I’m not usually impacted by celebrities but I was hit surprisingly hard by the death of John Bain aka TotalBiscuit on YouTube. Why? He just kind of seemed like a regular, fairly young gamer and decent dude who just wanted to let people know whether a game might be worth buying… and then suddenly surprise, cancer. A shit ton of treatment and four years later, gone. It just felt like a reminder that life is random and unfair.
More than enough people who claim to know how it works think it might be “evolving” into a sentient being inside it’s little black box. Example from a conversation I gave up on… https://sh.itjust.works/comment/18759960
That was an example of a situation where time zones make sense. Any time it is important where the sun is in the sky, the time that it occurs will differ depending on where you are in the world. When is lunch break? When do backups run? When can you see the eclipse? If we weren’t in an interconnected world, it wouldn’t matter much but we need some convention to communicate information that is dependent on where the sun is, as that very often dictates human activity.
It seems like a universal time makes sense but I can’t think of a way to get around the fact that activity will vary according to timezones anyway.
And there are no other external factors that could possibly influence their compensation besides their objective “worth” to the hiring organization?
Edit: To clarify, might personal bias from the employer lead to a higher compensation? If two CEOs are interviewed and one went to the same college as several members of the board, or if several members of the board know one personally, but the known CEO isn’t as accomplished… is it possible that the CEO benefitting from bias is going be hired? Will the benefitting CEO receive a lower compensation, higher compensation, or the same compensation?
Is it possible for a CEO to lie about their ability and get hired under false pretenses? Is it possible for a CEO to be hired for political or “public image” reasons rather than talent/productivity reasons? Are these reflected in their compensation?
I think the word “learning”, and even “training”, is an approximation from a human perspective. MLs “learn” by adjusting parameters when processing data. At least as far as I know, the base algorithm and hyperparameters for the model are set in stone.
The base algorithm for “living” things is basically only limited by chemistry/physics and evolution. I doubt anyone could create an algorithm that advanced any time soon. We don’t even understand the brain or physics at the quantum level that well. Hell, we are using ML to create new molecules because we don’t understand it well.
I suppose the context of condiment vs. ingredient is enough. I don’t think many recipes use ketchup/catsup and most meals don’t leave tomato sauce out to be used as a condiment.
What I consider ketchup/catsup includes much more sugar and vinegar than what I consider tomato sauce. Is that not the case where you are from or is there a different word used?
We should stop using time zones
Check this out. I’m a business with at least one office in every US state. You want to know when my New York office opens so you can come by. Instead of seeing “Offices are open 9 AM to 5 PM” You now need to check every office… by state… by city? Time zones would be helpful even if we all used GMT, so that you could easily determine which time zone a business is in to set a reasonable time to be open.
DST can fuck off though.
The actors and athletes get paid a lot because someone is willing to pay that money, and they are willing because only a miniscule part of humankind has exceptional skills/talent.
I see. So you are saying that every CEO is paid what they are worth?
I think you’re either being a little dismissive of the potential complexity of the “thinking” capability of LLMs or at least a little generous if not mystical in your imagination of what the purely physical electrical signals in our heads are actually doing to learn how to interpret all these little shapes we see on screens.
I don’t think I’m doing either of those things. I respect the scale and speed of the models and I am well aware that I’m little more than a machine made of meat.
Babies start out mimicking. The thing is, they learn.
Humans learn so much more before they start communicating. They start learning reason, logic, etc as they develop their vocabulary.
The difference is that, as I understand it, these models are often “trained” on very, very large sets of data. They have built a massive network of the way words are used in communication - likely built from more texts than a human could process in several lifetimes. They come out the gate with an enormous vocabulary and understanding of how to mimic, replicate it’s use. If they had been trained on just as much data, but data unrelated to communication, would you still think it capable of reasoning without the ability to “sound” human? They have the “vocabulary” and references to mimic a deep understanding but because we lack the ability to understand the final algorithm it seems like an enormous leap to presume actual reasoning is taking place.
Frankly, I see no reason for models like LLMs at this stage. I’m fine putting the breaks on this shit - even if we disagree on the reasons why. ML can and has been employed to achieve far more practical goals. Use it alongside humans for a while until it is verifiably more reliable at some task - recognizing cancer in imaging or generating molecules likely of achieving a desired goal. LLMs are just a lazy shortcut to look impressive and sell investors on the technology.
Maybe I am failing to see reality - maybe I don’t understand the latest “AI” well enough to give my two cents. That’s fine. I just think it’s being hyped because these companies desperately need VC money to stay afloat.
