts and switch to new accounts every so often to break up your history. You could also delete your content but this is again up to each instance to respect the deletion request. It’s not an optimal solutions but depending on your goals it is the available solution.

Edit: Also if your curious about the downvotes, it’s not the subject matter but your post violates Rule 3: Not regarding using or support for Lemmy.

Best I could find is here, which is an article by Randall Munroe (the xkcd artist), and states:

davean (the xkcd sysadmin) wrote the patch

This blog post links to another wayback machine page (thank you archive.org!) here, which explains the sorting algorithm and states it’s original author:

Fortunately, the math for this was worked out in 1927 by Edwin B. Wilson.

From Time (link: https://time.com/6133336/jan-6-capitol-riot-arrests-sentences/)

So far, the median prison sentence for the Jan. 6 rioters is 60 days, according to TIME’s calculation of the public records.

An additional 113 rioters have been sentenced to periods of home detention, while most sentences have included fines, community service and probation for low-level offenses like illegally parading or demonstrating in the Capitol, which is a misdemeanor.

Overall these people are getting less time than kids who get caught with some weed on them.

You can think you have rights, or you can know your rights, but when you violate the law don’t be surprised when one of the most pro-incarceration states around throw you in jail. Lots of protesters get arrested and prosecuted as a scare tactic. This is if you are assuming these people didn’t have seditious intentions, which does change things a bit. Overall sounds like they fucked around and found out, at least protesters fighting for real causes are more prepared to get fucked with by the state than these jokers.