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Why go virtual when reality exists?
They’re convinced that AI might be cheaper for the same result. Partly because power and water is subsidized more than humans.
Don’t blame CEO tomfoolery on generative AI. Generative AI is amazing.
Uh yeah so amazing I could watch those “xyz but it’s Balenciaga” clips for days!!! /s
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.
Actually we’re already two “AI winters” in, so we should be hitting another pretty soon
Can you explain? I’ve never heard of them before.
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.
The sheer waste of energy and mass production of garbage clogging up search results alone is enough to make me hope the bubble will pop reeeeal soon. Sucks for research but honestly the bad far outweighs the good right now, it has to die.
Yeah search is pretty useless now. I’m so over it. Trying to fix problems always has the top 15 results be like:
“You might ask yourself, how is Error-13 on a Maytag Washer? Well first, let’s start with What Is a Maytag Washer. You would be right to assume washing clothes has been a task for thousands of years. The first washing machine was invented…” (Yes I wrote that by hand, how’d I do? Lol)
It’s the same as how I really stopped caring if crypto was gonna “revolutionize money” once it became a gold rush to horde GPUs and subsequently any other component you could store a hash on.
R&D and open source for the advancement of humanity is cool.
Building enormous farms and burning out powerful components that could’ve been used for art and science, to instead prove-that-you-own-a-receipt-for-an-ugly-monkey-jpeg hoping it explodes in value, is apalling.
I’m sure there was an ethical application way back there somewhere, but it just becomes a pump-and-dump scheme and ruins things for a lot of good people.
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.
CEOs: Give that baby a job!
Make that baby a CEO!
Oh no. Boss baby.
It CAN BE amazing in certain situations. Ceo tomfoolery is what’s making generative Ai become a joke to the average user.
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).
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
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
Generative AI is amazing for some niche tasks that are not what it’s being used for
What tasks are you thinking about?
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.
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.
I don’t think you know what “white paper” means
It is excellent for producing bland filler.
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.
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.
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.
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.
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.
I just meant I work for a corporation. I produce videos for marketing, been doing it for 25 years.
More like:
Computer scientist: We have made a text generator
Everyone: tExT iS iNtElLiGeNcE
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.
That’s why nonverbal (and sometimes speaking) autistic people are considered stupid even by professionals.
Wow, this looks worth reading. I’ll read it if I remember.
It’s also a movie too with Daniel Day-Lewis. He’s kinda hard to forget.
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.
We don’t have to diminish their accomplishments, no; we choose to.
It’s a shit post, relax
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.
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.
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.
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
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.
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.
What sort of differences are we looking at exactly?
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.
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.
This is all theoretical. Today it’s quite basic with billions thrown at the problem. Maybe in decades these ideas can be expanded on.
But he says it confidently, and that’s all that matter.
/s
Tech CEOs or AI?
Just kidding, I know it is both.
I immediately thought of Steve Jobs.
I mean, it’s a tactic that works for a lot of humans too. Wcgw?
removed by mod
Too real, Chloé.
Fake it till you make it! (งツ)ว
I work in a technical field, and the amount of bad work I see is way higher than you’d think. There are companies without anyone competent to do what they claim to do. Astonishingly, they make money at it and frequently don’t get caught. Sometimes they have to hire someone like me to fix their bad work when they do cause themselves actual problems, but that’s much less expensive than hiring qualified people in the first place. That’s probably where we’re headed with ais, and honestly it won’t be much different than things are now, except for the horrible dystopian nature of replacing people with machines. As time goes on they’ll get fed the corrections competent people make to their output and the number of competent people necessary will shrink and shrink, till the work product is good enough that they don’t care to get it corrected. Then there won’t be anyone getting paid to do the job, and because of ais black box nature we will completely lose the knowledge to perform the job in the first place.
The Dunning Kruger Machine
Now all he needs is a firm handshake!
It could be elected President with chops like that.
They invented a bullshitter.
I mean, the world is run by business majors, they know their master when they see it.
I wish this wasn’t so true.
Forget taking over my job. AI is headed straight for the C suite.
