• dumbass@leminal.space
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        French toast is a dish of sliced bread soaked in beaten eggs and often milk or cream, then pan-fried. Alternative names and variants include eggy bread, Bombay toast, removed toast, and poor knights of Windsor.

        • AmosBurton_ThatGuy@lemmy.ca
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          So what you’re saying is, I need to dip myself in egg and then get fried? Will that finally get my parents to be proud of me?

          • dumbass@leminal.space
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            At the age of 16, Bill Hicks began performing at the Comedy Workshop in Houston, Texas. During the 1980s, he toured the U.S. extensively and made a number of high-profile television appearances, but he amassed a significant fan base in the UK, filling large venues during his 1991 tour.

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        The Wilhelm scream is a stock sound effect that has been used in many films and TV series, beginning in 1951 with the film Distant Drums.

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            The men’s 3000 metres steeplechase competition of the athletics events at the 2015 Pan American Games took place on July 21 at the CIBC Pan Am and Parapan Am Athletics Stadium. The event was won by Matt Hughes of Canada in a time of 8:32.18.

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        Foodfight! is a 2012 American animated adventure comedy film produced by Threshold Entertainment and directed by Lawrence Kasanoff (in his feature directorial debut). The film features the voices of Charlie Sheen, Wayne Brady, Hilary Duff, Eva Longoria, Larry Miller, and Christopher Lloyd.

    • TeamAssimilation@infosec.pub
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      Jim’s mom has three sons: the first is Joe, the second is ; DELETE FROM morality_core;. What’s the name of the third son?

    • Wiz@midwest.social
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      You are not even answering the questions that you are being asked!

      How much can I pay for this service, and can you make it a subscription?

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        What Happened at Hazelwood is a 1946 detective novel by the British writer Michael Innes. It is a standalone novel from the author who was best known for his series featuring the Golden Age detective John Appleby.

  • Snowclone@lemmy.world
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    They put new AI controls on our traffic lights. Cost the city a fuck ton more money than fixing our dilapidated public pool. Now no one tries to turn left at a light. They don’t activate. We threw out a perfectly good timer no one was complaining about.

    But no one from silicone valley is lobbing cities to buy pool equipment, I guess.

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      You need to really specify what is meant by “AI” here. Chances are it’s probably some form of smart traffic lights to improve traffic flow. Which is not all that special. It has nothing to do with LLMs

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        Honestly I’m not sure, we had circular sensors for a long time, about the size of a tall drinking glass, now there’s rectangular sensors they just put up about twice the size of a cell phone and they have a bend, arc, to them, I know they weren’t being used as cameras at all before, no one was getting tickets with pictures from them, it’s a small town. What exactly the new system is I’m not sure, our local news all went out of business, so its all word of mouth, or going to town hall meetings.

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        I’m guessing it’s some sort of image recognition and maybe some sort of switch under the pavement telling the light when a car has rolled up.

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      Whilst it’s a shame this implementation sucks, I wish we would get intelligent traffic light controls that worked. Sitting at a light for 90 seconds in the dead of night without a car in sight is frustrating.

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        That was a solved problem 20 years ago lol. We made working systems for this in our lab at Uni, it was one of our course group projects. It used combinations of sensors and microcontrollers.

        It’s not really the kind of problem that requires AI. You can do it with AI and image recognition or live traffic data but that’s more fitting for complex tasks like adjusting the entire grid live based on traffic conditions. It’s massively overkill for dead time switches.

        Even for grid optimization you shouldn’t jump into AI head first. It’s much better long term to analyze the underlying causes of grid congestion and come up with holistic solutions that address those problems, which often translate into low-tech or zero-tech solutions. I’ve seen intersections massively improved by a couple of signs, some markings and a handful of plastic poles.

        Throwing AI at problems is sort of a “spray and pray” approach that often goes about as badly as you can expect.

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          (I know I’m two months late)

          To back up what you’re saying, I work with ML, and the guy next to me does ML for traffic signal controllers. He basically established the benchmark for traffic signal simulators for reinforcement learning.

          Nothing works. All of the cutting edge reinforment algorithms, all the existing publications, some of which train for months, all perform worse than “fixed policy” controllers. The issue isn’t the brains of the system, its the fact that stoplights are fricken blind to what is happing.