It works because humans have an insatiable desire to see agency everywhere they look. Spirits, monsters, ghosts, gods, and now “AI.”
Yes, both systems - the human brain and an LLM - assimilate and organize human written languages in order to use it for communication. An LLM is very little else beyond this. It is then given rules (using those written languages) and then designed to create more related words when given input. I just don’t find it convincing that an ML algorithm designed explicitly to mimic human written communication in response to given input “understands” anything. No matter *how convincingly" an algorithm might reproduce a human voice - perfectly matching intonation and inflexion when given text to read - if I knew it was an algorithm designed to do it as convincingly as possible I wouldn’t say it was capable of the feeling it is able to express.
The only thing in favor of sentience is that the ML algorithms modify themselves and end up being a black box - so complex with no way to represent them that they are impossible for humans to comprehend. Could it somehow have achieved sentience? Technically, yes, because we don’t understand how they work. We are just meat machines, after all.
LLMs (Large Language Modles, like Claude) are not AGIs (Artificial General Intelligence). LLMs generate convincing text by mapping the relationships between words scraped from their training data. Even if they are given “tools” that give them interfaces to reference new data or output data into other systems, they still don’t really learn, understand, comprehend, gain actual awareness, or feel… they just mimic their training data.
My interpretation of this might be different, but I agree wholeheartedly with my interpretation.
Being morally just doesn’t just mean “not causing harm” directly. It means striving to not cause harm both directly and indirectly. As someone who lives in the USA, our entire society is built off of exploitation. The less expensive something is, the more heavy the exploitation likely is. The cheapest manufacturing is done in countries where labor is exploited or even enslaved, where the manufacturing process can pollute and poison the area with little consequence (to the manufacturer), and where the powerful can force deals on the government to let them extract valuable resources and pay a fraction of its value - depriving the locals and nation prosperity. Even when buying US food products, the food industry mostly relies on extremely poor conditions for the animals it keeps, taking advantage of farmers it buys from or employs, and may even employ migrant children for dangerous slaughterhouse labor.
Avoiding these kinds of practices throughout most supply chains is sometimes impossible and usually more expensive the more thoroughly you manage to avoid the practices. Even then someone has to check in and constantly verify that the practices are legitimately avoided and not just greenwashing or fraudulent.
It’s really quite depressing.
Their Dogs Were Astronauts - Progressive, Djenty. Hard to pick a favorite track or album.
Opeth - Started as progressive death metal but they have gotten more chill and progressive and experimental over time. Favorites for me are Blackwater Park (on the harsher end of the spectrum), Windowpane (chill end of the spectrum), Reverie / Harlequin Forest.
It uh… actually doesn’t.
Thanks for being so detailed!
I use caddy for straightforward https, but every time I try to use it for a service that isn’t just a reverse_proxy entry, I really struggle to find resources I understand… and most of the time the “solutions” I find are outdated and don’t seem to work. The most recent example of this for me would be Baikal.
Do you have any recommendations for where I might get good examples and learn more about how do troubleshoot and improve my Caddyfile entries?
Thanks!
I replied to the following statement:
I could look up my dad’s name and all I get are articles about a serial killer who just happened to have the same name
I countered this dismissal by quoting the article, which explains that it was more than just a coincidental name mix up.
You response is not really relevant to my response, unless you are assuming I’m arguing for one side or the other. I’m just informing someone who dismissed the article’s headline using an explanation that demonstrated that they didn’t bother to read the article.
Nothing is wrong with the tech (except it doesn’t seem very useful when you firmly know what it can’t do), but everything is wrong with that tech being called artificial intelligence.
If the owners of the technology call it artificial intelligence and hype or sell it as a potential replacement for intelligent human decision making then it should be absolutely be judged on those grounds.
ChatGPT’s “made-up horror story” not only hallucinated events that never happened, but it also mixed “clearly identifiable personal data”—such as the actual number and gender of Holmen’s children and the name of his hometown—with the “fake information,” Noyb’s press release said.
Don’t know about getting money back, but it is something of a coop. My link includes a recommendation to vote “withhold” in the current election, why they recommend the action, and how to do so.
Clearly the author doesn’t understand how capitalism works. If Apple can pick you up by the neck, turn you upside down, and shake whatever extra money it can from you then it absolutely will do so.
The problem is that one indie developer doesn’t have any power over Apple… so they can go fuck themselves. The developer is granted the opportunity to grovel at the feet of their betters (richers) and pray that they are allowed to keep enough of their own crop to survive the winter. If they don’t survive… then some other dev will probably jump at the chance to take part in the “free market” and demonstrate their worth.