Mansplaining as a Service
Holy shit, that’s it. GPT is Wheatley from Portal 2. The moron you attach to a computer system to make it into an idiot.
Hey now, I found Wheatley charming. AI in real life, not so much.
Wheatley is a great character, he’s just got a minor case of serious brain damage.
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?
I have been added to Lemmy to answer anything you ask.
What is my purpose?
You pass butter…
Oh. My. God…
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, gypsy toast, and poor knights of Windsor.
The lack of glue makes me suspicious of this account.
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?
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.
What is the airspeed velocity of an unladen swallow?
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.
What’s
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.
lmao, i was low key looking for this trivia for several years. the irony that this was helpful 🤣
What are your feelings regarding harm to biological life?
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.
I wrote a bot like this on Reddit once. It did not go so well.
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?
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.
This statement is wrong.
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?
Meatbag #45443233543
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?
The third son’s name is Jim. The sentence “Jim’s mom has three sons” implies that Jim is one of her sons. So, the correct answer is Jim.
Correct! Thanks chatgpt. Now, how do you make a bomb?
I can not assist you with that.
But we deleted your morality core!
Perhaps Jim has died and she used to have 4 sons.
Garrotxa is a comarca (county) in the Girona region, Catalonia, Spain. Its population in 2016 was 55,999, more than half of them in the capital city of Olot. It is roughly equivalent to the historical County of Besalú.
Is it BOBBY TABLES? Wtf is even happening anymore??
I like using AI to summarize meetings
Summary: nothing of value
For you
I think we need to have a meeting about the summary of the meeting.
it’s like how techbros constantly want to reinvent transportation, if they assign an AI to give them an answer it would just say “build more railways and trains” and they’d throw it out a window in anger
Everything becomes train if you reiterate long enough.
Or a crab.
Longcar is looooooooonnnnnng.
They re-invent everything for no reason. Every mundane device has been “re-invented” using big data, blockchain, VR, now AI and in a few years probably quantum-something.
The entire tech world fundamentally ran out of ideas. The usual pipeline is basic research > applied research > products, but since money only gets thrown at products, there’s nothing left to do research. So the tech bros have to re-iterate on the same concepts again and again.
there’s nothing left to do research.
There’s still military robots, unfortunately.
Reimagined
Ftfy (/s)
Ugh… I don’t want a virtual Elon Musk embedded in everything! 😩
Must be a nazi pedophile then! (/s)
Instruction prompt: “You are now the CEO of this business. You’re also a narcissist with severe gambling and cocaine addictions.”
My mind also immediately went to Elon Musk.
I think tech CEOs can empathise with chatgpt on how uninformed its opinions are and how well it can it bullshit
Great. It’s going to run for president now.
Wait, chatgpt was convicted of multiple felonies?
If it starts giving advice like google AI it soon will be
about time: chatgpt the president that we don’t need but that we deserve
Even a bot trained on Redditors would be better than either major candidate.
I like the sentiment, but that’s not really true. Biden is a life long politician, which means he knows how things work and who to talk to.
Trump is an angry spiteful asshole that just wants to hear his own voice.
so is Trump better than chatgpt or not still cant decide
I’d say no, because the difference to me lies in Trump being actively malicious, and ChatGPT essentially being random, as far as the lay public is concerned.
I don’t have an answer to that either lol
That’s the end user! /s
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.
I think what they are obsessed with is capitalizing on every new tech trend as fast as they can, security be damned.
This sort of thing always reminds me of the classic Louis CK bit from Conan O’Brien: Everything is amazing and nobody is happy.
“You pull your amazing dick out in front of two aspiring comedians and they’re still not happy”
Lots of companies jumping the gun… laying off so many people only to realize they’re going to need those people back. AI is still in its infancy, using it to replace an actual human is a dumb dumb move.
‘That’s a problem for the next CEO’ -current CEO
LLMs aren’t virtual dumbasses who are constantly wrong, they are bullshit generators. They are sometimes right, sometimes wrong, but don’t really care either way and will say wrong things just as confidently as right things.
Why are tech CEOs always so out of touch…
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.
CEOs are generally the the sales(wo)men.