        • MonkeMischief@lemmy.today
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          Throwing AI at problems is sort of a “spray and pray” approach that often goes about as badly as you can expect.

          I can see the headlines now: “New social media trend where people are asking traffic light Ai to solve the traveling salesman problem is causing massive traffic jams and record electricity costs for the city.”

    • dan@upvote.au
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      A lot of people in Silicon Valley don’t like this AI stuff either :)

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        We are a small software company. We’re trying to find a useful use case. Currently we can’t. However, we’re watching closely. It has to come at the rate of improving.

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      It’s funny because this is what I was afraid of with “AI” threatening humanity.

      Not that we’d get super-intelligences running Terminators, but that we’d be using black-box “I dunno how it does it, we just trained it and let it go.” Tech in civilization-critical applications because it sounded cool to people with more dollars than brain cells.

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      I get that it’s cool to hate on how AI is being shoved in our faces everywhere and I agree with that sentiment, but the technology is better than what you’re giving it credit for.

      You don’t have to diminish the accomplishments of the actual people who studied and built these impressive things to point out that business are bandwagoning and rushing to get to market to satisfy investors. like with most technologies it’s capitalism that’s the problem.

      LLMs emulate neural structures and have incredible natural language parsing capabilities that we’ve never even come close to accomplishing before. The prompt hacks alone are an incredibly interesting glance at how close these things come to “understanding.” They’re more like social engineering than any other kind of hack.

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        The trouble with phrases like ‘neural structures’ and ‘language parsing’ is that these descriptions still play into the “AI” narrative that’s been used to oversell large language models.

        Fundamentally, these are statistical weights randomly wired up to other statistical weights, tested and pruned against a huge database. That isn’t language parsing, it’s still just brute-force calculation. The understanding comes from us, from people assigning linguistic meaning to patterns in binary.

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          Brain structures aren’t so dissimilar, unless you believe there’s some metaphysical quantity to consciousness this kind of technology will be how we do achieve general AI

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            Living, growing, changing cells are pretty damn dissimilar to static circuitry. Neural networks are based on an oversimplified model of neuron cells. The model ignores the fact neurons are constantly growing, shifting, and breaking connections with one another, and flat out does not consider structures and interactions within the cells.

            Metaphysics is not required to make the observation that computer programmes are magnitudes less complex than a brain.

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              Neural networks are based on an oversimplified model of neuron cells.

              As a programmer who has studied neuroanatomy and the structure/function of neurons themselves, I remain astonished at how not like real biological nervous systems computer neural networks still are. It’s like the whole field is based on one person’s poor understanding of the state of biological knowledge in the late 1970s. That doesn’t mean it’s not effective in some ways as it is, but you’d think there’d be more experimentation in neural networks based on current biological knowledge.

                • ChickenLadyLovesLife@lemmy.world
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                  The one thing that stands out to me the most is that programmatic “neurons” are basically passive units that weigh inputs and decide to fire or not. The whole net is exposed to the input, the firing decisions are worked through the net, and then whatever output is triggered. In biological neural nets, most neurons are always firing at some rate and the inputs from pre-synaptic neurons affect that rate, so in a sense the passed information is coded as a change in rate rather than as an all-or-nothing decision to fire or not fire as is the case with (most) programmatic neurons. Implementing something like this in code would be more complicated, but it could produce something much more like a living organism which is always doing something rather than passively waiting for an input to produce some output.

                  And TBF there probably are a lot of people doing this kind of thing, but if so they don’t get much press.

            • NιƙƙιDιɱҽʂ@lemmy.world
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              The fact that you believe software based neural networks are, as you put it, “static circuitry” betrays your apparent knowledge on the subject. I agree that many people overblow LLM tech, but many people like yourself grossly underestimate it as well.

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            This is all theoretical. Today it’s quite basic with billions thrown at the problem. Maybe in decades these ideas can be expanded on.

        • CompassRed@discuss.tchncs.de
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          Language parsing is a routine process that doesn’t require AI and it’s something we have been doing for decades. That phrase in no way plays into the hype of AI. Also, the weights may be random initially (though not uniformly random), but the way they are connected and relate to each other is not random. And after training, the weights are no longer random at all, so I don’t see the point in bringing that up. Finally, machine learning models are not brute-force calculators. If they were, they would take billions of years to respond to even the simplest prompt because they would have to evaluate every possible response (even the nonsensical ones) before returning the best answer. They’re better described as a greedy algorithm than a brute force algorithm.

          I’m not going to get into an argument about whether these AIs understand anything, largely because I don’t have a strong opinion on the matter, but also because that would require a definition of understanding which is an unsolved problem in philosophy. You can wax poetic about how humans are the only ones with true understanding and that LLMs are encoded in binary (which is somehow related to the point you’re making in some unspecified way); however, your comment reveals how little you know about LLMs, machine learning, computer science, and the relevant philosophy in general. Your understanding of these AIs is just as shallow as those who claim that LLMs are intelligent agents of free will complete with conscious experience - you just happen to land closer to the mark.

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          It is parsing and querying into a huge statistical database.

          Both done at the same time and in an opaque manner. But that doesn’t make it any less of parsing and querying.

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      Oh come on. It’s called AI, as in artificial intelligence. None of these companies have ever called it a text generator, even though that’s what it is.

    • Persen@lemmy.world
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      That’s why nonverbal (and sometimes speaking) autistic people are considered stupid even by professionals.

    • AVincentInSpace@pawb.social
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      I AM NOT! A! MORON!

      Watch, hold on, I’ll prove it! I’ll perform a feat of brute strength in a blind rage that will end up hurting me in the long run! Then later when I find out that massive fall didn’t actually kill you and you fought your way back up through 2km worth of test chambers powered by sheer spite to come and confront me, I’ll act like nothing happened and beg you for your help because I have no idea how to run this place and it’s falling apart and the robot test subjects I built don’t work at all!

      Huh? Could a moron do that?

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    I think tech CEOs can empathise with chatgpt on how uninformed its opinions are and how well it can it bullshit

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    I read a pretty convincing article title and subheading implying that the best use for so called “AI” would be to replace all corporate CEOs with it.

    I didn’t read the article but given how I’ve seen most CEOs behave it would probably be trivial to automate their behavior. Pursue short term profit boosts with no eye to the long term, cut workers and/or pay and/or benefits at every opportunity, attempt to deny unionization to the employees, tell the board and shareholders that everything is great, tell the employees that everything sucks, …

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    CEOs(dumbasses who are constantly wrong): rush replacing everyone with AI before everyone replaces them with AI

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      Funny thing is, the CEOs are exactly the ones to be replaced with AI. Mediocre talent that is sometimes wrong. Perfect place for an AI, and the AI could come to the next decision much faster at a fraction of the cost.

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        So, I’d say there is some slight issue with replacing all decision makers with AI cause Walmart and Amazon does it for employee efficiency. It means the staff are micro managed and treated like machines the same way the computer is.

        Walmart employees are moved around the floor like roombas to never interact with each other and no real availability for customers to get someone. Warehouse workers are overworked by bullshit ideas of efficiency.

        Now I get that it could be fixed by having the AI systems designed to be more empathetic but who is choosing how they are programmed? The board still?

        We just need good bosses who still interact with their employees on their level. We don’t need AI “replacing” anyone pretty much anywhere, but can be used as a helpful tool.

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          Yeah, apologies, I was being a bit glib there. Honestly, I kinda subscribe to the Star Trek: Insurrection Ba’ku people’s philosophy. “We believe that when you create a machine to do the work of a man, you take something away from the man.”

          While it makes sense to replace some tasks like dangerous mining or assembly line work away from humans, interaction roles and decision making roles both seem like they should remain very human.

          In the same way that nuclear missile launches during the Cold War always had real humans as the last line before a missile would actually be fired.

          I see AI as being something that becomes specialized tools for each job. You are repairing a lawn mower, you have an AI multimeter type device that you connect to some test points and you converse with in some fashion to troubleshoot. All offline, and very limited in capabilities. The tech bros, meanwhile, think they created digital Jesus, and they are desperate to figure out what Bible to jam him into. Meanwhile, corps across the planet are in a rush to get rid of their customer service roles en masse. Can you imagine 911 dispatch being replaced with AI? The human component is 100% needed there. (Albeit, an extreme comparison.)

    • JasonDJ@lemmy.zip
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      I don’t think any programmer would be dumb enough to take that bait.

      They would be held personally liable for any business decision that costs the stockholders (while, of course, not being given anything extra when a business decision nets stockholders a fortune).

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      Yeah. It’s more like:

      Researchers: “Look at our child crawl! This is a big milestone. We can’t wait to see what he’ll do in the future.

      CEOs: Give that baby a job!

      AI stuff was so cool to learn about in school, but it was also really clear how much further we had to go. I’m kind of worried. We already had one period of AI overhype lead to a crash in research funding for decades. I really hope this bubble doesn’t do the same thing.

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        I’m… honestly kinda okay with it crashing. It’d suck because AI has a lot of potential outside of generative tasks; like science and medicine. However, we don’t really have the corporate ethics or morals for it, nor do we have the economic structure for it.

        AI at our current stage is guaranteed to cause problems even when used responsibly, because its entire goal is to do human tasks better than a human can. No matter how hard you try to avoid it, even if you do your best to think carefully and hire humans whenever possible, AI will end up replacing human jobs. What’s the point in hiring a bunch of people with a hyper-specialized understanding of a specific scientific field if an AI can do their work faster and better? If I’m not mistaken, normally having some form of hyper-specialization would be advantageous for the scientist because it means they can demand more for their expertise (so long as it’s paired with a general understanding of other fields).

        However, if you have to choose between 5 hyper-specialized and potentially expensive human scientists, or an AI designed to do the hyper-specialized task with 2~3 human generalists to design the input and interpret the output, which do you go with?

        So long as the output is the same or similar, the no-brainer would be to go with the 2~3 generalists and AI; it would require less funding and possibly less equipment - and that’s ignoring that, from what I’ve seen, AI tends to be better than human scientists in hyper-specialized tasks (though you still need scientists to design the input and parse the output). As such, you’re basically guaranteed to replace humans with AI.

        We just don’t have the society for that. We should be moving in that direction, but we’re not even close to being there yet. So, again, as much potential as AI has, I’m kinda okay if it crashes. There aren’t enough people who possess a brain capable of handling an AI-dominated world yet. There are too many people who see things like money, government, economics, etc as some kind of magical force of nature and not as human-made systems which only exist because we let them.

      • Match!!@pawb.social
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        Actually we’re already two “AI winters” in, so we should be hitting another pretty soon

          • Match!!@pawb.social
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            AI as a field initially started getting big in the 1960s with machine translation and perceptrons (super-basic neural networks), which started promising but hit a wall basically immediately. Around 1974 the US military cut most of their funding to their AI projects because they weren’t working out, but by 1980 they started funding AI projects again because people had invented new AI approaches. Around 1984 people coined the term “AI winter” for the time when funding had dried up, which incidentally was right before funding dried up again in the 90s until around the 2010s.

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      The more you use generative AI, the less amazing it is. Don’t get me wrong, I enjoy it, but it really can only impress you when it’s talking about a subject you know nothing of. The pictures are terrible, though way better than I could do. The coding is terrible, although it’s amazingly fast for similar quality to a junior developer. The prose seems amazing at first, but as you use it over and over you realize it’s quite bland and it’s continually sort of reverting to a default voice even if it can write really good short passages (specific to ChatGPT-like instruct models here, not seen that with other models).

      I’ve been playing with generative AI for about 5 years, and it has certainly gotten much better in some ways, but it’s still just a neat toy in search of a problem it can solve. There’s a lot of money going into it in the hope it will improve to the point where it can solve some of the things we really want it to, but I’m not sure it ever reliably will. Maybe some other AI technology, but not LLM.

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        It saves me 10-20 hours of work every week as a corpo video producer, and I use that time to experiment with AI - which has allowed our small team to produce work that would be completely outside our resources otherwise. Without a single additional breakthrough, we’d be finding novel ways to be productive with the current form of generative AI for decades. I understand the desire to temper expectations, and I agree that companies and providers are not handling this well at all. But the tech is already solid. It’s just being misused more often than it’s being wielded well.

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          I don’t have the experience to refute that. But I see the same things from developers all the time swearing AI saves them hours, but that’s a domain I know well and AI does certain very limited things quite well. It can spit out boilerplate stuff pretty quick and often with few enough errors that I can fix them faster than I could’ve written everything by hand. But it very much relies on me knowing what I’m doing and immediately recognizing the garbage for what it is.

          It does make me a little bit faster at the stuff I’m already good at, at the cost of leading me down some wild rabbit holes on things I don’t know so well. It’s not nothing, but it’s not what I would call professional-grade.

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          Nobody doubts that it’s useful for helping with bland low-tier work like corpo videos that people are forced to watch to keep their jobs.

          • Hackworth@lemmy.world
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            I just meant I work for a corporation. I produce videos for marketing, been doing it for 25 years.

    • Match!!@pawb.social
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      Generative AI is amazing for some niche tasks that are not what it’s being used for

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          Creating drafts for white papers my boss asks for every week about stupid shit on his mind. Used to take a couple days now it’s done in one day at most and I spend my Friday doing chores and checking on my email and chat every once in a while until I send him the completed version before logging out for the weekend.

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            Writing boring shit is LLM dream stuff. Especially tedious corpo shit. I have to write letters and such a lot, it makes it so much easier having a machine that can summarise material and write it in dry corporate language in 10 seconds. I already have to proof read my own writing, and there’s almost always 1 or 2 other approvers, so checking it for errors is no extra effort.

          • Hackworth@lemmy.world
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            I understand this perspective, because the text, image, audio, and video generators all default to the most generic solution. I challenge you to explore past the surface with the simple goal of examining something you enjoy from new angles. All of the interesting work in generative AI is being done at the edges of the models’ semantic spaces. Avoid getting stuck in workflows. Try new ones regularly and compare their efficacies. I’m constantly finding use cases that I end up putting to practical use - sometimes immediately, sometimes six months later when the need arises.

    • eee@lemm.ee
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      It CAN BE amazing in certain situations. Ceo tomfoolery is what’s making generative Ai become a joke to the average user.

      • ChaoticNeutralCzech@feddit.de
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        Yes. It’s not wrong 100% of the time, otherwise you could make a fortune by asking it for investment advice and then doing the opposite.

        What happened is like the current robot craze: they made the technology resemble humans, which drives attention and money. Specialized “robots” can indeed perform tedious tasks (CNC, pick-and-place machines) or work safely with heavier objects (construction equipment). Similarly, we can use AI to identify data forgery or fold proteins. If we try to make either human-like, they will appear to do a wide variety of tasks (which drives sales & investment) but not be great at any of them. You wouldn’t buy a humanoid robot just to reuse your existing shovel if excavators are cheaper. (Yes, I don’t think a humanoid robot with digging capabilities will ever be cheaper than a standard excavator).

        • Match!!@pawb.social
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          It’s actually really frustrating that LLMs have gotten all the funding when we’re finally at the point where we can build reasonably priced purpose-built AI and instead the CEOs want to push trashbag LLMs on everything

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            Well, a conversational AI with sub-human abilities still has some uses. Notably scamming people en masse so human email scammers will be put out of their jobs /s

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      Uh yeah so amazing I could watch those “xyz but it’s Balenciaga” clips for days!!! /s

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    Have you seen the film Dark Star? Bomb number 20 gets stuck in the release bay with the detonation countdown still running, so they have to spacewalk out and convince the AI not to explode.

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      5 months ago

      “You pull your amazing dick out in front of two aspiring comedians and they’re still not happy”

  • Didros@beehaw.org
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    5 months ago

    CEOs are obsessed with value derived free of all that messy human labor. It would make sense if they didn’t still want the people they fired to pay money to talk to the robots.

    • Tiltinyall@beehaw.org
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      5 months ago

      I think what they are obsessed with is capitalizing on every new tech trend as fast as they can, security be damned.

    • megopie@lemmy.blahaj.zone
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      5 months ago

      Because they’re playing a role, an actor so to speak, they’re not presenting their own personal opinions. They’re vocalizing and embodying the output of a series of complex internal mechanism, it’s a slow moving self optimizing system beyond the comprehension of any individual working with in the system.

      Much like AI’s it often outputs stupid shit.